Trends in life science grid: from computing grid to knowledge grid.

PubMed

Konagaya, Akihiko

2006-12-18

Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

Trends in life science grid: from computing grid to knowledge grid

PubMed Central

Konagaya, Akihiko

2006-01-01

Background Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. Results This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Conclusion Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community. PMID:17254294

The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences.

PubMed

Merchant, Nirav; Lyons, Eric; Goff, Stephen; Vaughn, Matthew; Ware, Doreen; Micklos, David; Antin, Parker

2016-01-01

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant's platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses.

CDC Vital Signs: Alcohol Screening and Counseling

MedlinePlus

... these services in state and community programs, using computers, smartphones, and other electronic devices. Help conduct community ... be made worse by drinking. Top of Page Science Behind the Issue MMWR Science Clips Related Pages ...

CAL-laborate: A Collaborative Publication on the Use of Computer Aided Learning for Tertiary Level Physical Sciences and Geosciences.

ERIC Educational Resources Information Center

Fernandez, Anne, Ed.; Sproats, Lee, Ed.; Sorensen, Stacey, Ed.

2000-01-01

The science community has been trying to use computers in teaching for many years. There has been much conformity in how this was to be achieved, and the wheel has been re-invented again and again as enthusiast after enthusiast has "done their bit" towards getting computers accepted. Computers are now used by science undergraduates (as well as…

Sustaining and Extending the Open Science Grid: Science Innovation on a PetaScale Nationwide Facility (DE-FC02-06ER41436) SciDAC-2 Closeout Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Livny, Miron; Shank, James; Ernst, Michael

Under this SciDAC-2 grant the project’s goal w a s t o stimulate new discoveries by providing scientists with effective and dependable access to an unprecedented national distributed computational facility: the Open Science Grid (OSG). We proposed to achieve this through the work of the Open Science Grid Consortium: a unique hands-on multi-disciplinary collaboration of scientists, software developers and providers of computing resources. Together the stakeholders in this consortium sustain and use a shared distributed computing environment that transforms simulation and experimental science in the US. The OSG consortium is an open collaboration that actively engages new research communities. Wemore » operate an open facility that brings together a broad spectrum of compute, storage, and networking resources and interfaces to other cyberinfrastructures, including the US XSEDE (previously TeraGrid), the European Grids for ESciencE (EGEE), as well as campus and regional grids. We leverage middleware provided by computer science groups, facility IT support organizations, and computing programs of application communities for the benefit of consortium members and the US national CI.« less

Impacts | Computational Science | NREL

Science.gov Websites

Impacts Impacts Read about the impacts of NREL's innovations in computational science. Awards community. Photo of the Peregrine supercomputer 2014 R&D 100 Award and R&D Magazine Editor's Choice

The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences

PubMed Central

Merchant, Nirav; Lyons, Eric; Goff, Stephen; Vaughn, Matthew; Ware, Doreen; Micklos, David; Antin, Parker

2016-01-01

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant’s platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses. PMID:26752627

A Computer Science Educational Program for Establishing an Entry Point into the Computing Community of Practice

ERIC Educational Resources Information Center

Haberman, Bruria; Yehezkel, Cecile

2008-01-01

The rapid evolvement of the computing domain has posed challenges in attempting to bridge the gap between school and the contemporary world of computing, which is related to content, learning culture, and professional norms. We believe that the interaction of high-school students who major in computer science or software engineering with leading…

Community College Men and Women: A Test of Three Widely Held Beliefs about Who Pursues Computer Science

ERIC Educational Resources Information Center

Denner, Jill; Werner, Linda; O'Connor, Lisa; Glassman, Jill

2014-01-01

Efforts to increase the number of women who pursue and complete advanced degrees in computer and information sciences (CIS) have been limited, in part, by a lack of research on pathways into and out of community college CIS classes. This longitudinal study tests three widely held beliefs about how to increase the number of CIS majors at 4-year…

Community Information Centers and the Computer.

ERIC Educational Resources Information Center

Carroll, John M.; Tague, Jean M.

Two computer data bases have been developed by the Computer Science Department at the University of Western Ontario for "Information London," the local community information center. One system, called LONDON, permits Boolean searches of a file of 5,000 records describing human service agencies in the London area. The second system,…

A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Liu, Shu-Guang; Nichols, Erin; Haga, Jim; Maddox, Brian; Bilderback, Chris; Feller, Mark; Homer, George

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost, personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting information science research into parallel computing systems and applications.

Reconfigurable Computing for Computational Science: A New Focus in High Performance Computing

DTIC Science & Technology

2006-11-01

in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more...complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been “free” with increased...the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and

An Overview of NASA's Intelligent Systems Program

NASA Technical Reports Server (NTRS)

Cooke, Daniel E.; Norvig, Peter (Technical Monitor)

2001-01-01

NASA and the Computer Science Research community are poised to enter a critical era. An era in which - it seems - that each needs the other. Market forces, driven by the immediate economic viability of computer science research results, place Computer Science in a relatively novel position. These forces impact how research is done, and could, in worst case, drive the field away from significant innovation opting instead for incremental advances that result in greater stability in the market place. NASA, however, requires significant advances in computer science research in order to accomplish the exploration and science agenda it has set out for itself. NASA may indeed be poised to advance computer science research in this century much the way it advanced aero-based research in the last.

Students' Attitudes toward Computers at the College of Nursing at King Saud University (KSU)

ERIC Educational Resources Information Center

Samarkandi, Osama Abdulhaleem

2011-01-01

Computer knowledge and skills are becoming essential components technology in nursing education. Saudi nurses must be prepared to utilize these technologies for the advancement of science and nursing practice in local and global communities. Little attention has been directed to students' attitudes about computer usage in academic communities in…

Designing a Curriculum for Computer Students in the Community College.

ERIC Educational Resources Information Center

Kolatis, Maria

An overview is provided of the institutional and technological factors to be considered in designing or updating a computer science curriculum at the community college level. After underscoring the importance of the computer in today's society, the paper identifies and discusses the following considerations in curriculum design: (1) the mission of…

INDIGO-DataCloud solutions for Earth Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Fiore, Sandro; Monna, Stephen; Chen, Yin

2017-04-01

INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is a European Commission funded project aiming to develop a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The development of INDIGO solutions covers the different layers in cloud computing (IaaS, PaaS, SaaS), and provides tools to exploit resources like HPC or GPGPUs. INDIGO is oriented to support European Scientific research communities, that are well represented in the project. Twelve different Case Studies have been analyzed in detail from different fields: Biological & Medical sciences, Social sciences & Humanities, Environmental and Earth sciences and Physics & Astrophysics. INDIGO-DataCloud provides solutions to emerging challenges in Earth Science like: -Enabling an easy deployment of community services at different cloud sites. Many Earth Science research infrastructures often involve distributed observation stations across countries, and also have distributed data centers to support the corresponding data acquisition and curation. There is a need to easily deploy new data center services while the research infrastructure continuous spans. As an example: LifeWatch (ESFRI, Ecosystems and Biodiversity) uses INDIGO solutions to manage the deployment of services to perform complex hydrodynamics and water quality modelling over a Cloud Computing environment, predicting algae blooms, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator for deployment, AAI (AuthN, AuthZ) and OneData (Distributed Storage System). -Supporting Big Data Analysis. Nowadays, many Earth Science research communities produce large amounts of data and and are challenged by the difficulties of processing and analysing it. A climate models intercomparison data analysis case study for the European Network for Earth System Modelling (ENES) community has been setup, based on the Ophidia big data analysis framework and the Kepler workflow management system. Such services normally involve a large and distributed set of data and computing resources. In this regard, this case study exploits the INDIGO PaaS for a flexible and dynamic allocation of the resources at the infrastructural level. -Providing Distributed Data Storage Solutions. In order to allow scientific communities to perform heavy computation on huge datasets, INDIGO provides global data access solutions allowing researchers to access data in a distributed environment like fashion regardless of its location, and also to publish and share their research results with public or close communities. INDIGO solutions that support the access to distributed data storage (OneData) are being tested on EMSO infrastructure (Ocean Sciences and Geohazards) data. Another aspect of interest for the EMSO community is in efficient data processing by exploiting INDIGO services like PaaS Orchestrator. Further, for HPC exploitation, a new solution named Udocker has been implemented, enabling users to execute docker containers in supercomputers, without requiring administration privileges. This presentation will overview INDIGO solutions that are interesting and useful for Earth science communities and will show how they can be applied to other Case Studies.

The iPlant collaborative: cyberinfrastructure for enabling data to discovery for the life sciences

USDA-ARS?s Scientific Manuscript database

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identify management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning m...

Spice Products Available to The Planetary Science Community

NASA Technical Reports Server (NTRS)

Acton, Charles

1999-01-01

This paper presents the availability of SPICE products to the Planetary Science Community. The topics include: 1) What Are SPICE Data; 2) SPICE File Types; 3) SPICE Software; 4) Examples of What Can Be Computed Using SPICE Data and Software; and 5) SPICE File Avalability.

Community Based Informatics: Geographical Information Systems, Remote Sensing and Ontology collaboration - A technical hands-on approach

NASA Astrophysics Data System (ADS)

Branch, B. D.; Raskin, R. G.; Rock, B.; Gagnon, M.; Lecompte, M. A.; Hayden, L. B.

2009-12-01

With the nation challenged to comply with Executive Order 12906 and its needs to augment the Science, Technology, Engineering and Mathematics (STEM) pipeline, applied focus on geosciences pipelines issue may be at risk. The Geosciences pipeline may require intentional K-12 standard course of study consideration in the form of project based, science based and evidenced based learning. Thus, the K-12 to geosciences to informatics pipeline may benefit from an earth science experience that utilizes a community based “learning by doing” approach. Terms such as Community GIS, Community Remotes Sensing, and Community Based Ontology development are termed Community Informatics. Here, approaches of interdisciplinary work to promote and earth science literacy are affordable, consisting of low cost equipment that renders GIS/remote sensing data processing skills necessary in the workforce. Hence, informal community ontology development may evolve or mature from a local community towards formal scientific community collaboration. Such consideration may become a means to engage educational policy towards earth science paradigms and needs, specifically linking synergy among Math, Computer Science, and Earth Science disciplines.

A Study of Attrition and the Use of Student Learning Communities in the Computer Science Introductory Programming Sequence

ERIC Educational Resources Information Center

Howles, Trudy

2009-01-01

Student attrition and low graduation rates are critical problems in computer science education. Disappointing graduation rates and declining student interest have caught the attention of business leaders, researchers and universities. With weak graduation rates and little interest in scientific computing, many are concerned about the USA's ability…

Pedagogy Matters: Engaging Diverse Students as Community Researchers in Three Computer Science Classrooms

ERIC Educational Resources Information Center

Ryoo, Jean Jinsun

2013-01-01

Computing occupations are among the fastest growing in the U.S. and technological innovations are central to solving world problems. Yet only our most privileged students are learning to use technology for creative purposes through rigorous computer science education opportunities. In order to increase access for diverse students and females who…

Becoming Responsible Learners: Community Matters

ERIC Educational Resources Information Center

Wiersema, Janice A.; Licklider, Barbara L.; Ebbers, Larry

2013-01-01

Students at Iowa State University had the opportunity to enroll in a two-year National Science Foundation (NFS) Scholarship for Service (SFS) leadership development program, in addition to their work within their majors. This interdisciplinary program included faculty and students in computer engineering, computer science, mathematics, political…

Situated Learning in Computer Science Education

ERIC Educational Resources Information Center

Ben-Ari, Mordechai

2004-01-01

Sociocultural theories of learning such as Wenger and Lave's situated learning have been suggested as alternatives to cognitive theories of learning like constructivism. This article examines situated learning within the context of computer science (CS) education. Situated learning accurately describes some CS communities like open-source software…

Information technology developments within the national biological information infrastructure

USGS Publications Warehouse

Cotter, G.; Frame, M.T.

2000-01-01

Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

Report on Computing and Networking in the Space Science Laboratory by the SSL Computer Committee

NASA Technical Reports Server (NTRS)

Gallagher, D. L. (Editor)

1993-01-01

The Space Science Laboratory (SSL) at Marshall Space Flight Center is a multiprogram facility. Scientific research is conducted in four discipline areas: earth science and applications, solar-terrestrial physics, astrophysics, and microgravity science and applications. Representatives from each of these discipline areas participate in a Laboratory computer requirements committee, which developed this document. The purpose is to establish and discuss Laboratory objectives for computing and networking in support of science. The purpose is also to lay the foundation for a collective, multiprogram approach to providing these services. Special recognition is given to the importance of the national and international efforts of our research communities toward the development of interoperable, network-based computer applications.

PREPARING FOR EXASCALE: ORNL Leadership Computing Application Requirements and Strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joubert, Wayne; Kothe, Douglas B; Nam, Hai Ah

2009-12-01

In 2009 the Oak Ridge Leadership Computing Facility (OLCF), a U.S. Department of Energy (DOE) facility at the Oak Ridge National Laboratory (ORNL) National Center for Computational Sciences (NCCS), elicited petascale computational science requirements from leading computational scientists in the international science community. This effort targeted science teams whose projects received large computer allocation awards on OLCF systems. A clear finding of this process was that in order to reach their science goals over the next several years, multiple projects will require computational resources in excess of an order of magnitude more powerful than those currently available. Additionally, for themore » longer term, next-generation science will require computing platforms of exascale capability in order to reach DOE science objectives over the next decade. It is generally recognized that achieving exascale in the proposed time frame will require disruptive changes in computer hardware and software. Processor hardware will become necessarily heterogeneous and will include accelerator technologies. Software must undergo the concomitant changes needed to extract the available performance from this heterogeneous hardware. This disruption portends to be substantial, not unlike the change to the message passing paradigm in the computational science community over 20 years ago. Since technological disruptions take time to assimilate, we must aggressively embark on this course of change now, to insure that science applications and their underlying programming models are mature and ready when exascale computing arrives. This includes initiation of application readiness efforts to adapt existing codes to heterogeneous architectures, support of relevant software tools, and procurement of next-generation hardware testbeds for porting and testing codes. The 2009 OLCF requirements process identified numerous actions necessary to meet this challenge: (1) Hardware capabilities must be advanced on multiple fronts, including peak flops, node memory capacity, interconnect latency, interconnect bandwidth, and memory bandwidth. (2) Effective parallel programming interfaces must be developed to exploit the power of emerging hardware. (3) Science application teams must now begin to adapt and reformulate application codes to the new hardware and software, typified by hierarchical and disparate layers of compute, memory and concurrency. (4) Algorithm research must be realigned to exploit this hierarchy. (5) When possible, mathematical libraries must be used to encapsulate the required operations in an efficient and useful way. (6) Software tools must be developed to make the new hardware more usable. (7) Science application software must be improved to cope with the increasing complexity of computing systems. (8) Data management efforts must be readied for the larger quantities of data generated by larger, more accurate science models. Requirements elicitation, analysis, validation, and management comprise a difficult and inexact process, particularly in periods of technological change. Nonetheless, the OLCF requirements modeling process is becoming increasingly quantitative and actionable, as the process becomes more developed and mature, and the process this year has identified clear and concrete steps to be taken. This report discloses (1) the fundamental science case driving the need for the next generation of computer hardware, (2) application usage trends that illustrate the science need, (3) application performance characteristics that drive the need for increased hardware capabilities, (4) resource and process requirements that make the development and deployment of science applications on next-generation hardware successful, and (5) summary recommendations for the required next steps within the computer and computational science communities.« less

ASCR Workshop on Quantum Computing for Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aspuru-Guzik, Alan; Van Dam, Wim; Farhi, Edward

This report details the findings of the DOE ASCR Workshop on Quantum Computing for Science that was organized to assess the viability of quantum computing technologies to meet the computational requirements of the DOE’s science and energy mission, and to identify the potential impact of quantum technologies. The workshop was held on February 17-18, 2015, in Bethesda, MD, to solicit input from members of the quantum computing community. The workshop considered models of quantum computation and programming environments, physical science applications relevant to DOE's science mission as well as quantum simulation, and applied mathematics topics including potential quantum algorithms formore » linear algebra, graph theory, and machine learning. This report summarizes these perspectives into an outlook on the opportunities for quantum computing to impact problems relevant to the DOE’s mission as well as the additional research required to bring quantum computing to the point where it can have such impact.« less

Joint the Center for Applied Scientific Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, Todd; Bremer, Timo; Van Essen, Brian

The Center for Applied Scientific Computing serves as Livermore Lab’s window to the broader computer science, computational physics, applied mathematics, and data science research communities. In collaboration with academic, industrial, and other government laboratory partners, we conduct world-class scientific research and development on problems critical to national security. CASC applies the power of high-performance computing and the efficiency of modern computational methods to the realms of stockpile stewardship, cyber and energy security, and knowledge discovery for intelligence applications.

Transformative Connections: Community-Based K-12 Computing Program Strives to Strengthen Academic and Career Aspirations of Its Participants

ERIC Educational Resources Information Center

Roach, Ronald

2005-01-01

The Joint Educational Facilities Inc. (JEF) computer science program has as its goal to acquaint minority and socially disadvantaged K-12 students with computer science basics and the innovative subdisciplines within the field, and to reinforce the college ambitions of participants or help them consider college as an option. A non-profit…

Dropping Out of Computer Science: A Phenomenological Study of Student Lived Experiences in Community College Computer Science

NASA Astrophysics Data System (ADS)

Gilbert-Valencia, Daniel H.

California community colleges contribute alarmingly few computer science degree or certificate earners. While the literature shows clear K-12 impediments to CS matriculation in higher education, very little is known about the experiences of those who overcome initial impediments to CS yet do not persist through to program completion. This phenomenological study explores insights into that specific experience by interviewing underrepresented, low income, first-generation college students who began community college intending to transfer to 4-year institutions majoring in CS but switched to another field and remain enrolled or graduated. This study explores the lived experiences of students facing barriers, their avenues for developing interest in CS, and the persistence support systems they encountered, specifically looking at how students constructed their academic choice from these experiences. The growing diversity within California's population necessitates that experiences specific to underrepresented students be considered as part of this exploration. Ten semi-structured interviews and observations were conducted, transcribed and coded. Artifacts supporting student experiences were also collected. Data was analyzed through a social-constructivist lens to provide insight into experiences and how they can be navigated to create actionable strategies for community college computer science departments wishing to increase student success. Three major themes emerged from this research: (1) students shared pre-college characteristics; (2) faced similar challenges in college CS courses; and (3) shared similar reactions to the "work" of computer science. Results of the study included (1) CS interest development hinged on computer ownership in the home; (2) participants shared characteristics that were ideal for college success but not CS success; and (3) encounters in CS departments produced unique challenges for participants. Though CS interest was and remains abundant, opportunities for learning programming skills before college were non-existent and there were few opportunities in college to build skills or establish a peer support networks. Recommendations for institutional leaders and further research are also provided.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

NASA Astrophysics Data System (ADS)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

2014-06-01

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared overmore » the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.« less

Data handling and visualization for NASA's science programs

NASA Technical Reports Server (NTRS)

Bredekamp, Joseph H. (Editor)

1995-01-01

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Grids: The Top Ten Questions

DOE PAGES

Schopf, Jennifer M.; Nitzberg, Bill

2002-01-01

The design and implementation of a national computing system and data grid has become a reachable goal from both the computer science and computational science point of view. A distributed infrastructure capable of sophisticated computational functions can bring many benefits to scientific work, but poses many challenges, both technical and socio-political. Technical challenges include having basic software tools, higher-level services, functioning and pervasive security, and standards, while socio-political issues include building a user community, adding incentives for sites to be part of a user-centric environment, and educating funding sources about the needs of this community. This paper details the areasmore » relating to Grid research that we feel still need to be addressed to fully leverage the advantages of the Grid.« less

The Difficult Bridge between University and Industry: A Case Study in Computer Science Teaching

ERIC Educational Resources Information Center

Schilling, Jan; Klamma, Ralf

2010-01-01

Recently, there has been increasing criticism concerning academic computer science education. This paper presents a new approach based on the principles of constructivist learning design as well as the ideas of knowledge transfer in communities of practice. The course "High-tech Entrepreneurship and New Media" was introduced as an…

Astronomy and Computing: A new journal for the astronomical computing community

NASA Astrophysics Data System (ADS)

Accomazzi, Alberto; Budavári, Tamás; Fluke, Christopher; Gray, Norman; Mann, Robert G.; O'Mullane, William; Wicenec, Andreas; Wise, Michael

2013-02-01

We introduce Astronomy and Computing, a new journal for the growing population of people working in the domain where astronomy overlaps with computer science and information technology. The journal aims to provide a new communication channel within that community, which is not well served by current journals, and to help secure recognition of its true importance within modern astronomy. In this inaugural editorial, we describe the rationale for creating the journal, outline its scope and ambitions, and seek input from the community in defining in detail how the journal should work towards its high-level goals.

REVIEW OF THE GOVERNING EQUATIONS, COMPUTATIONAL ALGORITHMS, AND OTHER COMPONENTS OF THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

Opportunities for Computational Discovery in Basic Energy Sciences

NASA Astrophysics Data System (ADS)

Pederson, Mark

2011-03-01

An overview of the broad-ranging support of computational physics and computational science within the Department of Energy Office of Science will be provided. Computation as the third branch of physics is supported by all six offices (Advanced Scientific Computing, Basic Energy, Biological and Environmental, Fusion Energy, High-Energy Physics, and Nuclear Physics). Support focuses on hardware, software and applications. Most opportunities within the fields of~condensed-matter physics, chemical-physics and materials sciences are supported by the Officeof Basic Energy Science (BES) or through partnerships between BES and the Office for Advanced Scientific Computing. Activities include radiation sciences, catalysis, combustion, materials in extreme environments, energy-storage materials, light-harvesting and photovoltaics, solid-state lighting and superconductivity.~ A summary of two recent reports by the computational materials and chemical communities on the role of computation during the next decade will be provided. ~In addition to materials and chemistry challenges specific to energy sciences, issues identified~include a focus on the role of the domain scientist in integrating, expanding and sustaining applications-oriented capabilities on evolving high-performance computing platforms and on the role of computation in accelerating the development of innovative technologies. ~~

Computational Accelerator Physics. Proceedings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bisognano, J.J.; Mondelli, A.A.

1997-04-01

The sixty two papers appearing in this volume were presented at CAP96, the Computational Accelerator Physics Conference held in Williamsburg, Virginia from September 24{minus}27,1996. Science Applications International Corporation (SAIC) and the Thomas Jefferson National Accelerator Facility (Jefferson lab) jointly hosted CAP96, with financial support from the U.S. department of Energy`s Office of Energy Research and the Office of Naval reasearch. Topics ranged from descriptions of specific codes to advanced computing techniques and numerical methods. Update talks were presented on nearly all of the accelerator community`s major electromagnetic and particle tracking codes. Among all papers, thirty of them are abstracted formore » the Energy Science and Technology database.(AIP)« less

Communities Count: Community Based Sourcebook for Promoting Mathematics & Science Education.

ERIC Educational Resources Information Center

Crespo, Hilda; Cid, Nadine

In the increasingly technological workforce, greater competency in mathematics, science, and computers among Latino and other minority students takes on a new urgency. Hispanic Americans are a vital pool of workers to tap for the nation's future growth. Schools must ensure that Hispanic Americans have the skills they need to enter the labor force…

NASA Center for Climate Simulation (NCCS) Advanced Technology AT5 Virtualized Infiniband Report

NASA Technical Reports Server (NTRS)

Thompson, John H.; Bledsoe, Benjamin C.; Wagner, Mark; Shakshober, John; Fromkin, Russ

2013-01-01

The NCCS is part of the Computational and Information Sciences and Technology Office (CISTO) of Goddard Space Flight Center's (GSFC) Sciences and Exploration Directorate. The NCCS's mission is to enable scientists to increase their understanding of the Earth, the solar system, and the universe by supplying state-of-the-art high performance computing (HPC) solutions. To accomplish this mission, the NCCS (https://www.nccs.nasa.gov) provides high performance compute engines, mass storage, and network solutions to meet the specialized needs of the Earth and space science user communities

Soccer science and the Bayes community: exploring the cognitive implications of modern scientific communication.

PubMed

Shrager, Jeff; Billman, Dorrit; Convertino, Gregorio; Massar, J P; Pirolli, Peter

2010-01-01

Science is a form of distributed analysis involving both individual work that produces new knowledge and collaborative work to exchange information with the larger community. There are many particular ways in which individual and community can interact in science, and it is difficult to assess how efficient these are, and what the best way might be to support them. This paper reports on a series of experiments in this area and a prototype implementation using a research platform called CACHE. CACHE both supports experimentation with different structures of interaction between individual and community cognition and serves as a prototype for computational support for those structures. We particularly focus on CACHE-BC, the Bayes community version of CACHE, within which the community can break up analytical tasks into "mind-sized" units and use provenance tracking to keep track of the relationship between these units. Copyright © 2009 Cognitive Science Society, Inc.

Earth System Grid II, Turning Climate Datasets into Community Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Middleton, Don

2006-08-01

The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects,more » we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.« less

Using Visual Technologies in the Introductory Programming Courses for Computer Science Majors

ERIC Educational Resources Information Center

Price, Kellie W.

2013-01-01

Decreasing enrollments, lower rates of student retention and changes in the learning styles of today's students are all issues that the Computer Science (CS) academic community is currently facing. As a result, CS educators are being challenged to find the right blend of technology and pedagogy for their curriculum in order to help students…

High Performance Computing and Network Program. Hearing before the Subcommittee on Science of the Committee on Science, Space, and Technology, House of Representatives, One Hundred Third Congress, First Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science, Space and Technology.

The purpose of the hearing transcribed in this document was to obtain the views of representatives of network user and provider communities regarding the path the National Science Foundation (NSF) is taking for recompetition of the NSFNET computer network. In particular the committee was interested in the consistency of the evolution of NSFNET…

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

PubMed Central

Duarte, Afonso M. S.; Psomopoulos, Fotis E.; Blanchet, Christophe; Bonvin, Alexandre M. J. J.; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C.; de Lucas, Jesus M.; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B.

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community. PMID:26157454

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis.

PubMed

Duarte, Afonso M S; Psomopoulos, Fotis E; Blanchet, Christophe; Bonvin, Alexandre M J J; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C; de Lucas, Jesus M; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

Computational Infrastructure for Geodynamics (CIG)

NASA Astrophysics Data System (ADS)

Gurnis, M.; Kellogg, L. H.; Bloxham, J.; Hager, B. H.; Spiegelman, M.; Willett, S.; Wysession, M. E.; Aivazis, M.

2004-12-01

Solid earth geophysicists have a long tradition of writing scientific software to address a wide range of problems. In particular, computer simulations came into wide use in geophysics during the decade after the plate tectonic revolution. Solution schemes and numerical algorithms that developed in other areas of science, most notably engineering, fluid mechanics, and physics, were adapted with considerable success to geophysics. This software has largely been the product of individual efforts and although this approach has proven successful, its strength for solving problems of interest is now starting to show its limitations as we try to share codes and algorithms or when we want to recombine codes in novel ways to produce new science. With funding from the NSF, the US community has embarked on a Computational Infrastructure for Geodynamics (CIG) that will develop, support, and disseminate community-accessible software for the greater geodynamics community from model developers to end-users. The software is being developed for problems involving mantle and core dynamics, crustal and earthquake dynamics, magma migration, seismology, and other related topics. With a high level of community participation, CIG is leveraging state-of-the-art scientific computing into a suite of open-source tools and codes. The infrastructure that we are now starting to develop will consist of: (a) a coordinated effort to develop reusable, well-documented and open-source geodynamics software; (b) the basic building blocks - an infrastructure layer - of software by which state-of-the-art modeling codes can be quickly assembled; (c) extension of existing software frameworks to interlink multiple codes and data through a superstructure layer; (d) strategic partnerships with the larger world of computational science and geoinformatics; and (e) specialized training and workshops for both the geodynamics and broader Earth science communities. The CIG initiative has already started to leverage and develop long-term strategic partnerships with open source development efforts within the larger thrusts of scientific computing and geoinformatics. These strategic partnerships are essential as the frontier has moved into multi-scale and multi-physics problems in which many investigators now want to use simulation software for data interpretation, data assimilation, and hypothesis testing.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter.

PubMed

Schmitt, Marco; Jäschke, Robert

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists' style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

PubMed Central

Schmitt, Marco

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science. PMID:28636619

Protecting Information: The Role of Community Colleges in Cybersecurity Education. A Report from a Workshop Sponsored by the National Science Foundation and the American Association of Community Colleges (Washington, DC, June 26-28, 2002).

ERIC Educational Resources Information Center

American Association of Community Colleges, Washington, DC.

The education and training of the cybersecurity workforce is an essential element in protecting the nation's computer and information systems. On June 26-28, 2002, the National Science Foundation supported a cybersecurity education workshop hosted by the American Association of Community Colleges. The goals of the workshop were to map out the role…

CyVerse Data Commons: lessons learned in cyberinfrastructure management and data hosting from the Life Sciences

NASA Astrophysics Data System (ADS)

Swetnam, T. L.; Walls, R.; Merchant, N.

2017-12-01

CyVerse, is a US National Science Foundation funded initiative "to design, deploy, and expand a national cyberinfrastructure for life sciences research, and to train scientists in its use," supporting and enabling cross disciplinary collaborations across institutions. CyVerse' free, open-source, cyberinfrastructure is being adopted into biogeoscience and space sciences research. CyVerse data-science agnostic platforms provide shared data storage, high performance computing, and cloud computing that allow analysis of very large data sets (including incomplete or work-in-progress data sets). Part of CyVerse success has been in addressing the handling of data through its entire lifecycle, from creation to final publication in a digital data repository to reuse in new analyses. CyVerse developers and user communities have learned many lessons that are germane to Earth and Environmental Science. We present an overview of the tools and services available through CyVerse including: interactive computing with the Discovery Environment (https://de.cyverse.org/), an interactive data science workbench featuring data storage and transfer via the Data Store; cloud computing with Atmosphere (https://atmo.cyverse.org); and access to HPC via Agave API (https://agaveapi.co/). Each CyVerse service emphasizes access to long term data storage, including our own Data Commons (http://datacommons.cyverse.org), as well as external repositories. The Data Commons service manages, organizes, preserves, publishes, allows for discovery and reuse of data. All data published to CyVerse's Curated Data receive a permanent identifier (PID) in the form of a DOI (Digital Object Identifier) or ARK (Archival Resource Key). Data that is more fluid can also be published in the Data commons through Community Collaborated data. The Data Commons provides landing pages, permanent DOIs or ARKs, and supports data reuse and citation through features such as open data licenses and downloadable citations. The ability to access and do computing on data within the CyVerse framework or with external compute resources when necessary, has proven highly beneficial to our user community, which has continuously grown since the inception of CyVerse nine years ago.

Community Science Workshops: A Powerful and Feasible Model for Serving Underserved Youth. An Evaluation Brief

ERIC Educational Resources Information Center

Inverness Research Associates, 2007

2007-01-01

The people at Inverness Research Associates spent 12 years studying Community Science Workshops (CSW) in California and in six other states. They gathered statistics on the scale, scope, and cost-efficiency of CSW services to youth. They observed youth at work in the shops--taking apart computers, repairing bikes, growing plants, and so on--and…

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

PubMed

Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

2017-12-05

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

Evolution of a Collaborative Model between Nursing and Computer Science Faculty and a Community Service Organization to Develop an Information System

PubMed Central

Carson, Anne; Troy, Douglas

2007-01-01

Nursing and computer science students and faculty worked with the American Red Cross to investigate the potential for information technology to provide Red Cross disaster services nurses with improved access to accurate community resources in times of disaster. Funded by a national three-year grant, this interdisciplinary partnership led to field testing of an information system to support local community disaster preparedness at seven Red Cross chapters across the United States. The field test results demonstrate the benefits of the technology and the value of interdisciplinary research. The work also created a sustainable learning and research model for the future. This paper describes the collaborative model employed in this interdisciplinary research and exemplifies the benefits to faculty and students of well-timed interdisciplinary and community collaboration. PMID:18600129

The Synthetic Aperture Radar Science Data Processing Foundry Concept for Earth Science

NASA Astrophysics Data System (ADS)

Rosen, P. A.; Hua, H.; Norton, C. D.; Little, M. M.

2015-12-01

Since 2008, NASA's Earth Science Technology Office and the Advanced Information Systems Technology Program have invested in two technology evolutions to meet the needs of the community of scientists exploiting the rapidly growing database of international synthetic aperture radar (SAR) data. JPL, working with the science community, has developed the InSAR Scientific Computing Environment (ISCE), a next-generation interferometric SAR processing system that is designed to be flexible and extensible. ISCE currently supports many international space borne data sets but has been primarily focused on geodetic science and applications. A second evolutionary path, the Advanced Rapid Imaging and Analysis (ARIA) science data system, uses ISCE as its core science data processing engine and produces automated science and response products, quality assessments and metadata. The success of this two-front effort has been demonstrated in NASA's ability to respond to recent events with useful disaster support. JPL has enabled high-volume and low latency data production by the re-use of the hybrid cloud computing science data system (HySDS) that runs ARIA, leveraging on-premise cloud computing assets that are able to burst onto the Amazon Web Services (AWS) services as needed. Beyond geodetic applications, needs have emerged to process large volumes of time-series SAR data collected for estimation of biomass and its change, in such campaigns as the upcoming AfriSAR field campaign. ESTO is funding JPL to extend the ISCE-ARIA model to a "SAR Science Data Processing Foundry" to on-ramp new data sources and to produce new science data products to meet the needs of science teams and, in general, science community members. An extension of the ISCE-ARIA model to support on-demand processing will permit PIs to leverage this Foundry to produce data products from accepted data sources when they need them. This paper will describe each of the elements of the SAR SDP Foundry and describe their integration into a new conceptual approach to enable more effective use of SAR instruments.

The SCEC Community Modeling Environment (SCEC/CME) - An Overview of its Architecture and Current Capabilities

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Jordan, T. H.; Minster, B.; Moore, R.; Kesselman, C.; SCEC ITR Collaboration

2004-12-01

The Southern California Earthquake Center (SCEC), in collaboration with the San Diego Supercomputer Center, the USC Information Sciences Institute, the Incorporated Research Institutions for Seismology, and the U.S. Geological Survey, is developing the Southern California Earthquake Center Community Modeling Environment (CME) under a five-year grant from the National Science Foundation's Information Technology Research (ITR) Program jointly funded by the Geosciences and Computer and Information Science & Engineering Directorates. The CME system is an integrated geophysical simulation modeling framework that automates the process of selecting, configuring, and executing models of earthquake systems. During the Project's first three years, we have performed fundamental geophysical and information technology research and have also developed substantial system capabilities, software tools, and data collections that can help scientist perform systems-level earthquake science. The CME system provides collaborative tools to facilitate distributed research and development. These collaborative tools are primarily communication tools, providing researchers with access to information in ways that are convenient and useful. The CME system provides collaborators with access to significant computing and storage resources. The computing resources of the Project include in-house servers, Project allocations on USC High Performance Computing Linux Cluster, as well as allocations on NPACI Supercomputers and the TeraGrid. The CME system provides access to SCEC community geophysical models such as the Community Velocity Model, Community Fault Model, Community Crustal Motion Model, and the Community Block Model. The organizations that develop these models often provide access to them so it is not necessary to use the CME system to access these models. However, in some cases, the CME system supplements the SCEC community models with utility codes that make it easier to use or access these models. In some cases, the CME system also provides alternatives to the SCEC community models. The CME system hosts a collection of community geophysical software codes. These codes include seismic hazard analysis (SHA) programs developed by the SCEC/USGS OpenSHA group. Also, the CME system hosts anelastic wave propagation codes including Kim Olsen's Finite Difference code and Carnegie Mellon's Hercules Finite Element tool chain. The CME system can execute a workflow, that is, a series of geophysical computations using the output of one processing step as the input to a subsequent step. Our workflow capability utilizes grid-based computing software that can submit calculations to a pool of computing resources as well as data management tools that help us maintain an association between data files and metadata descriptions of those files. The CME system maintains, and provides access to, a collection of valuable geophysical data sets. The current CME Digital Library holdings include a collection of 60 ground motion simulation results calculated by a SCEC/PEER working group and a collection of Greens Functions calculated for 33 TriNet broadband receiver sites in the Los Angeles area.

Impacts and Characteristics of Computer-Based Science Inquiry Learning Environments for Precollege Students

ERIC Educational Resources Information Center

Donnelly, Dermot F.; Linn, Marcia C.; Ludvigsen, Sten

2014-01-01

The National Science Foundation-sponsored report "Fostering Learning in the Networked World" called for "a common, open platform to support communities of developers and learners in ways that enable both to take advantage of advances in the learning sciences." We review research on science inquiry learning environments (ILEs)…

Changing from computing grid to knowledge grid in life-science grid.

PubMed

Talukdar, Veera; Konar, Amit; Datta, Ayan; Choudhury, Anamika Roy

2009-09-01

Grid computing has a great potential to become a standard cyber infrastructure for life sciences that often require high-performance computing and large data handling, which exceeds the computing capacity of a single institution. Grid computer applies the resources of many computers in a network to a single problem at the same time. It is useful to scientific problems that require a great number of computer processing cycles or access to a large amount of data.As biologists,we are constantly discovering millions of genes and genome features, which are assembled in a library and distributed on computers around the world.This means that new, innovative methods must be developed that exploit the re-sources available for extensive calculations - for example grid computing.This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing a "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. By extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

NASA Astrophysics Data System (ADS)

Brescia, Massimo

2012-11-01

Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to produce efficient and reliable scientific results. All these considerations will be described in the detail in the chapter. Moreover, examples of modern applications offering to a wide variety of e-science communities a large spectrum of computational facilities to exploit the wealth of available massive data sets and powerful machine learning and statistical algorithms will be also introduced.

The future of scientific workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deelman, Ewa; Peterka, Tom; Altintas, Ilkay

Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less

Damsel: A Data Model Storage Library for Exascale Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koziol, Quincey

The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. We will accomplish this through three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community.

The Role of Technology in Supporting Learning Communities.

ERIC Educational Resources Information Center

Riel, Margaret; Fulton, Kathleen

2001-01-01

In a learning community, students learn to cooperate and make teams work. Past technologies (print, photography, film, and computers) have enabled idea sharing, but are one-way communication modes. Broader learning communities have been made possible through electronic field trips, online mentoring, science investigations, and humanities…

ISEES: an institute for sustainable software to accelerate environmental science

NASA Astrophysics Data System (ADS)

Jones, M. B.; Schildhauer, M.; Fox, P. A.

2013-12-01

Software is essential to the full science lifecycle, spanning data acquisition, processing, quality assessment, data integration, analysis, modeling, and visualization. Software runs our meteorological sensor systems, our data loggers, and our ocean gliders. Every aspect of science is impacted by, and improved by, software. Scientific advances ranging from modeling climate change to the sequencing of the human genome have been rendered possible in the last few decades due to the massive improvements in the capabilities of computers to process data through software. This pivotal role of software in science is broadly acknowledged, while simultaneously being systematically undervalued through minimal investments in maintenance and innovation. As a community, we need to embrace the creation, use, and maintenance of software within science, and address problems such as code complexity, openness,reproducibility, and accessibility. We also need to fully develop new skills and practices in software engineering as a core competency in our earth science disciplines, starting with undergraduate and graduate education and extending into university and agency professional positions. The Institute for Sustainable Earth and Environmental Software (ISEES) is being envisioned as a community-driven activity that can facilitate and galvanize activites around scientific software in an analogous way to synthesis centers such as NCEAS and NESCent that have stimulated massive advances in ecology and evolution. We will describe the results of six workshops (Science Drivers, Software Lifecycles, Software Components, Workforce Development and Training, Sustainability and Governance, and Community Engagement) that have been held in 2013 to envision such an institute. We will present community recommendations from these workshops and our strategic vision for how ISEES will address the technical issues in the software lifecycle, sustainability of the whole software ecosystem, and the critical issue of computational training for the scientific community. Process for envisioning ISEES.

Community College Users' Report, Fall 1975.

ERIC Educational Resources Information Center

Zimmer, A. L., Ed.

This report was compiled from information supplied by instructors participating in the National Science Foundation's community college field test of PLATO IV--a computer-based system developed at the University of Illinois--during the fall semester of 1975. Represented here are the responses of instructors at five Illinois community colleges to…

A Research Program in Computer Technology. 1982 Annual Technical Report

DTIC Science & Technology

1983-03-01

for the Defense Advanced Research Projects Agency. The research applies computer science and technology to areas of high DoD/ military impact. The ISI...implement the plan; New Computing Environment - investigation and adaptation of developing computer technologies to serve the research and military ...Computing Environment - ,.*_i;.;"’.)n and adaptation of developing computer technologies to serve the research and military tser communities; and Computer

The SGI/CRAY T3E: Experiences and Insights

NASA Technical Reports Server (NTRS)

Bernard, Lisa Hamet

1999-01-01

The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

Towards Reproducibility in Computational Hydrology

NASA Astrophysics Data System (ADS)

Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei; Duffy, Chris; Arheimer, Berit

2017-04-01

Reproducibility is a foundational principle in scientific research. The ability to independently re-run an experiment helps to verify the legitimacy of individual findings, and evolve (or reject) hypotheses and models of how environmental systems function, and move them from specific circumstances to more general theory. Yet in computational hydrology (and in environmental science more widely) the code and data that produces published results are not regularly made available, and even if they are made available, there remains a multitude of generally unreported choices that an individual scientist may have made that impact the study result. This situation strongly inhibits the ability of our community to reproduce and verify previous findings, as all the information and boundary conditions required to set up a computational experiment simply cannot be reported in an article's text alone. In Hutton et al 2016 [1], we argue that a cultural change is required in the computational hydrological community, in order to advance and make more robust the process of knowledge creation and hypothesis testing. We need to adopt common standards and infrastructures to: (1) make code readable and re-useable; (2) create well-documented workflows that combine re-useable code together with data to enable published scientific findings to be reproduced; (3) make code and workflows available, easy to find, and easy to interpret, using code and code metadata repositories. To create change we argue for improved graduate training in these areas. In this talk we reflect on our progress in achieving reproducible, open science in computational hydrology, which are relevant to the broader computational geoscience community. In particular, we draw on our experience in the Switch-On (EU funded) virtual water science laboratory (http://www.switch-on-vwsl.eu/participate/), which is an open platform for collaboration in hydrological experiments (e.g. [2]). While we use computational hydrology as the example application area, we believe that our conclusions are of value to the wider environmental and geoscience community as far as the use of code and models for scientific advancement is concerned. References: [1] Hutton, C., T. Wagener, J. Freer, D. Han, C. Duffy, and B. Arheimer (2016), Most computational hydrology is not reproducible, so is it really science?, Water Resour. Res., 52, 7548-7555, doi:10.1002/2016WR019285. [2] Ceola, S., et al. (2015), Virtual laboratories: New opportunities for collaborative water science, Hydrol. Earth Syst. Sci. Discuss., 11(12), 13443-13478, doi:10.5194/hessd-11-13443-2014.

Opportunities and challenges for the life sciences community.

PubMed

Kolker, Eugene; Stewart, Elizabeth; Ozdemir, Vural

2012-03-01

Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19-20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16-17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org ) was formed to become a Digital Commons for the life sciences community.

Opportunities and Challenges for the Life Sciences Community

PubMed Central

Stewart, Elizabeth; Ozdemir, Vural

2012-01-01

Abstract Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19–20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16–17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org) was formed to become a Digital Commons for the life sciences community. PMID:22401659

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design

PubMed Central

Alford, Rebecca F.; Dolan, Erin L.

2017-01-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology. PMID:29216185

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

PubMed

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

Mentoring the Next Generation of Science Gateway Developers and Users

NASA Astrophysics Data System (ADS)

Hayden, L. B.; Jackson-Ward, F.

2016-12-01

The Science Gateway Institute (SGW-I) for the Democratization and Acceleration of Science was a SI2-SSE Collaborative Research conceptualization award funded by NSF in 2012. From 2012 through 2015, we engaged interested members of the science and engineering community in a planning process for a Science Gateway Community Institute (SGCI). Science Gateways provide Web interfaces to some of the most sophisticated cyberinfrastructure resources. They interact with remotely executing science applications on supercomputers, they connect to remote scientific data collections, instruments and sensor streams, and support large collaborations. Gateways allow scientists to concentrate on the most challenging science problems while underlying components such as computing architectures and interfaces to data collection changes. The goal of our institute was to provide coordinating activities across the National Science Foundation, eventually providing services more broadly to projects funded by other agencies. SGW-I has succeeded in identifying two underrepresented communities of future gateway designers and users. The Association of Computer and Information Science/Engineering Departments at Minority Institutions (ADMI) was identified as a source of future gateway designers. The National Organization for the Professional Advancement of Black Chemists and Chemical Engineers (NOBCChE) was identified as a community of future science gateway users. SGW-I efforts to engage NOBCChE and ADMI faculty and students in SGW-I are now woven into the workforce development component of SGCI. SGCI (ScienceGateways.org ) is a collaboration of six universities, led by San Diego Supercomputer Center. The workforce development component is led by Elizabeth City State University (ECSU). ECSU efforts focus is on: Produce a model of engagement; Integration of research into education; and Mentoring of students while aggressively addressing diversity. This paper documents the outcome of the SGW-I conceptualization project and describes the extensive Workforce Development effort going forward into the 5-year SGCI project recently funded by NSF.

Implementations of the CC'01 Human-Computer Interaction Guidelines Using Bloom's Taxonomy

ERIC Educational Resources Information Center

Manaris, Bill; Wainer, Michael; Kirkpatrick, Arthur E.; Stalvey, RoxAnn H.; Shannon, Christine; Leventhal, Laura; Barnes, Julie; Wright, John; Schafer, J. Ben; Sanders, Dean

2007-01-01

In today's technology-laden society human-computer interaction (HCI) is an important knowledge area for computer scientists and software engineers. This paper surveys existing approaches to incorporate HCI into computer science (CS) and such related issues as the perceived gap between the interests of the HCI community and the needs of CS…

Globus Quick Start Guide. Globus Software Version 1.1

NASA Technical Reports Server (NTRS)

1999-01-01

The Globus Project is a community effort, led by Argonne National Laboratory and the University of Southern California's Information Sciences Institute. Globus is developing the basic software infrastructure for computations that integrate geographically distributed computational and information resources.

A parallel-processing approach to computing for the geographic sciences

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Haga, Jim; Maddox, Brian; Feller, Mark

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting research into various areas, such as advanced computer architecture, algorithms to meet the processing needs for real-time image and data processing, the creation of custom datasets from seamless source data, rapid turn-around of products for emergency response, and support for computationally intense spatial and temporal modeling.

Building a bioinformatics community of practice through library education programs.

PubMed

Moore, Margaret E; Vaughan, K T L; Hayes, Barrie E

2004-01-01

This paper addresses the following questions:What makes the community of practice concept an intriguing framework for developing library services for bioinformatics? What is the campus context and setting? What has been the Health Sciences Library's role in bioinformatics at the University of North Carolina (UNC) Chapel Hill? What are the Health Sciences Library's goals? What services are currently offered? How will these services be evaluated and developed? How can libraries demonstrate their value? Providing library services for an emerging community such as bioinformatics and computational biology presents special challenges for libraries including understanding needs, defining and communicating the library's role, building relationships within the community, preparing staff, and securing funding. Like many academic health sciences libraries, the University of North Carolina (UNC) at Chapel Hill Health Sciences Library is addressing these challenges in the context of its overall mission and goals.

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

Changing the Paradigm: Preparing Students for the Computing Profession in the 21st Century

NASA Technical Reports Server (NTRS)

Robbins, Kay A.

2003-01-01

The dramatic technological developments of the past decade have led to a tremendous growth in the demand for computer science professionals well-versed in advanced technology and techniques. NASA, traditionally a haven for cutting-edge innovators, is now competing with every industrial and government sector for computer science talent. The computer science program at University of Texas at San Antonio (UTSA) faces challenges beyond those intrinsically presented by rapid technological change, because a significant number of UTSA students come from low-income families with no Internet or computer access at home. An examination of enrollment statistics for the computer science program at UTSA showed that very few students who entered as freshmen successfully graduated. The upper division courses appeared to be populated by graduate students removing deficiencies and by transfer students. The faculty was also concerned that the students who did graduate from the program did not have the strong technical and programming skills that the CS program had been noted for in the community during the 1980's.

A Research Agenda and Vision for Data Science

NASA Astrophysics Data System (ADS)

Mattmann, C. A.

2014-12-01

Big Data has emerged as a first-class citizen in the research community spanning disciplines in the domain sciences - Astronomy is pushing velocity with new ground-based instruments such as the Square Kilometre Array (SKA) and its unprecedented data rates (700 TB/sec!); Earth-science is pushing the boundaries of volume with increasing experiments in the international Intergovernmental Panel on Climate Change (IPCC) and climate modeling and remote sensing communities increasing the size of the total archives into the Exabytes scale; airborne missions from NASA such as the JPL Airborne Snow Observatory (ASO) is increasing both its velocity and decreasing the overall turnaround time required to receive products and to make them available to water managers and decision makers. Proteomics and the computational biology community are sequencing genomes and providing near real time answers to clinicians, researchers, and ultimately to patients, helping to process and understand and create diagnoses. Data complexity is on the rise, and the norm is no longer 100s of metadata attributes, but thousands to hundreds of thousands, including complex interrelationships between data and metadata and knowledge. I published a vision for data science in Nature 2013 that encapsulates four thrust areas and foci that I believe the computer science, Big Data, and data science communities need to attack over the next decade to make fundamental progress in the data volume, velocity and complexity challenges arising from the domain sciences such as those described above. These areas include: (1) rapid and unobtrusive algorithm integration; (2) intelligent and automatic data movement; (3) automated and rapid extraction text, metadata and language from heterogeneous file formats; and (4) participation and people power via open source communities. In this talk I will revisit these four areas and describe current progress; future work and challenges ahead as we move forward in this exciting age of Data Science.

Symposium Connects Government Problems with State of the Art Network Science Research

DTIC Science & Technology

2015-10-16

Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering

Regime, phase and paradigm shifts: making community ecology the basic science for fisheries

PubMed Central

Mangel, Marc; Levin, Phillip S.

2005-01-01

Modern fishery science, which began in 1957 with Beverton and Holt, is ca. 50 years old. At its inception, fishery science was limited by a nineteenth century mechanistic worldview and by computational technology; thus, the relatively simple equations of population ecology became the fundamental ecological science underlying fisheries. The time has come for this to change and for community ecology to become the fundamental ecological science underlying fisheries. This point will be illustrated with two examples. First, when viewed from a community perspective, excess production must be considered in the context of biomass left for predators. We argue that this is a better measure of the effects of fisheries than spawning biomass per recruit. Second, we shall analyse a simple, but still multi-species, model for fishery management that considers the alternatives of harvest regulations, inshore marine protected areas and offshore marine protected areas. Population or community perspectives lead to very different predictions about the efficacy of reserves. PMID:15713590

Community Coordinated Modeling Center: A Powerful Resource in Space Science and Space Weather Education

NASA Astrophysics Data System (ADS)

Chulaki, A.; Kuznetsova, M. M.; Rastaetter, L.; MacNeice, P. J.; Shim, J. S.; Pulkkinen, A. A.; Taktakishvili, A.; Mays, M. L.; Mendoza, A. M. M.; Zheng, Y.; Mullinix, R.; Collado-Vega, Y. M.; Maddox, M. M.; Pembroke, A. D.; Wiegand, C.

2015-12-01

Community Coordinated Modeling Center (CCMC) is a NASA affiliated interagency partnership with the primary goal of aiding the transition of modern space science models into space weather forecasting while supporting space science research. Additionally, over the past ten years it has established itself as a global space science education resource supporting undergraduate and graduate education and research, and spreading space weather awareness worldwide. A unique combination of assets, capabilities and close ties to the scientific and educational communities enable this small group to serve as a hub for raising generations of young space scientists and engineers. CCMC resources are publicly available online, providing unprecedented global access to the largest collection of modern space science models (developed by the international research community). CCMC has revolutionized the way simulations are utilized in classrooms settings, student projects, and scientific labs and serves hundreds of educators, students and researchers every year. Another major CCMC asset is an expert space weather prototyping team primarily serving NASA's interplanetary space weather needs. Capitalizing on its unrivaled capabilities and experiences, the team provides in-depth space weather training to students and professionals worldwide, and offers an amazing opportunity for undergraduates to engage in real-time space weather monitoring, analysis, forecasting and research. In-house development of state-of-the-art space weather tools and applications provides exciting opportunities to students majoring in computer science and computer engineering fields to intern with the software engineers at the CCMC while also learning about the space weather from the NASA scientists.

Center for Center for Technology for Advanced Scientific Component Software (TASCS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostadin, Damevski

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technologymore » for Advanced Scientific Component Software (TASCS)1 tackles these these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.« less

Riding the Hype Wave: Evaluating new AI Techniques for their Applicability in Earth Science

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Zhang, J.; Maskey, M.; Lee, T. J.

2016-12-01

Every few years a new technology rides the hype wave generated by the computer science community. Converts to this new technology who surface from both the science community and the informatics community promulgate that it can radically improve or even change the existing scientific process. Recent examples of new technology following in the footsteps of "big data" now include deep learning algorithms and knowledge graphs. Deep learning algorithms mimic the human brain and process information through multiple stages of transformation and representation. These algorithms are able to learn complex functions that map pixels directly to outputs without relying on human-crafted features and solve some of the complex classification problems that exist in science. Similarly, knowledge graphs aggregate information around defined topics that enable users to resolve their query without having to navigate and assemble information manually. Knowledge graphs could potentially be used in scientific research to assist in hypothesis formulation, testing, and review. The challenge for the Earth science research community is to evaluate these new technologies by asking the right questions and considering what-if scenarios. What is this new technology enabling/providing that is innovative and different? Can one justify the adoption costs with respect to the research returns? Since nothing comes for free, utilizing a new technology entails adoption costs that may outweigh the benefits. Furthermore, these technologies may require significant computing infrastructure in order to be utilized effectively. Results from two different projects will be presented along with lessons learned from testing these technologies. The first project primarily evaluates deep learning techniques for different applications of image retrieval within Earth science while the second project builds a prototype knowledge graph constructed for Hurricane science.

Development of EarthCube Governance: An Agile Approach

NASA Astrophysics Data System (ADS)

Pearthree, G.; Allison, M. L.; Patten, K.

2013-12-01

Governance of geosciences cyberinfrastructure is a complex and essential undertaking, critical in enabling distributed knowledge communities to collaborate and communicate across disciplines, distances, and cultures. Advancing science with respect to 'grand challenges," such as global climate change, weather prediction, and core fundamental science, depends not just on technical cyber systems, but also on social systems for strategic planning, decision-making, project management, learning, teaching, and building a community of practice. Simply put, a robust, agile technical system depends on an equally robust and agile social system. Cyberinfrastructure development is wrapped in social, organizational and governance challenges, which may significantly impede progress. An agile development process is underway for governance of transformative investments in geosciences cyberinfrastructure through the NSF EarthCube initiative. Agile development is iterative and incremental, and promotes adaptive planning and rapid and flexible response. Such iterative deployment across a variety of EarthCube stakeholders encourages transparency, consensus, accountability, and inclusiveness. A project Secretariat acts as the coordinating body, carrying out duties for planning, organizing, communicating, and reporting. A broad coalition of stakeholder groups comprises an Assembly (Mainstream Scientists, Cyberinfrastructure Institutions, Information Technology/Computer Sciences, NSF EarthCube Investigators, Science Communities, EarthCube End-User Workshop Organizers, Professional Societies) to serve as a preliminary venue for identifying, evaluating, and testing potential governance models. To offer opportunity for broader end-user input, a crowd-source approach will engage stakeholders not involved otherwise. An Advisory Committee from the Earth, ocean, atmosphere, social, computer and library sciences is guiding the process from a high-level policy point of view. Developmental evaluators from the social sciences embedded in the project provide real-time review and adjustments. While a large number of agencies and organizations have agreed to participate, in order to ensure an open and inclusive process, community selected leaders yet to be identified will play key roles through an Assembly Advisory Council. Once consensus is reached on a governing framework, a community-selected demonstration governance pilot will help facilitate community convergence on system design.

Government regulations and other influences on the medical use of computers.

PubMed

Mishelevich, D J; Grams, R R; Mize, S G; Smith, J P

1979-01-01

This paper presents points brought out in a panel discussion held at the 12th Hawaiian International Conference on System Sciences, January 1979. The session was attended by approximately two dozen interested parties from various segments of the academic, government, and health care communities. The broad categories covered include the specific problems of government regulations and their impact on specific clinical information systems installed at The University of Texas Health Science Center at Dallas, opportunities in a regulated environment, problems in a regulated environment, vendor-related issues in the marketing and manufacture of computer-based information systems, rational approaches to government control, and specific issues related to medical computer science.

24 CFR 570.416 - Hispanic-serving institutions work study program.

Code of Federal Regulations, 2010 CFR

2010-04-01

... to pre-professional careers in these fields. (b) Definitions. The following definitions apply to HSI... such as natural sciences, computer sciences, mathematics, accounting, electronics, engineering, and the... pursuing careers in community building, and make them aware of the availability of assistance opportunities...

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

The CompTox Chemistry Dashboard - A Community Data Resource for Environmental Chemistry

EPA Science Inventory

Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protectio...

Advancing Capabilities for Understanding the Earth System Through Intelligent Systems, the NSF Perspective

NASA Astrophysics Data System (ADS)

Gil, Y.; Zanzerkia, E. E.; Munoz-Avila, H.

2015-12-01

The National Science Foundation (NSF) Directorate for Geosciences (GEO) and Directorate for Computer and Information Science (CISE) acknowledge the significant scientific challenges required to understand the fundamental processes of the Earth system, within the atmospheric and geospace, Earth, ocean and polar sciences, and across those boundaries. A broad view of the opportunities and directions for GEO are described in the report "Dynamic Earth: GEO imperative and Frontiers 2015-2020." Many of the aspects of geosciences research, highlighted both in this document and other community grand challenges, pose novel problems for researchers in intelligent systems. Geosciences research will require solutions for data-intensive science, advanced computational capabilities, and transformative concepts for visualizing, using, analyzing and understanding geo phenomena and data. Opportunities for the scientific community to engage in addressing these challenges are available and being developed through NSF's portfolio of investments and activities. The NSF-wide initiative, Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21), looks to accelerate research and education through new capabilities in data, computation, software and other aspects of cyberinfrastructure. EarthCube, a joint program between GEO and the Advanced Cyberinfrastructure Division, aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating our ability to understand and predict the Earth system. EarthCube's mission opens an opportunity for collaborative research on novel information systems enhancing and supporting geosciences research efforts. NSF encourages true, collaborative partnerships between scientists in computer sciences and the geosciences to meet these challenges.

CESDIS

NASA Technical Reports Server (NTRS)

1994-01-01

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. The 1993-94 CESDIS year included a broad range of computer science research applied to NASA problems. This report provides an overview of these research projects and programs as well as a summary of the various other activities of CESDIS in support of NASA and the university research community, We have had an exciting and challenging year.

Uses of the Drupal CMS Collaborative Framework in the Woods Hole Scientific Community (Invited)

NASA Astrophysics Data System (ADS)

Maffei, A. R.; Chandler, C. L.; Work, T. T.; Shorthouse, D.; Furfey, J.; Miller, H.

2010-12-01

Organizations that comprise the Woods Hole scientific community (Woods Hole Oceanographic Institution, Marine Biological Laboratory, USGS Woods Hole Coastal and Marine Science Center, Woods Hole Research Center, NOAA NMFS Northeast Fisheries Science Center, SEA Education Association) have a long history of collaborative activity regarding computing, computer network and information technologies that support common, inter-disciplinary science needs. Over the past several years there has been growing interest in the use of the Drupal Content Management System (CMS) playing a variety of roles in support of research projects resident at several of these organizations. Many of these projects are part of science programs that are national and international in scope. Here we survey the current uses of Drupal within the Woods Hole scientific community and examine reasons it has been adopted. The promise of emerging semantic features in the Drupal framework is examined and projections of how pre-existing Drupal-based websites might benefit are made. Closer examination of Drupal software design exposes it as more than simply a content management system. The flexibility of its architecture; the power of its taxonomy module; the care taken in nurturing the open-source developer community that surrounds it (including organized and often well-attended code sprints); the ability to bind emerging software technologies as Drupal modules; the careful selection process used in adopting core functionality; multi-site hosting and cross-site deployment of updates and a recent trend towards development of use-case inspired Drupal distributions casts Drupal as a general-purpose application deployment framework. Recent work in the semantic arena casts Drupal as an emerging RDF framework as well. Examples of roles played by Drupal-based websites within the Woods Hole scientific community that will be discussed include: science data metadata database, organization main website, biological taxonomy development, bibliographic database, physical media data archive inventory manager, disaster-response website development framework, science project task management, science conference planning, and spreadsheet-to-database converter.

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Potok, Thomas; Schuman, Catherine; Patton, Robert

The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshopmore » we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.« less

EarthCube: A Community-Driven Cyberinfrastructure for the Geosciences

NASA Astrophysics Data System (ADS)

Koskela, Rebecca; Ramamurthy, Mohan; Pearlman, Jay; Lehnert, Kerstin; Ahern, Tim; Fredericks, Janet; Goring, Simon; Peckham, Scott; Powers, Lindsay; Kamalabdi, Farzad; Rubin, Ken; Yarmey, Lynn

2017-04-01

EarthCube is creating a dynamic, System of Systems (SoS) infrastructure and data tools to collect, access, analyze, share, and visualize all forms of geoscience data and resources, using advanced collaboration, technological, and computational capabilities. EarthCube, as a joint effort between the U.S. National Science Foundation Directorate for Geosciences and the Division of Advanced Cyberinfrastructure, is a quickly growing community of scientists across all geoscience domains, as well as geoinformatics researchers and data scientists. EarthCube has attracted an evolving, dynamic virtual community of more than 2,500 contributors, including earth, ocean, polar, planetary, atmospheric, geospace, computer and social scientists, educators, and data and information professionals. During 2017, EarthCube will transition to the implementation phase. The implementation will balance "innovation" and "production" to advance cross-disciplinary science goals as well as the development of future data scientists. This presentation will describe the current architecture design for the EarthCube cyberinfrastructure and implementation plan.

Tracking Women and Minorities as They Attain Degrees in Computing and Related Fields

ERIC Educational Resources Information Center

Sorkin, Sylvia; Gore, Mary Elizabeth; Mento, Barbara; Stanton, Jon

2010-01-01

Two Maryland colleges (one a four-year liberal arts college for women, and one a public community college) have worked to increase the number of graduates, especially women and other under-represented groups, in their computer science, computer information systems, engineering, and mathematics programs over a four-year period. In August 2004, they…

Cognitive Computational Neuroscience: A New Conference for an Emerging Discipline.

PubMed

Naselaris, Thomas; Bassett, Danielle S; Fletcher, Alyson K; Kording, Konrad; Kriegeskorte, Nikolaus; Nienborg, Hendrikje; Poldrack, Russell A; Shohamy, Daphna; Kay, Kendrick

2018-05-01

Understanding the computational principles that underlie complex behavior is a central goal in cognitive science, artificial intelligence, and neuroscience. In an attempt to unify these disconnected communities, we created a new conference called Cognitive Computational Neuroscience (CCN). The inaugural meeting revealed considerable enthusiasm but significant obstacles remain. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mother, Earth, Father Sky Symposium

NASA Technical Reports Server (NTRS)

Bowman, B.

1977-01-01

A conference was held in which minority aerospace scientists and engineers interacted with the minority community, particularly at the junior high, high school, and college levels. There were two presentations in the biological sciences, two in the physical and environmental sciences, seven in engineering and computer sciences, and nine in aerospace science and engineering. Aerospace technology careers and aerospace activities were discussed as to how they are relevant to minorities and women.

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Rethinking Approaches to Exploration and Analysis of Big Data in Earth Science

NASA Astrophysics Data System (ADS)

Graves, S. J.; Maskey, M.

2015-12-01

With increasing amounts of data available for exploration and analysis, there are increasing numbers of users that need information extracted from the data for very specific purposes. Many of the specific purposes may not have even been considered yet so how do computational and data scientists plan for this diverse and not well defined set of possible users? There are challenges to be considered in the computational architectures, as well as the organizational structures for the data to allow for the best possible exploration and analytical capabilities. Data analytics need to be a key component in thinking about the data structures and types of storage of these large amounts of data, coming from a variety of sensing platforms that may be space based, airborne, in situ and social media. How do we provide for better capabilities for exploration and anaylsis at the point of collection for real-time or near real-time requirements? This presentation will address some of the approaches being considered and the challenges the computational and data science communities are facing in collaboration with the Earth Science research and application communities.

A Community Publication and Dissemination System for Hydrology Education Materials

NASA Astrophysics Data System (ADS)

Ruddell, B. L.

2015-12-01

Hosted by CUAHSI and the Science Education Resource Center (SERC), federated by the National Science Digital Library (NSDL), and allied with the Water Data Center (WDC), Hydrologic Information System (HIS), and HydroShare projects, a simple cyberinfrastructure has been launched for the publication and dissemination of data and model driven university hydrology education materials. This lightweight system's metadata describes learning content as a data-driven module with defined data inputs and outputs. This structure allows a user to mix and match modules to create sequences of content that teach both hydrology and computer learning outcomes. Importantly, this modular infrastructure allows an instructor to substitute a module based on updated computer methods for one based on outdated computer methods, hopefully solving the problem of rapid obsolescence that has hampered previous community efforts. The prototype system is now available from CUAHSI and SERC, with some example content. The system is designed to catalog, link to, make visible, and make accessible the existing and future contributions of the community; this system does not create content. Submissions from hydrology educators are eagerly solicited, especially for existing content.

77 FR 66873 - Advisory Committee for Computer and Information Science and Engineering; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-07

... Engineering; Notice of Meeting In accordance with Federal Advisory Committee Act (Pub. L. 92-463, as amended... and Information Science and Engineering (1115). Date/Time: November 28, 2012: 12:00 p.m. to 5:30 p.m... Information Science and Engineering (CISE) community. To provide advice to the Assistant Director for CISE on...

Fusion Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Fusion Energy Sciences, January 27-29, 2016, Gaithersburg, Maryland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Choong-Seock; Greenwald, Martin; Riley, Katherine

The additional computing power offered by the planned exascale facilities could be transformational across the spectrum of plasma and fusion research — provided that the new architectures can be efficiently applied to our problem space. The collaboration that will be required to succeed should be viewed as an opportunity to identify and exploit cross-disciplinary synergies. To assess the opportunities and requirements as part of the development of an overall strategy for computing in the exascale era, the Exascale Requirements Review meeting of the Fusion Energy Sciences (FES) community was convened January 27–29, 2016, with participation from a broad range ofmore » fusion and plasma scientists, specialists in applied mathematics and computer science, and representatives from the U.S. Department of Energy (DOE) and its major computing facilities. This report is a summary of that meeting and the preparatory activities for it and includes a wealth of detail to support the findings. Technical opportunities, requirements, and challenges are detailed in this report (and in the recent report on the Workshop on Integrated Simulation). Science applications are described, along with mathematical and computational enabling technologies. Also see http://exascaleage.org/fes/ for more information.« less

Community Colleges and Cybersecurity Education.

ERIC Educational Resources Information Center

Teles, Elizabeth J.; Hovis, R. Corby

2002-01-01

Describes recent federal legislation (H.R. 3394) that charges the National Science Foundation with offering more grants to colleges and universities for degree programs in computer and network security, and to establish trainee programs for graduate students who pursue doctoral degrees in computer and network security. Discusses aspects of…

The Minority Honors Program in Energy-Related Curricula.

ERIC Educational Resources Information Center

Kish, Evelyn Rubio; Santa Rita, Emilio

In 1984, Bronx Community College (BCC) established the Minority Honors Program in Energy Related Curricula, a partnership between their academic honors program and the U.S. Department of Energy. The program's goal is to increase the participation of minorities in the fields of Computer Science, Electrical Technology, Engineering Science, Data…

Tested Strategies for Recruiting and Retention of STEM Majors

ERIC Educational Resources Information Center

Davari, Sadegh; Perkins-Hall, Sharon; Abeysekera, Krishani

2017-01-01

There is a shortage of STEM (Science, Technology, Engineering and Mathematics) educated workforce in the US, especially among minority and underrepresented groups. Recruiting and retaining STEM majors has been a major problem for universities and community colleges for many years. The Computer Science department of University of Houston-Clear Lake…

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Care and the Construction of Hacker Identities, Communities, and Society

ERIC Educational Resources Information Center

Toombs, Austin Lewis

2016-01-01

Recent scholarship in Human-Computer Interaction, science and technology studies, and design research has focused on hacker communities as sites of innovation and entrepreneurship, novel forms of education, and the democratization of technological production. However, hacking practices are more than new technical practices; they are also…

Grid Computing for Earth Science

NASA Astrophysics Data System (ADS)

Renard, Philippe; Badoux, Vincent; Petitdidier, Monique; Cossu, Roberto

2009-04-01

The fundamental challenges facing humankind at the beginning of the 21st century require an effective response to the massive changes that are putting increasing pressure on the environment and society. The worldwide Earth science community, with its mosaic of disciplines and players (academia, industry, national surveys, international organizations, and so forth), provides a scientific basis for addressing issues such as the development of new energy resources; a secure water supply; safe storage of nuclear waste; the analysis, modeling, and mitigation of climate changes; and the assessment of natural and industrial risks. In addition, the Earth science community provides short- and medium-term prediction of weather and natural hazards in real time, and model simulations of a host of phenomena relating to the Earth and its space environment. These capabilities require that the Earth science community utilize, both in real and remote time, massive amounts of data, which are usually distributed among many different organizations and data centers.

The ACLS Survey of Scholars: Views on Publications, Computers, Libraries.

ERIC Educational Resources Information Center

Morton, Herbert C.; Price, Anne Jamieson

1986-01-01

Reviews results of a survey by the American Council of Learned Societies (ACLS) of 3,835 scholars in the humanities and social sciences who are working both in colleges and universities and outside the academic community. Areas highlighted include professional reading, authorship patterns, computer use, and library use. (LRW)

Computational modeling in cognitive science: a manifesto for change.

PubMed

Addyman, Caspar; French, Robert M

2012-07-01

Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces.  For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. Copyright © 2012 Cognitive Science Society, Inc.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology.

PubMed

Goff, Stephen A; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B S; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M; Cranston, Karen A; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J; White, Jeffery W; Leebens-Mack, James; Donoghue, Michael J; Spalding, Edgar P; Vision, Todd J; Myers, Christopher R; Lowenthal, David; Enquist, Brian J; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

PubMed Central

Goff, Stephen A.; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E.; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H.; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B. S.; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M.; Cranston, Karen A.; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J.; White, Jeffery W.; Leebens-Mack, James; Donoghue, Michael J.; Spalding, Edgar P.; Vision, Todd J.; Myers, Christopher R.; Lowenthal, David; Enquist, Brian J.; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services. PMID:22645531

A Hybrid Cloud Computing Service for Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, C. P.

2016-12-01

Cloud Computing is becoming a norm for providing computing capabilities for advancing Earth sciences including big Earth data management, processing, analytics, model simulations, and many other aspects. A hybrid spatiotemporal cloud computing service is bulit at George Mason NSF spatiotemporal innovation center to meet this demands. This paper will report the service including several aspects: 1) the hardware includes 500 computing services and close to 2PB storage as well as connection to XSEDE Jetstream and Caltech experimental cloud computing environment for sharing the resource; 2) the cloud service is geographically distributed at east coast, west coast, and central region; 3) the cloud includes private clouds managed using open stack and eucalyptus, DC2 is used to bridge these and the public AWS cloud for interoperability and sharing computing resources when high demands surfing; 4) the cloud service is used to support NSF EarthCube program through the ECITE project, ESIP through the ESIP cloud computing cluster, semantics testbed cluster, and other clusters; 5) the cloud service is also available for the earth science communities to conduct geoscience. A brief introduction about how to use the cloud service will be included.

Soil, Weeds, and Computers

ERIC Educational Resources Information Center

McClennen, Nate

2004-01-01

Events in a community can lead to valuable learning experiences in science. By the end of the summer of 2001, the Green Knoll Fire had burned almost 4000 acres of forest south of Wilson, Wyoming. This article describes how students at the Journeys School of Teton Science Schools participated in a collaborative project with the United States Forest…

Reality Is Our Laboratory: Communities of Practice in Applied Computer Science

ERIC Educational Resources Information Center

Rohde, M.; Klamma, R.; Jarke, M.; Wulf, V.

2007-01-01

The present paper presents a longitudinal study of the course "High-tech Entrepreneurship and New Media." The course design is based on socio-cultural theories of learning and considers the role of social capital in entrepreneurial networks. By integrating student teams into the communities of practice of local start-ups, we offer…

Engaging College Students on a Community Engagement with High School Students with Disabilities

ERIC Educational Resources Information Center

Lawler, James; Joseph, Anthony; Narula, Stuti

2014-01-01

Community engagement is a common course in college curricula of computer science and information systems. In this study, the authors analyze the benefits of digital storytelling, in a course engaging college students with high school students with disabilities. The authors discover that a project of storytelling progressively enables high…

Air, Ocean and Climate Monitoring Enhancing Undergraduate Training in the Physical, Environmental and Computer Sciences

NASA Technical Reports Server (NTRS)

Hope, W. W.; Johnson, L. P.; Obl, W.; Stewart, A.; Harris, W. C.; Craig, R. D.

2000-01-01

Faculty in the Department of Physical, Environmental and Computer Sciences strongly believe in the concept that undergraduate research and research-related activities must be integrated into the fabric of our undergraduate Science and Technology curricula. High level skills, such as problem solving, reasoning, collaboration and the ability to engage in research, are learned for advanced study in graduate school or for competing for well paying positions in the scientific community. One goal of our academic programs is to have a pipeline of research activities from high school to four year college, to graduate school, based on the GISS Institute on Climate and Planets model.

RIACS FY2002 Annual Report

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

2002-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

On the design of computer-based models for integrated environmental science.

PubMed

McIntosh, Brian S; Jeffrey, Paul; Lemon, Mark; Winder, Nick

2005-06-01

The current research agenda in environmental science is dominated by calls to integrate science and policy to better understand and manage links between social (human) and natural (nonhuman) processes. Freshwater resource management is one area where such calls can be heard. Designing computer-based models for integrated environmental science poses special challenges to the research community. At present it is not clear whether such tools, or their outputs, receive much practical policy or planning application. It is argued that this is a result of (1) a lack of appreciation within the research modeling community of the characteristics of different decision-making processes including policy, planning, and (2) participation, (3) a lack of appreciation of the characteristics of different decision-making contexts, (4) the technical difficulties in implementing the necessary support tool functionality, and (5) the socio-technical demands of designing tools to be of practical use. This article presents a critical synthesis of ideas from each of these areas and interprets them in terms of design requirements for computer-based models being developed to provide scientific information support for policy and planning. Illustrative examples are given from the field of freshwater resources management. Although computer-based diagramming and modeling tools can facilitate processes of dialogue, they lack adequate simulation capabilities. Component-based models and modeling frameworks provide such functionality and may be suited to supporting problematic or messy decision contexts. However, significant technical (implementation) and socio-technical (use) challenges need to be addressed before such ambition can be realized.

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

NASA Astrophysics Data System (ADS)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into computational science and engineering codes. Finally, we are partnering with the lead PTP developers at IBM, to ensure we are as effective as possible within the Eclipse community development. We are also conducting training and outreach to our user community, including conference BOF sessions, monthly user calls, and an annual user meeting, so that we can best inform the improvements we make to Eclipse PTP. With these activities we endeavor to encourage use of modern software engineering practices, as enabled through the Eclipse IDE, with computational science and engineering applications. These practices include proper use of source code repositories, tracking and rectifying issues, measuring and monitoring code performance changes against both optimizations as well as ever-changing software stacks and configurations on HPC systems, as well as ultimately encouraging development and maintenance of testing suites -- things that have become commonplace in many software endeavors, but have lagged in the development of science applications. We view that the challenge with the increased complexity of both HPC systems and science applications demands the use of better software engineering methods, preferably enabled by modern tools such as Eclipse PTP, to help the computational science community thrive as we evolve the HPC landscape.

Interests diffusion on a semantic multiplex. Comparing Computer Science and American Physical Society communities

NASA Astrophysics Data System (ADS)

D'Agostino, Gregorio; De Nicola, Antonio

2016-10-01

Exploiting the information about members of a Social Network (SN) represents one of the most attractive and dwelling subjects for both academic and applied scientists. The community of Complexity Science and especially those researchers working on multiplex social systems are devoting increasing efforts to outline general laws, models, and theories, to the purpose of predicting emergent phenomena in SN's (e.g. success of a product). On the other side the semantic web community aims at engineering a new generation of advanced services tailored to specific people needs. This implies defining constructs, models and methods for handling the semantic layer of SNs. We combined models and techniques from both the former fields to provide a hybrid approach to understand a basic (yet complex) phenomenon: the propagation of individual interests along the social networks. Since information may move along different social networks, one should take into account a multiplex structure. Therefore we introduced the notion of "Semantic Multiplex". In this paper we analyse two different semantic social networks represented by authors publishing in the Computer Science and those in the American Physical Society Journals. The comparison allows to outline common and specific features.

Expanding the Scope of High-Performance Computing Facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uram, Thomas D.; Papka, Michael E.

The high-performance computing centers of the future will expand their roles as service providers, and as the machines scale up, so should the sizes of the communities they serve. National facilities must cultivate their users as much as they focus on operating machines reliably. The authors present five interrelated topic areas that are essential to expanding the value provided to those performing computational science.

An Analysis of Cloud Computing with Amazon Web Services for the Atmospheric Science Data Center

NASA Astrophysics Data System (ADS)

Gleason, J. L.; Little, M. M.

2013-12-01

NASA science and engineering efforts rely heavily on compute and data handling systems. The nature of NASA science data is such that it is not restricted to NASA users, instead it is widely shared across a globally distributed user community including scientists, educators, policy decision makers, and the public. Therefore NASA science computing is a candidate use case for cloud computing where compute resources are outsourced to an external vendor. Amazon Web Services (AWS) is a commercial cloud computing service developed to use excess computing capacity at Amazon, and potentially provides an alternative to costly and potentially underutilized dedicated acquisitions whenever NASA scientists or engineers require additional data processing. AWS desires to provide a simplified avenue for NASA scientists and researchers to share large, complex data sets with external partners and the public. AWS has been extensively used by JPL for a wide range of computing needs and was previously tested on a NASA Agency basis during the Nebula testing program. Its ability to support the Langley Science Directorate needs to be evaluated by integrating it with real world operational needs across NASA and the associated maturity that would come with that. The strengths and weaknesses of this architecture and its ability to support general science and engineering applications has been demonstrated during the previous testing. The Langley Office of the Chief Information Officer in partnership with the Atmospheric Sciences Data Center (ASDC) has established a pilot business interface to utilize AWS cloud computing resources on a organization and project level pay per use model. This poster discusses an effort to evaluate the feasibility of the pilot business interface from a project level perspective by specifically using a processing scenario involving the Clouds and Earth's Radiant Energy System (CERES) project.

Building professional identity as computer science teachers: Supporting high school computer science teachers through reflection and community building

NASA Astrophysics Data System (ADS)

Ni, Lijun

Computing education requires qualified computing teachers. The reality is that too few high schools in the U.S. have computing/computer science teachers with formal computer science (CS) training, and many schools do not have CS teacher at all. Moreover, teacher retention rate is often low. Beginning teacher attrition rate is particularly high in secondary education. Therefore, in addition to the need for preparing new CS teachers, we also need to support those teachers we have recruited and trained to become better teachers and continue to teach CS. Teacher education literature, especially teacher identity theory, suggests that a strong sense of teacher identity is a major indicator or feature of committed, qualified teachers. However, under the current educational system in the U.S., it could be challenging to establish teacher identity for high school (HS) CS teachers, e.g., due to a lack of teacher certification for CS. This thesis work centers upon understanding the sense of identity HS CS teachers hold and exploring ways of supporting their identity development through a professional development program: the Disciplinary Commons for Computing Educators (DCCE). DCCE has a major focus on promoting reflection on teaching practice and community building. With scaffolded activities such as course portfolio creation, peer review and peer observation among a group of HS CS teachers, it offers opportunities for CS teachers to explicitly reflect on and narrate their teaching, which is a central process of identity building through their participation within the community. In this thesis research, I explore the development of CS teacher identity through professional development programs. I first conducted an interview study with local HS CS teachers to understand their sense of identity and factors influencing their identity formation. I designed and enacted the professional program (DCCE) and conducted case studies with DCCE participants to understand how their participation in DCCE supported their identity development as a CS teacher. Overall, I found that these CS teachers held different teacher identities with varied features related to their motivation and commitment in teaching CS. I identified four concrete factors that contributed to these teachers' sense of professional identity as a CS teacher. I addressed some of these issues for CS teachers' identity development (especially the issue of lacking community) through offering professional development opportunities with a major focus on teacher reflection and community building. Results from this work indicate a potential model of supporting CS identity development, mapping the characteristics of the professional development program with particular facets of CS teacher identity. This work offers further understanding of the unique challenges that current CS teachers are facing in their CS teaching, as well as the challenges of preparing and supporting CS teachers. My findings also suggest guidelines for teacher education and professional development program design and implementation for building committed, qualified CS teachers in ways that promote the development of CS teacher identity.

Data Serving Climate Simulation Science at the NASA Center for Climate Simulation

NASA Technical Reports Server (NTRS)

Salmon, Ellen M.

2011-01-01

The NASA Center for Climate Simulation (NCCS) provides high performance computational resources, a multi-petabyte archive, and data services in support of climate simulation research and other NASA-sponsored science. This talk describes the NCCS's data-centric architecture and processing, which are evolving in anticipation of researchers' growing requirements for higher resolution simulations and increased data sharing among NCCS users and the external science community.

In Pursuit of a Computing Degree: Cultural Implications for American Indians

ERIC Educational Resources Information Center

Kodaseet, Glenda G.; Varma, Roli

2012-01-01

While a number of challenges contribute to the American Indian population's disconnect from information technology (IT), the most glaring is the low number of American Indian students pursuing computer science (CS) studies--a degree essential to IT's entry into and diffusion across communities. Yet, research is scant on factors that contribute to…

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

NASA Astrophysics Data System (ADS)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical community.

PubMed

Mohammed, Yassene; Dickmann, Frank; Sax, Ulrich; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

2010-01-01

Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears".

A framework for detecting communities of unbalanced sizes in networks

NASA Astrophysics Data System (ADS)

Žalik, Krista Rizman; Žalik, Borut

2018-01-01

Community detection in large networks has been a focus of recent research in many of fields, including biology, physics, social sciences, and computer science. Most community detection methods partition the entire network into communities, groups of nodes that have many connections within communities and few connections between them and do not identify different roles that nodes can have in communities. We propose a community detection model that integrates more different measures that can fast identify communities of different sizes and densities. We use node degree centrality, strong similarity with one node from community, maximal similarity of node to community, compactness of communities and separation between communities. Each measure has its own strength and weakness. Thus, combining different measures can benefit from the strengths of each one and eliminate encountered problems of using an individual measure. We present a fast local expansion algorithm for uncovering communities of different sizes and densities and reveals rich information on input networks. Experimental results show that the proposed algorithm is better or as effective as the other community detection algorithms for both real-world and synthetic networks while it requires less time.

EarthCube Activities: Community Engagement Advancing Geoscience Research

NASA Astrophysics Data System (ADS)

Kinkade, D.

2015-12-01

Our ability to advance scientific research in order to better understand complex Earth systems, address emerging geoscience problems, and meet societal challenges is increasingly dependent upon the concept of Open Science and Data. Although these terms are relatively new to the world of research, Open Science and Data in this context may be described as transparency in the scientific process. This includes the discoverability, public accessibility and reusability of scientific data, as well as accessibility and transparency of scientific communication (www.openscience.org). Scientists and the US government alike are realizing the critical need for easy discovery and access to multidisciplinary data to advance research in the geosciences. The NSF-supported EarthCube project was created to meet this need. EarthCube is developing a community-driven common cyberinfrastructure for the purpose of accessing, integrating, analyzing, sharing and visualizing all forms of data and related resources through advanced technological and computational capabilities. Engaging the geoscience community in EarthCube's development is crucial to its success, and EarthCube is providing several opportunities for geoscience involvement. This presentation will provide an overview of the activities EarthCube is employing to entrain the community in the development process, from governance development and strategic planning, to technical needs gathering. Particular focus will be given to the collection of science-driven use cases as a means of capturing scientific and technical requirements. Such activities inform the development of key technical and computational components that collectively will form a cyberinfrastructure to meet the research needs of the geoscience community.

Final Report. Institute for Ultralscale Visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Kwan-Liu; Galli, Giulia; Gygi, Francois

The SciDAC Institute for Ultrascale Visualization brought together leading experts from visualization, high-performance computing, and science application areas to make advanced visualization solutions for SciDAC scientists and the broader community. Over the five-year project, the Institute introduced many new enabling visualization techniques, which have significantly enhanced scientists’ ability to validate their simulations, interpret their data, and communicate with others about their work and findings. This Institute project involved a large number of junior and student researchers, who received the opportunities to work on some of the most challenging science applications and gain access to the most powerful high-performance computing facilitiesmore » in the world. They were readily trained and prepared for facing the greater challenges presented by extreme-scale computing. The Institute’s outreach efforts, through publications, workshops and tutorials, successfully disseminated the new knowledge and technologies to the SciDAC and the broader scientific communities. The scientific findings and experience of the Institute team helped plan the SciDAC3 program.« less

International Symposium on Grids and Clouds (ISGC) 2014

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2014 will be held at Academia Sinica in Taipei, Taiwan from 23-28 March 2014, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC).“Bringing the data scientist to global e-Infrastructures” is the theme of ISGC 2014. The last decade has seen the phenomenal growth in the production of data in all forms by all research communities to produce a deluge of data from which information and knowledge need to be extracted. Key to this success will be the data scientist - educated to use advanced algorithms, applications and infrastructures - collaborating internationally to tackle society’s challenges. ISGC 2014 will bring together researchers working in all aspects of data science from different disciplines around the world to collaborate and educate themselves in the latest achievements and techniques being used to tackle the data deluge. In addition to the regular workshops, technical presentations and plenary keynotes, ISGC this year will focus on how to grow the data science community by considering the educational foundation needed for tomorrow’s data scientist. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities & Social Sciences Application, Virtual Research Environment (including Middleware, tools, services, workflow, ... etc.), Data Management, Big Data, Infrastructure & Operations Management, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC).

Proposal for a Spatial Organization Model in Soil Science (The Example of the European Communities Soil Map).

ERIC Educational Resources Information Center

King, D.; And Others

1994-01-01

Discusses the computational problems of automating paper-based spatial information. A new relational structure for soil science information based on the main conceptual concepts used during conventional cartographic work is proposed. This model is a computerized framework for coherent description of the geographical variability of soils, combined…

Multicore: Fallout from a Computing Evolution

ScienceCinema

Yelick, Kathy [Director, NERSC

2017-12-09

July 22, 2008 Berkeley Lab lecture: Parallel computing used to be reserved for big science and engineering projects, but in two years that's all changed. Even laptops and hand-helds use parallel processors. Unfortunately, the software hasn't kept pace. Kathy Yelick, Director of the National Energy Research Scientific Computing Center at Berkeley Lab, describes the resulting chaos and the computing community's efforts to develop exciting applications that take advantage of tens or hundreds of processors on a single chip.

Integrating Intelligent Systems Domain Knowledge Into the Earth Science Curricula

NASA Astrophysics Data System (ADS)

Güereque, M.; Pennington, D. D.; Pierce, S. A.

2017-12-01

High-volume heterogeneous datasets are becoming ubiquitous, migrating to center stage over the last ten years and transcending the boundaries of computationally intensive disciplines into the mainstream, becoming a fundamental part of every science discipline. Despite the fact that large datasets are now pervasive across industries and academic disciplines, the array of skills is generally absent from earth science programs. This has left the bulk of the student population without access to curricula that systematically teach appropriate intelligent-systems skills, creating a void for skill sets that should be universal given their need and marketability. While some guidance regarding appropriate computational thinking and pedagogy is appearing, there exist few examples where these have been specifically designed and tested within the earth science domain. Furthermore, best practices from learning science have not yet been widely tested for developing intelligent systems-thinking skills. This research developed and tested evidence based computational skill modules that target this deficit with the intention of informing the earth science community as it continues to incorporate intelligent systems techniques and reasoning into its research and classrooms.

The NASA Science Internet: An integrated approach to networking

NASA Technical Reports Server (NTRS)

Rounds, Fred

1991-01-01

An integrated approach to building a networking infrastructure is an absolute necessity for meeting the multidisciplinary science networking requirements of the Office of Space Science and Applications (OSSA) science community. These networking requirements include communication connectivity between computational resources, databases, and library systems, as well as to other scientists and researchers around the world. A consolidated networking approach allows strategic use of the existing science networking within the Federal government, and it provides networking capability that takes into consideration national and international trends towards multivendor and multiprotocol service. It also offers a practical vehicle for optimizing costs and maximizing performance. Finally, and perhaps most important to the development of high speed computing is that an integrated network constitutes a focus for phasing to the National Research and Education Network (NREN). The NASA Science Internet (NSI) program, established in mid 1988, is structured to provide just such an integrated network. A description of the NSI is presented.

Optimizing Engineering Tools Using Modern Ground Architectures

DTIC Science & Technology

2017-12-01

Considerations,” International Journal of Computer Science & Engineering Survey , vol. 5, no. 4, 2014. [10] R. Bell. (n.d). A beginner’s guide to big O notation...scientific community. Traditional computing architectures were not capable of processing the data efficiently, or in some cases, could not process the...thesis investigates how these modern computing architectures could be leveraged by industry and academia to improve the performance and capabilities of

The Center for Nanophase Materials Sciences

NASA Astrophysics Data System (ADS)

Lowndes, Douglas

2005-03-01

The Center for Nanophase Materials Sciences (CNMS) located at Oak Ridge National Laboratory (ORNL) will be the first DOE Nanoscale Science Research Center to begin operation, with construction to be completed in April 2005 and initial operations in October 2005. The CNMS' scientific program has been developed through workshops with the national community, with the goal of creating a highly collaborative research environment to accelerate discovery and drive technological advances. Research at the CNMS is organized under seven Scientific Themes selected to address challenges to understanding and to exploit particular ORNL strengths (see http://cnms.ornl.govhttp://cnms.ornl.gov). These include extensive synthesis and characterization capabilities for soft, hard, nanostructured, magnetic and catalytic materials and their composites; neutron scattering at the Spallation Neutron Source and High Flux Isotope Reactor; computational nanoscience in the CNMS' Nanomaterials Theory Institute and utilizing facilities and expertise of the Center for Computational Sciences and the new Leadership Scientific Computing Facility at ORNL; a new CNMS Nanofabrication Research Laboratory; and a suite of unique and state-of-the-art instruments to be made reliably available to the national community for imaging, manipulation, and properties measurements on nanoscale materials in controlled environments. The new research facilities will be described together with the planned operation of the user research program, the latter illustrated by the current ``jump start'' user program that utilizes existing ORNL/CNMS facilities.

Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

PubMed

Kapur, Tina; Pieper, Steve; Fedorov, Andriy; Fillion-Robin, J-C; Halle, Michael; O'Donnell, Lauren; Lasso, Andras; Ungi, Tamas; Pinter, Csaba; Finet, Julien; Pujol, Sonia; Jagadeesan, Jayender; Tokuda, Junichi; Norton, Isaiah; Estepar, Raul San Jose; Gering, David; Aerts, Hugo J W L; Jakab, Marianna; Hata, Nobuhiko; Ibanez, Luiz; Blezek, Daniel; Miller, Jim; Aylward, Stephen; Grimson, W Eric L; Fichtinger, Gabor; Wells, William M; Lorensen, William E; Schroeder, Will; Kikinis, Ron

2016-10-01

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision. Copyright © 2016 Elsevier B.V. All rights reserved.

Using Cloud-Computing Applications to Support Collaborative Scientific Inquiry: Examining Pre-Service Teachers' Perceived Barriers to Integration

ERIC Educational Resources Information Center

Donna, Joel D.; Miller, Brant G.

2013-01-01

Technology plays a crucial role in facilitating collaboration within the scientific community. Cloud-computing applications, such as Google Drive, can be used to model such collaboration and support inquiry within the secondary science classroom. Little is known about pre-service teachers' beliefs related to the envisioned use of collaborative,…

Use of Standardized Test Scores to Predict Success in a Computer Applications Course

ERIC Educational Resources Information Center

Harris, Robert V.; King, Stephanie B.

2016-01-01

The purpose of this study was to see if a relationship existed between American College Testing (ACT) scores (i.e., English, reading, mathematics, science reasoning, and composite) and student success in a computer applications course at a Mississippi community college. The study showed that while the ACT scores were excellent predictors of…

LINUX, Virtualization, and the Cloud: A Hands-On Student Introductory Lab

ERIC Educational Resources Information Center

Serapiglia, Anthony

2013-01-01

Many students are entering Computer Science education with limited exposure to operating systems and applications other than those produced by Apple or Microsoft. This gap in familiarity with the Open Source community can quickly be bridged with a simple exercise that can also be used to strengthen two other important current computing concepts,…

Embodying Our Values in Our Teaching Practices: Building Open and Critical Discourse through Computer Mediated Communication

ERIC Educational Resources Information Center

Geelan, David R.; Taylor, Peter C.

2004-01-01

Computer mediated communication--including web pages, email and web-based bulletin boards--was used to support the development of a cooperative learning community among students in a web-based distance education unit for practicing science and mathematics educators. The students lived in several Australian states and a number of Pacific Rim…

eHealth research from the user's perspective.

PubMed

Hesse, Bradford W; Shneiderman, Ben

2007-05-01

The application of information technology (IT) to issues of healthcare delivery has had a long and tortuous history in the United States. Within the field of eHealth, vanguard applications of advanced computing techniques, such as applications in artificial intelligence or expert systems, have languished in spite of a track record of scholarly publication and decisional accuracy. The problem is one of purpose, of asking the right questions for the science to solve. Historically, many computer science pioneers have been tempted to ask "what can the computer do?" New advances in eHealth are prompting developers to ask "what can people do?" How can eHealth take part in national goals for healthcare reform to empower relationships between healthcare professionals and patients, healthcare teams and families, and hospitals and communities to improve health equitably throughout the population? To do this, eHealth researchers must combine best evidence from the user sciences (human factors engineering, human-computer interaction, psychology, and usability) with best evidence in medicine to create transformational improvements in the quality of care that medicine offers. These improvements should follow recommendations from the Institute of Medicine to create a healthcare system that is (1) safe, (2) effective (evidence based), (3) patient centered, and (4) timely. Relying on the eHealth researcher's intuitive grasp of systems issues, improvements should be made with considerations of users and beneficiaries at the individual (patient-physician), group (family-staff), community, and broad environmental levels.

CSBB: synthetic biology research at Newcastle University.

PubMed

Goñi-Moreno, Angel; Wipat, Anil; Krasnogor, Natalio

2017-06-15

The Centre for Synthetic Biology and the Bioeconomy (CSBB) brings together a far-reaching multidisciplinary community across all Newcastle University's faculties - Medical Sciences, Science, Agriculture and Engineering, and Humanities, Arts and Social Sciences. The CSBB focuses on many different areas of Synthetic Biology, including bioprocessing, computational design and in vivo computation, as well as improving understanding of basic molecular machinery. Such breadth is supported by major national and international research funding, a range of industrial partners in the North East of England and beyond, as well as a large number of doctoral and post-doctoral researchers. The CSBB trains the next generation of scientists through a 1-year MSc in Synthetic Biology. © 2017 The Author(s).

Science and Software

NASA Astrophysics Data System (ADS)

Zelt, C. A.

2017-12-01

Earth science attempts to understand how the earth works. This research often depends on software for modeling, processing, inverting or imaging. Freely sharing open-source software is essential to prevent reinventing the wheel and allows software to be improved and applied in ways the original author may never have envisioned. For young scientists, releasing software can increase their name ID when applying for jobs and funding, and create opportunities for collaborations when scientists who collect data want the software's creator to be involved in their project. However, we frequently hear scientists say software is a tool, it's not science. Creating software that implements a new or better way of earth modeling or geophysical processing, inverting or imaging should be viewed as earth science. Creating software for things like data visualization, format conversion, storage, or transmission, or programming to enhance computational performance, may be viewed as computer science. The former, ideally with an application to real data, can be published in earth science journals, the latter possibly in computer science journals. Citations in either case should accurately reflect the impact of the software on the community. Funding agencies need to support more software development and open-source releasing, and the community should give more high-profile awards for developing impactful open-source software. Funding support and community recognition for software development can have far reaching benefits when the software is used in foreseen and unforeseen ways, potentially for years after the original investment in the software development. For funding, an open-source release that is well documented should be required, with example input and output files. Appropriate funding will provide the incentive and time to release user-friendly software, and minimize the need for others to duplicate the effort. All funded software should be available through a single web site, ideally maintained by someone in a funded position. Perhaps the biggest challenge is the reality that researches who use software, as opposed to develop software, are more attractive university hires because they are more likely to be "big picture" scientists that publish in the highest profile journals, although sometimes the two go together.

Un profil de compétences pour les professeurs d'informatique de l'enseignement secondaire camerounais

NASA Astrophysics Data System (ADS)

Fouda Ndjodo, Marcel; Ngah, Virginie Blanche; Zobo, Erick Patrick

2013-07-01

A competency profile for teachers of Computer Science in Cameroonian secondary education - In 1998, the Cameroonian government decided to introduce Computer Science as a school subject. To implement this decision, it began to train teachers of Computer Science according to the same training model used for teachers of other disciplines. Despite the consensus that seems to be emerging from the scientific community regarding the need to give priority to a cross-disciplinary use of information and communication technologies (ICT) in primary and secondary education, some countries, such as Cameroon, have opted to teach Computer Science. While such a political choice might in principle appear to be inappropriate for the development of students' ICT skills, the article shows that it nevertheless introduces teachers into the system who have a predisposition to act as catalysts for the pedagogical integration of ICT. Such a development could occur provided these teachers are trained in a range of additional skills - those proposed in the article - which would enable them to contribute effectively. If this approach were implemented, sub-Saharan countries such as Cameroon would, in their Computer Science teachers, have access to human resources capable of quickly generalising the cross-disciplinary use of ICT in the education system.

Advancing Water Science through Improved Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Koch, B. J.; Miles, B.; Rai, A.; Ahalt, S.; Band, L. E.; Minsker, B.; Palmer, M.; Williams, M. R.; Idaszak, R.; Whitton, M. C.

2012-12-01

Major scientific advances are needed to help address impacts of climate change and increasing human-mediated environmental modification on the water cycle at global and local scales. However, such advances within the water sciences are limited in part by inadequate information infrastructures. For example, cyberinfrastructure (CI) includes the integrated computer hardware, software, networks, sensors, data, and human capital that enable scientific workflows to be carried out within and among individual research efforts and across varied disciplines. A coordinated transformation of existing CI and development of new CI could accelerate the productivity of water science by enabling greater discovery, access, and interoperability of data and models, and by freeing scientists to do science rather than create and manage technological tools. To elucidate specific ways in which improved CI could advance water science, three challenges confronting the water science community were evaluated: 1) How does ecohydrologic patch structure affect nitrogen transport and fate in watersheds?, 2) How can human-modified environments emulate natural water and nutrient cycling to enhance both human and ecosystem well-being?, 3) How do changes in climate affect water availability to support biodiversity and human needs? We assessed the approaches used by researchers to address components of these challenges, identified barriers imposed by limitations of current CI, and interviewed leaders in various water science subdisciplines to determine the most recent CI tools employed. Our preliminary findings revealed four areas where CI improvements are likely to stimulate scientific advances: 1) sensor networks, 2) data quality assurance/quality control, 3) data and modeling standards, 4) high performance computing. In addition, the full potential of a re-envisioned water science CI cannot be realized without a substantial training component. In light of these findings, we suggest that CI industry-proven practices such as open-source community architecture, agile development methodologies, and sound software engineering methods offer a promising pathway to a transformed water science CI capable of meeting the demands of both individual scientists and community-wide research initiatives.

ISCR Annual Report: Fical Year 2004

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGraw, J R

2005-03-03

Large-scale scientific computation and all of the disciplines that support and help to validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of computational simulation as a tool of scientific and engineering research is underscored in the November 2004 statement of the Secretary of Energy that, ''high performance computing is the backbone of the nation's science and technologymore » enterprise''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use efficiently. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to LLNL's core missions than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In Fiscal Year 2004, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for short- and long-term visits with the aim of encouraging long-term academic research agendas that address LLNL's research priorities. Through such collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''feet and hands'' that carry those advances into the Laboratory and incorporates them into practice. ISCR research participants are integrated into LLNL's Computing and Applied Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other five institutes of the URP, it navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort.« less

Computational materials science and engineering education: A survey of trends and needs

NASA Astrophysics Data System (ADS)

Thornton, K.; Nola, Samanthule; Edwin Garcia, R.; Asta, Mark; Olson, G. B.

2009-10-01

Results from a recent reassessment of the state of computational materials science and engineering (CMSE) education are reported. Surveys were distributed to the chairs and heads of materials programs, faculty members engaged in computational research, and employers of materials scientists and engineers, mainly in the United States. The data was compiled to assess current course offerings related to CMSE, the general climate for introducing computational methods in MSE curricula, and the requirements from the employers’ viewpoint. Furthermore, the available educational resources and their utilization by the community are examined. The surveys show a general support for integrating computational content into MSE education. However, they also reflect remaining issues with implementation, as well as a gap between the tools being taught in courses and those that are used by employers. Overall, the results suggest the necessity for a comprehensively developed vision and plans to further the integration of computational methods into MSE curricula.

Multicore: Fallout From a Computing Evolution (LBNL Summer Lecture Series)

ScienceCinema

Yelick, Kathy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

2018-05-07

Summer Lecture Series 2008: Parallel computing used to be reserved for big science and engineering projects, but in two years that's all changed. Even laptops and hand-helds use parallel processors. Unfortunately, the software hasn't kept pace. Kathy Yelick, Director of the National Energy Research Scientific Computing Center at Berkeley Lab, describes the resulting chaos and the computing community's efforts to develop exciting applications that take advantage of tens or hundreds of processors on a single chip.

Project : semi-autonomous parking for enhanced safety and efficiency.

DOT National Transportation Integrated Search

2016-04-01

Index coding, a coding formulation traditionally analyzed in the theoretical computer science and : information theory communities, has received considerable attention in recent years due to its value in : wireless communications and networking probl...

EUDAT: A New Cross-Disciplinary Data Infrastructure For Science

NASA Astrophysics Data System (ADS)

Lecarpentier, Damien; Michelini, Alberto; Wittenburg, Peter

2013-04-01

In recent years significant investments have been made by the European Commission and European member states to create a pan-European e-Infrastructure supporting multiple research communities. As a result, a European e-Infrastructure ecosystem is currently taking shape, with communication networks, distributed grids and HPC facilities providing European researchers from all fields with state-of-the-art instruments and services that support the deployment of new research facilities on a pan-European level. However, the accelerated proliferation of data - newly available from powerful new scientific instruments, simulations and the digitization of existing resources - has created a new impetus for increasing efforts and investments in order to tackle the specific challenges of data management, and to ensure a coherent approach to research data access and preservation. EUDAT is a pan-European initiative that started in October 2011 and which aims to help overcome these challenges by laying out the foundations of a Collaborative Data Infrastructure (CDI) in which centres offering community-specific support services to their users could rely on a set of common data services shared between different research communities. Although research communities from different disciplines have different ambitions and approaches - particularly with respect to data organization and content - they also share many basic service requirements. This commonality makes it possible for EUDAT to establish common data services, designed to support multiple research communities, as part of this CDI. During the first year, EUDAT has been reviewing the approaches and requirements of a first subset of communities from linguistics (CLARIN), solid earth sciences (EPOS), climate sciences (ENES), environmental sciences (LIFEWATCH), and biological and medical sciences (VPH), and shortlisted four generic services to be deployed as shared services on the EUDAT infrastructure. These services are data replication from site to site, data staging to compute facilities, metadata, and easy storage. A number of enabling services such as distributed authentication and authorization, persistent identifiers, hosting of services, workspaces and centre registry were also discussed. The services being designed in EUDAT will thus be of interest to a broad range of communities that lack their own robust data infrastructures, or that are simply looking for additional storage and/or computing capacities to better access, use, re-use, and preserve their data. The first pilots were completed in 2012 and a pre-production ready operational infrastructure, comprised of five sites (RZG, CINECA, SARA, CSC, FZJ), offering 480TB of online storage and 4PB of near-line (tape) storage, initially serving four user communities (ENES, EPOS, CLARIN, VPH) was established. These services shall be available to all communities in a production environment by 2014. Although EUDAT has initially focused on a subset of research communities, it aims to engage with other communities interested in adapting their solutions or contributing to the design of the infrastructure. Discussions with other research communities - belonging to the fields of environmental sciences, biomedical science, physics, social sciences and humanities - have already begun and are following a pattern similar to the one we adopted with the initial communities. The next step will consist of integrating representatives from these communities into the existing pilots and task forces so as to include them in the process of designing the services and, ultimately, shaping the future CDI.

Learning Analytics and Computational Techniques for Detecting and Evaluating Patterns in Learning: An Introduction to the Special Issue

ERIC Educational Resources Information Center

Martin, Taylor; Sherin, Bruce

2013-01-01

The learning sciences community's interest in learning analytics (LA) has been growing steadily over the past several years. Three recent symposia on the theme (at the American Educational Research Association 2011 and 2012 annual conferences, and the International Conference of the Learning Sciences 2012), organized by Paulo Blikstein, led…

Science preparedness and science response: perspectives on the dynamics of preparedness conference.

PubMed

Lant, Timothy; Lurie, Nicole

2013-01-01

The ability of the scientific modeling community to meaningfully contribute to postevent response activities during public health emergencies was the direct result of a discrete set of preparedness activities as well as advances in theory and technology. Scientists and decision-makers have recognized the value of developing scientific tools (e.g. models, data sets, communities of practice) to prepare them to be able to respond quickly--in a manner similar to preparedness activities by first-responders and emergency managers. Computational models have matured in their ability to better inform response plans by modeling human behaviors and complex systems. We advocate for further development of science preparedness activities as deliberate actions taken in advance of an unpredicted event (or an event with unknown consequences) to increase the scientific tools and evidence-base available to decision makers and the whole-of-community to limit adverse outcomes.

Data Access, Interoperability and Sustainability: Key Challenges for the Evolution of Science Capabilities

NASA Astrophysics Data System (ADS)

Walton, A. L.

2015-12-01

In 2016, the National Science Foundation (NSF) will support a portfolio of activities and investments focused upon challenges in data access, interoperability, and sustainability. These topics are fundamental to science questions of increasing complexity that require multidisciplinary approaches and expertise. Progress has become tractable because of (and sometimes complicated by) unprecedented growth in data (both simulations and observations) and rapid advances in technology (such as instrumentation in all aspects of the discovery process, together with ubiquitous cyberinfrastructure to connect, compute, visualize, store, and discover). The goal is an evolution of capabilities for the research community based on these investments, scientific priorities, technology advances, and policies. Examples from multiple NSF directorates, including investments by the Advanced Cyberinfrastructure Division, are aimed at these challenges and can provide the geosciences research community with models and opportunities for participation. Implications for the future are highlighted, along with the importance of continued community engagement on key issues.

Online citizen science games: Opportunities for the biological sciences.

PubMed

Curtis, Vickie

2014-12-01

Recent developments in digital technologies and the rise of the Internet have created new opportunities for citizen science. One of these has been the development of online citizen science games where complex research problems have been re-imagined as online multiplayer computer games. Some of the most successful examples of these can be found within the biological sciences, for example, Foldit, Phylo and EteRNA. These games offer scientists the opportunity to crowdsource research problems, and to engage with those outside the research community. Games also enable those without a background in science to make a valid contribution to research, and may also offer opportunities for informal science learning.

The Quantum Engineering Conundrum

NASA Astrophysics Data System (ADS)

Monroe, Christopher

2017-04-01

There is newfound rush and excitement in Quantum Information Science, as this field seems to be moving toward an industrial/engineering phase. However, this evolution will require that quantum science, long the domain of academics and other researchers, make the leap to sustained engineering efforts in order to fabricate practical devices. I will address the conundrum, that full-blooded engineering does not generally happen on campuses, while many in the professional engineering and computer science community do not believe in quantum physics!

Advances in Cross-Cutting Ideas for Computational Climate Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, Esmond; Evans, Katherine J.; Caldwell, Peter

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Advances in Cross-Cutting Ideas for Computational Climate Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, E.; Evans, K.; Caldwell, P.

This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Welcome to the NASA High Performance Computing and Communications Computational Aerosciences (CAS) Workshop 2000

NASA Technical Reports Server (NTRS)

Schulbach, Catherine H. (Editor)

2000-01-01

The purpose of the CAS workshop is to bring together NASA's scientists and engineers and their counterparts in industry, other government agencies, and academia working in the Computational Aerosciences and related fields. This workshop is part of the technology transfer plan of the NASA High Performance Computing and Communications (HPCC) Program. Specific objectives of the CAS workshop are to: (1) communicate the goals and objectives of HPCC and CAS, (2) promote and disseminate CAS technology within the appropriate technical communities, including NASA, industry, academia, and other government labs, (3) help promote synergy among CAS and other HPCC scientists, and (4) permit feedback from peer researchers on issues facing High Performance Computing in general and the CAS project in particular. This year we had a number of exciting presentations in the traditional aeronautics, aerospace sciences, and high-end computing areas and in the less familiar (to many of us affiliated with CAS) earth science, space science, and revolutionary computing areas. Presentations of more than 40 high quality papers were organized into ten sessions and presented over the three-day workshop. The proceedings are organized here for easy access: by author, title and topic.

Filling the gap between biology and computer science

PubMed Central

Aguilar-Ruiz, Jesús S; Moore, Jason H; Ritchie, Marylyn D

2008-01-01

This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community. PMID:18822148

EVER-EST: a virtual research environment for Earth Sciences

NASA Astrophysics Data System (ADS)

Marelli, Fulvio; Albani, Mirko; Glaves, Helen

2016-04-01

There is an increasing requirement for researchers to work collaboratively using common resources whilst being geographically dispersed. By creating a virtual research environment (VRE) using a service oriented architecture (SOA) tailored to the needs of Earth Science (ES) communities, the EVEREST project will provide a range of both generic and domain specific data management services to support a dynamic approach to collaborative research. EVER-EST will provide the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. Researchers will be able to seamlessly manage both the data involved in their computationally intensive disciplines and the scientific methods applied in their observations and modelling, which lead to the specific results that need to be attributable, validated and shared both within the community and more widely e.g. in the form of scholarly communications. Central to the EVEREST approach is the concept of the Research Object (RO) , which provides a semantically rich mechanism to aggregate related resources about a scientific investigation so that they can be shared together using a single unique identifier. Although several e-laboratories are incorporating the research object concept in their infrastructure, the EVER-EST VRE will be the first infrastructure to leverage the concept of Research Objects and their application in observational rather than experimental disciplines. Development of the EVEREST VRE will leverage the results of several previous projects which have produced state-of-the-art technologies for scientific data management and curation as well those which have developed models, techniques and tools for the preservation of scientific methods and their implementation in computational forms such as scientific workflows. The EVER-EST data processing infrastructure will be based on a Cloud Computing approach, in which new applications can be integrated using "virtual machines" that have their own specifications (disk size, processor speed, operating system etc.) and run on shared private (physical deployment over local hardware) or commercial Cloud infrastructures. The EVER-EST e-infrastructure will be validated by four virtual research communities (VRC) covering different multidisciplinary Earth Science domains including: ocean monitoring, natural hazards, land monitoring and risk management (volcanoes and seismicity). Each VRC will use the virtual research environment according to its own specific requirements for data, software, best practice and community engagement. This user-centric approach will allow an assessment to be made of the capability for the proposed solution to satisfy the heterogeneous needs of a variety of Earth Science communities for more effective collaboration, and higher efficiency and creativity in research. EVER-EST is funded by the European Commission's H2020 for three years starting in October 2015. The project is led by the European Space Agency (ESA), involves some of the major European Earth Science data providers/users including NERC, DLR, INGV, CNR and SatCEN.

Analogy Mapping Development for Learning Programming

NASA Astrophysics Data System (ADS)

Sukamto, R. A.; Prabawa, H. W.; Kurniawati, S.

2017-02-01

Programming skill is an important skill for computer science students, whereas nowadays, there many computer science students are lack of skills and information technology knowledges in Indonesia. This is contrary with the implementation of the ASEAN Economic Community (AEC) since the end of 2015 which is the qualified worker needed. This study provided an effort for nailing programming skills by mapping program code to visual analogies as learning media. The developed media was based on state machine and compiler principle and was implemented in C programming language. The state of every basic condition in programming were successful determined as analogy visualization.

Modeling hazardous mass flows Geoflows09: Mathematical and computational aspects of modeling hazardous geophysical mass flows; Seattle, Washington, 9–11 March 2009

USGS Publications Warehouse

Iverson, Richard M.; LeVeque, Randall J.

2009-01-01

A recent workshop at the University of Washington focused on mathematical and computational aspects of modeling the dynamics of dense, gravity-driven mass movements such as rock avalanches and debris flows. About 30 participants came from seven countries and brought diverse backgrounds in geophysics; geology; physics; applied and computational mathematics; and civil, mechanical, and geotechnical engineering. The workshop was cosponsored by the U.S. Geological Survey Volcano Hazards Program, by the U.S. National Science Foundation through a Vertical Integration of Research and Education (VIGRE) in the Mathematical Sciences grant to the University of Washington, and by the Pacific Institute for the Mathematical Sciences. It began with a day of lectures open to the academic community at large and concluded with 2 days of focused discussions and collaborative work among the participants.

Automating CapCom: Pragmatic Operations and Technology Research for Human Exploration of Mars

NASA Technical Reports Server (NTRS)

Clancey, William J.

2003-01-01

During the Apollo program, NASA and the scientific community used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. More recently, computer scientists and human factors specialists have followed geologists and biologists into the field, learning how science is actually done on expeditions in extreme environments. Research stations have been constructed by the Mars Society in the Arctic and American southwest, providing facilities for hundreds of researchers to investigate how small crews might live and work on Mars. Combining these interests-science, operations, and technology-in Mars analog field expeditions provides tremendous synergy and authenticity to speculations about Mars missions. By relating historical analyses of Apollo and field science, engineers are creating experimental prototypes that provide significant new capabilities, such as a computer system that automates some of the functions of Apollo s CapCom. Thus, analog studies have created a community of practice-a new collaboration between scientists and engineers-so that technology begins with real human needs and works incrementally towards the challenges of the human exploration of Mars.

On transferring the grid technology to the biomedical community.

PubMed

Mohammed, Yassene; Sax, Ulrich; Dickmann, Frank; Lippert, Joerg; Solodenko, Juri; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

2010-01-01

Natural scientists such as physicists pioneered the sharing of computing resources, which resulted in the Grid. The inter domain transfer process of this technology has been an intuitive process. Some difficulties facing the life science community can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies that have achieved certain stability. Grid and Cloud solutions are technologies that are still in flux. We illustrate how Grid computing creates new difficulties for the technology transfer process that are not considered in Bozeman's model. We show why the success of health Grids should be measured by the qualified scientific human capital and opportunities created, and not primarily by the market impact. With two examples we show how the Grid technology transfer theory corresponds to the reality. We conclude with recommendations that can help improve the adoption of Grid solutions into the biomedical community. These results give a more concise explanation of the difficulties most life science IT projects are facing in the late funding periods, and show some leveraging steps which can help to overcome the "vale of tears".

Grid Technology as a Cyber Infrastructure for Earth Science Applications

NASA Technical Reports Server (NTRS)

Hinke, Thomas H.

2004-01-01

This paper describes how grids and grid service technologies can be used to develop an infrastructure for the Earth Science community. This cyberinfrastructure would be populated with a hierarchy of services, including discipline specific services such those needed by the Earth Science community as well as a set of core services that are needed by most applications. This core would include data-oriented services used for accessing and moving data as well as computer-oriented services used to broker access to resources and control the execution of tasks on the grid. The availability of such an Earth Science cyberinfrastructure would ease the development of Earth Science applications. With such a cyberinfrastructure, application work flows could be created to extract data from one or more of the Earth Science archives and then process it by passing it through various persistent services that are part of the persistent cyberinfrastructure, such as services to perform subsetting, reformatting, data mining and map projections.

The International Symposium on Grids and Clouds

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2012 will be held at Academia Sinica in Taipei from 26 February to 2 March 2012, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). 2012 is the decennium anniversary of the ISGC which over the last decade has tracked the convergence, collaboration and innovation of individual researchers across the Asia Pacific region to a coherent community. With the continuous support and dedication from the delegates, ISGC has provided the primary international distributed computing platform where distinguished researchers and collaboration partners from around the world share their knowledge and experiences. The last decade has seen the wide-scale emergence of e-Infrastructure as a critical asset for the modern e-Scientist. The emergence of large-scale research infrastructures and instruments that has produced a torrent of electronic data is forcing a generational change in the scientific process and the mechanisms used to analyse the resulting data deluge. No longer can the processing of these vast amounts of data and production of relevant scientific results be undertaken by a single scientist. Virtual Research Communities that span organisations around the world, through an integrated digital infrastructure that connects the trust and administrative domains of multiple resource providers, have become critical in supporting these analyses. Topics covered in ISGC 2012 include: High Energy Physics, Biomedicine & Life Sciences, Earth Science, Environmental Changes and Natural Disaster Mitigation, Humanities & Social Sciences, Operations & Management, Middleware & Interoperability, Security and Networking, Infrastructure Clouds & Virtualisation, Business Models & Sustainability, Data Management, Distributed Volunteer & Desktop Grid Computing, High Throughput Computing, and High Performance, Manycore & GPU Computing.

Network-based approaches to climate knowledge discovery

NASA Astrophysics Data System (ADS)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

Mild Cognitive Impairment: What Do We Do Now?

MedlinePlus

... in studies that focus on individual health, computer use and technology, family relationships and caregiving, community services, housing, and ... Reserve Officer Training Corps Navy Research Centers Science, Technology, and ... of Education School of Performing Arts College Office of the ...

Developing the Next Generation of Science Data System Engineers

NASA Technical Reports Server (NTRS)

Moses, John F.; Behnke, Jeanne; Durachka, Christopher D.

2016-01-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Developing the Next Generation of Science Data System Engineers

NASA Astrophysics Data System (ADS)

Moses, J. F.; Durachka, C. D.; Behnke, J.

2015-12-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects. The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peer mentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breath of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multi-discipline science and practitioner communities expect to have access to all types of observational data. This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

eHealth Research from the User’s Perspective

PubMed Central

Hesse, Bradford W.; Shneiderman, Ben

2007-01-01

The application of Information Technology (IT) to issues of healthcare delivery has had a long and tortuous history in the U.S. Within the field of eHealth, vanguard applications of advanced computing techniques, such as applications in artificial intelligence or expert systems, have languished in spite of a track record of scholarly publication and decisional accuracy. The problem is one of purpose, of asking the right questions for the science to solve. Historically, many computer science pioneers have been tempted to ask “what can the computer do?” New advances in eHealth are prompting developers to ask “what can people do?” How can eHealth take part in national goals for healthcare reform to empower relationships between healthcare professionals and patients, healthcare teams and families, and hospitals and communities to improve health equitably throughout the population? To do this, eHealth researchers must combine best evidence from the user sciences (human factors engineering, human-computer interaction, psychology, and usability) with best evidence in medicine to create transformational improvements in the quality of care that medicine offers. These improvements should follow recommendations from the Institute of Medicine to create a health care system that is (a) safe, (b) effective (evidence-based), (c) patient-centered, and (d) timely. Relying on the eHealth researcher’s intuitive grasp of systems issues, improvements should be made with considerations of users and beneficiaries at the individual (patient/physician), group (family/staff), community, and broad environmental levels. PMID:17466825

The building of the EUDAT Cross-Disciplinary Data Infrastructure

NASA Astrophysics Data System (ADS)

Lecarpentier, Damien; Michelini, Alberto; Wittenburg, Peter

2013-04-01

The EUDAT project is a European data initiative that brings together a unique consortium of 25 partners - including research communities, national data and high performance computing (HPC) centers, technology providers, and funding agencies - from 13 countries. EUDAT aims to build a sustainable cross-disciplinary and cross-national Commom Data Infrastructure (CDI) that provides a set of shared services for accessing and preserving research data. The design and deployment of these services is being coordinated by multi-disciplinary task forces comprising representatives from research communities and data centers. One of EUDAT's fundamental goals is the facilitation of cross-disciplinary data-intensive science. By providing opportunity for disciplines from across the spectrum to share data and cross-fertilize ideas, the CDI will encourage progress towards this vision of open and participatory data-intensive science. EUDAT will also facilitate this process through the creation of teams of experts from different disciplines, aiming to cooperatively develop services to meet the needs of several communities. Five research communities joined the EUDAT initiative at the start - CLARIN (Linguistics), ENES (Climate Modeling), EPOS (Earth Sciences), LifeWatch (Environmental Sciences - Biodiversity), VPH (Biological and Medical Sciences). They are acting as partners in the project, and have clear tasks and commitments. Since EUDAT started on the 1st of October 2011, we have been reviewing the approaches and requirements of these five communities regarding the deployment and use of a cross-disciplinary and persistent data e-Infrastructure. This analysis was conducted through interviews and frequent interactions with representatives of the communities. In this talk will be provided an updated status of the current CDI with specific refernce to the solid Earth science commnity of EPOS.

IEDA: Making Small Data BIG Through Interdisciplinary Partnerships Among Long-tail Domains

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Carbotte, S. M.; Arko, R. A.; Ferrini, V. L.; Hsu, L.; Song, L.; Ghiorso, M. S.; Walker, D. J.

2014-12-01

The Big Data world in the Earth Sciences so far exists primarily for disciplines that generate massive volumes of observational or computed data using large-scale, shared instrumentation such as global sensor networks, satellites, or high-performance computing facilities. These data are typically managed and curated by well-supported community data facilities that also provide the tools for exploring the data through visualization or statistical analysis. In many other domains, especially those where data are primarily acquired by individual investigators or small teams (known as 'Long-tail data'), data are poorly shared and integrated, lacking a community-based data infrastructure that ensures persistent access, quality control, standardization, and integration of data, as well as appropriate tools to fully explore and mine the data within the context of broader Earth Science datasets. IEDA (Integrated Earth Data Applications, www.iedadata.org) is a data facility funded by the US NSF to develop and operate data services that support data stewardship throughout the full life cycle of observational data in the solid earth sciences, with a focus on the data management needs of individual researchers. IEDA builds on a strong foundation of mature disciplinary data systems for marine geology and geophysics, geochemistry, and geochronology. These systems have dramatically advanced data resources in those long-tail Earth science domains. IEDA has strengthened these resources by establishing a consolidated, enterprise-grade infrastructure that is shared by the domain-specific data systems, and implementing joint data curation and data publication services that follow community standards. In recent years, other domain-specific data efforts have partnered with IEDA to take advantage of this infrastructure and improve data services to their respective communities with formal data publication, long-term preservation of data holdings, and better sustainability. IEDA hopes to foster such partnerships with streamlined data services, including user-friendly, single-point interfaces for data submission, discovery, and access across the partner systems to support interdisciplinary science.

Information science and technology developments within the National Biological Information Infrastructure

USGS Publications Warehouse

Frame, M.T.; Cotter, G.; Zolly, L.; Little, J.

2002-01-01

Whether your vantage point is that of an office window or a national park, your view undoubtedly encompasses a rich diversity of life forms, all carefully studied or managed by some scientist, resource manager, or planner. A few simple calculations - the number of species, their interrelationships, and the many researchers studying them - and you can easily see the tremendous challenges that the resulting biological data presents to the information and computer science communities. Biological information varies in format and content: it may pertain to a particular species or an entire ecosystem; it can contain land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents, the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993 on the recommendation of the National Research Council (National Research Council 1993). The NBII is designed to address these issues on a national scale, and through international partnerships. This paper discusses current information and computer science efforts within the National Biological Information Infrastructure Program, and future computer science research endeavors that are needed to address the ever-growing issues related to our nation's biological concerns. ?? 2003 by The Haworth Press, Inc. All rights reserved.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

1999-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Community Coordinated Modeling Center Support of Science Needs for Integrated Data Environment

NASA Technical Reports Server (NTRS)

Kuznetsova, M. M.; Hesse, M.; Rastatter, L.; Maddox, M.

2007-01-01

Space science models are essential component of integrated data environment. Space science models are indispensable tools to facilitate effective use of wide variety of distributed scientific sources and to place multi-point local measurements into global context. The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the- art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. The majority of models residing at CCMC are comprehensive computationally intensive physics-based models. To allow the models to be driven by data relevant to particular events, the CCMC developed an online data file generation tool that automatically downloads data from data providers and transforms them to required format. CCMC provides a tailored web-based visualization interface for the model output, as well as the capability to download simulations output in portable standard format with comprehensive metadata and user-friendly model output analysis library of routines that can be called from any C supporting language. CCMC is developing data interpolation tools that enable to present model output in the same format as observations. CCMC invite community comments and suggestions to better address science needs for the integrated data environment.

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

NASA Astrophysics Data System (ADS)

Strayer, Michael

2005-01-01

Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds immense promise. In this environment, I believe it is necessary to institute a system of science based performance metrics to help quantify our progress towards science goals and scientific computing. As a final comment I would like to reaffirm that the shifting landscapes of science will force changes to our computational sciences, and leave you with the quote from Richard Hamming, 'The purpose of computing is insight, not numbers'.

Software Assurance Curriculum Project Volume 4: Community College Education

DTIC Science & Technology

2011-09-01

no previous programming or computer science experience expected) • Precalculus -ready (that is, proficiency sufficient to enter college-level... precalculus course) • English Composition I-ready (that is, proficiency sufficient to enter college-level English I course) Co-Requisite Discrete

The U.S. "Tox21 Community" and the Future of Toxicology

EPA Science Inventory

In early 2008, the National Institute of Environmental Health Sciences/National Toxicology Program, the NIH Chemical Genomics Center, and the Environmental Protection Agency’s National Center for Computational Toxicology entered into a Memorandum of Understanding to collaborate o...

CyberShake: Running Seismic Hazard Workflows on Distributed HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Graves, R. W.; Gill, D.; Olsen, K. B.; Milner, K. R.; Yu, J.; Jordan, T. H.

2013-12-01

As part of its program of earthquake system science research, the Southern California Earthquake Center (SCEC) has developed a simulation platform, CyberShake, to perform physics-based probabilistic seismic hazard analysis (PSHA) using 3D deterministic wave propagation simulations. CyberShake performs PSHA by simulating a tensor-valued wavefield of Strain Green Tensors, and then using seismic reciprocity to calculate synthetic seismograms for about 415,000 events per site of interest. These seismograms are processed to compute ground motion intensity measures, which are then combined with probabilities from an earthquake rupture forecast to produce a site-specific hazard curve. Seismic hazard curves for hundreds of sites in a region can be used to calculate a seismic hazard map, representing the seismic hazard for a region. We present a recently completed PHSA study in which we calculated four CyberShake seismic hazard maps for the Southern California area to compare how CyberShake hazard results are affected by different SGT computational codes (AWP-ODC and AWP-RWG) and different community velocity models (Community Velocity Model - SCEC (CVM-S4) v11.11 and Community Velocity Model - Harvard (CVM-H) v11.9). We present our approach to running workflow applications on distributed HPC resources, including systems without support for remote job submission. We show how our approach extends the benefits of scientific workflows, such as job and data management, to large-scale applications on Track 1 and Leadership class open-science HPC resources. We used our distributed workflow approach to perform CyberShake Study 13.4 on two new NSF open-science HPC computing resources, Blue Waters and Stampede, executing over 470 million tasks to calculate physics-based hazard curves for 286 locations in the Southern California region. For each location, we calculated seismic hazard curves with two different community velocity models and two different SGT codes, resulting in over 1100 hazard curves. We will report on the performance of this CyberShake study, four times larger than previous studies. Additionally, we will examine the challenges we face applying these workflow techniques to additional open-science HPC systems and discuss whether our workflow solutions continue to provide value to our large-scale PSHA calculations.

IN13B-1660: Analytics and Visualization Pipelines for Big Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Technical Reports Server (NTRS)

Chaudhary, Aashish; Votava, Petr; Nemani, Ramakrishna R.; Michaelis, Andrew; Kotfila, Chris

2016-01-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

Analytics and Visualization Pipelines for Big ­Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Votava, P.; Nemani, R. R.; Michaelis, A.; Kotfila, C.

2016-12-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

The Three-Pronged Approach to Community Education: An Ongoing Hydrologic Science Outreach Campaign Directed from a University Research Center

NASA Astrophysics Data System (ADS)

Gallagher, L.; Morse, M.; Maxwell, R. M.

2017-12-01

The Integrated GroundWater Modeling Center (IGWMC) at Colorado School of Mines has, over the past three years, developed a community outreach program focusing on hydrologic science education, targeting K-12 teachers and students, and providing experiential learning for undergraduate and graduate students. During this time, the programs led by the IGWMC reached approximately 7500 students, teachers, and community members along the Colorado Front Range. An educational campaign of this magnitude for a small (2 full-time employees, 4 PIs) research center required restructuring and modularizing of the outreach strategy. We refined our approach to include three main "modules" of delivery. First: grassroots education delivery in the form of K-12 classroom visits, science fairs, and teacher workshops. Second: content development in the form of lesson plans for K-12 classrooms and STEM camps, hands-on physical and computer model activities, and long-term citizen science partnerships. Lastly: providing education/outreach experiences for undergraduate and graduate student volunteers, training them via a 3-credit honors course, and instilling the importance of effective science communication skills. Here we present specific case studies and examples of the successes and failures of our three-pronged system, future developments, and suggestions for entities newly embarking on an earth science education outreach campaign.

A Transcript Analysis of Graduates of Three Community College of Philadelphia Curricula between the Years 1985 and 1992. Institutional Research Report #83.

ERIC Educational Resources Information Center

Terzian, Aram L.; Obetz, Wayne S.

A study was conducted at the Community College of Philadelphia (CCP) to examine the course-taking patterns of 94 graduates of the associate in arts (AA) curriculum, 1,957 graduates of the association in general studies (AGS) curriculum, and 99 graduates of the associate in science (AS) curriculum. Using a computer-based approach to transcript…

Research Experiences for 14 Year Olds: preliminary report on the `Sky Explorer' pilot program at Springfield (MA) High School of Science and Technology

NASA Astrophysics Data System (ADS)

Tucker, G. E.

1997-05-01

This NSF supported program, emphasizing hands-on learning and observation with modern instruments, is described in its pilot phase, prior to being launched nationally. A group of 14 year old students are using a small (21 cm) computer controlled telescope and CCD camera to do: (1) a 'sky survey' of brighter celestial objects, finding, identifying, and learning about them, and accumulating a portfolio of images, (2) photometry of variable stars, reducing the data to get a light curve, and (3) learn modern computer-based communication/dissemination skills by posting images and data to a Web site they are designing (http://www.javanet.com/ sky) and contributing data to archives (e.g. AAVSO) via the Internet. To attract more interest to astronomy and science in general and have a wider impact on the school and surrounding community, peer teaching is used as a pedagogical technique and families are encouraged to participate. Students teach e.g. astronomy, software and computers, Internet, instrumentation, and observing to other students, parents and the community by means of daytime presentations of their results (images and data) and evening public viewing at the telescope, operating the equipment themselves. Students can contribute scientifically significant data and experience the `discovery' aspect of science through observing projects where a measurement is made. Their `informal education' activities also help improve the perception of science in general and astronomy in particular in society at large. This program could benefit from collaboration with astronomers wanting to organize geographically distributed observing campaigns coordinated over the Internet and willing to advise on promising observational programs for small telescopes in the context of current science.

Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerber, Richard; Hack, James; Riley, Katherine

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, andmore » deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.« less

International Symposium on Grids and Clouds (ISGC) 2016

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2016 will be held at Academia Sinica in Taipei, Taiwan from 13-18 March 2016, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). The theme of ISGC 2016 focuses on“Ubiquitous e-infrastructures and Applications”. Contemporary research is impossible without a strong IT component - researchers rely on the existence of stable and widely available e-infrastructures and their higher level functions and properties. As a result of these expectations, e-Infrastructures are becoming ubiquitous, providing an environment that supports large scale collaborations that deal with global challenges as well as smaller and temporal research communities focusing on particular scientific problems. To support those diversified communities and their needs, the e-Infrastructures themselves are becoming more layered and multifaceted, supporting larger groups of applications. Following the call for the last year conference, ISGC 2016 continues its aim to bring together users and application developers with those responsible for the development and operation of multi-purpose ubiquitous e-Infrastructures. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities, Arts, and Social Sciences (HASS) Applications, Virtual Research Environment (including Middleware, tools, services, workflow, etc.), Data Management, Big Data, Networking & Security, Infrastructure & Operations, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC), etc.

Developing Models for Predictive Climate Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drake, John B; Jones, Philip W

2007-01-01

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.« less

Commnity Petascale Project for Accelerator Science And Simulation: Advancing Computational Science for Future Accelerators And Accelerator Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spentzouris, Panagiotis; /Fermilab; Cary, John

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors.« less

Moving Virtual Research Environments from high maintenance Stovepipes to Multi-purpose Sustainable Service-oriented Science Platforms

NASA Astrophysics Data System (ADS)

Klump, Jens; Fraser, Ryan; Wyborn, Lesley; Friedrich, Carsten; Squire, Geoffrey; Barker, Michelle; Moloney, Glenn

2017-04-01

The researcher of today is likely to be part of a team distributed over multiple sites that will access data from an external repository and then process the data on a public or private cloud or even on a large centralised supercomputer. They are increasingly likely to use a mixture of their own code, third party software and libraries, or even access global community codes. These components will be connected into a Virtual Research Environments (VREs) that will enable members of the research team who are not co-located to actively work together at various scales to share data, models, tools, software, workflows, best practices, infrastructures, etc. Many VRE's are built in isolation: designed to meet a specific research program with components tightly coupled and not capable of being repurposed for other use cases - they are becoming 'stovepipes'. The limited number of users of some VREs also means that the cost of maintenance per researcher can be unacceptably high. The alternative is to develop service-oriented Science Platforms that enable multiple communities to develop specialised solutions for specific research programs. The platforms can offer access to data, software tools and processing infrastructures (cloud, supercomputers) through globally distributed, interconnected modules. In Australia, the Virtual Geophysics Laboratory (VGL) was initially built to enable a specific set of researchers in government agencies access to specific data sets and a limited number of tools, that is now rapidly evolving into a multi-purpose Earth science platform with access to an increased variety of data, a broader range of tools, users from more sectors and a diversity of computational infrastructures. The expansion has been relatively easy, because of the architecture whereby data, tools and compute resources are loosely coupled via interfaces that are built on international standards and accessed as services wherever possible. In recent years, investments in discoverability and accessibility of data via online services in Australia mean that data resources can be easily added to the virtual environments as and when required. Another key to increasing to reusability and uptake of the VRE is the capability to capturing workflows so that they can be reused and repurposed both within and beyond the community that that defined the original use case. Unfortunately, Software-as-a-Service in the research sector is not yet mature. In response, we developed a Scientific Software solutions Center (SSSC) that enables researchers to discover, deploy and then share computational codes, code snippets or processes both in a human and machine-readable manner. Growth has come not only from within the Earth science community but from the Australian Virtual Laboratory community which is building VREs for a diversity of communities such as astronomy, genomics, environment, humanities, climate etc. Components such as access control, provenance, visualisation, accounting etc. are common to all scientific domains and sharing of these across multiple domains reduces costs, but more importantly increases the ability to undertake interdisciplinary science. These efforts are transitioning VREs to more sustainable Service-oriented Science Platforms that can be delivered in an agile, adaptable manner for broader community interests.

The information science of microbial ecology.

PubMed

Hahn, Aria S; Konwar, Kishori M; Louca, Stilianos; Hanson, Niels W; Hallam, Steven J

2016-06-01

A revolution is unfolding in microbial ecology where petabytes of 'multi-omics' data are produced using next generation sequencing and mass spectrometry platforms. This cornucopia of biological information has enormous potential to reveal the hidden metabolic powers of microbial communities in natural and engineered ecosystems. However, to realize this potential, the development of new technologies and interpretative frameworks grounded in ecological design principles are needed to overcome computational and analytical bottlenecks. Here we explore the relationship between microbial ecology and information science in the era of cloud-based computation. We consider microorganisms as individual information processing units implementing a distributed metabolic algorithm and describe developments in ecoinformatics and ubiquitous computing with the potential to eliminate bottlenecks and empower knowledge creation and translation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

2005 White Paper on Institutional Capability Computing Requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carnes, B; McCoy, M; Seager, M

This paper documents the need for a significant increase in the computing infrastructure provided to scientists working in the unclassified domains at Lawrence Livermore National Laboratory (LLNL). This need could be viewed as the next step in a broad strategy outlined in the January 2002 White Paper (UCRL-ID-147449) that bears essentially the same name as this document. Therein we wrote: 'This proposed increase could be viewed as a step in a broader strategy linking hardware evolution to applications development that would take LLNL unclassified computational science to a position of distinction if not preeminence by 2006.' This position of distinctionmore » has certainly been achieved. This paper provides a strategy for sustaining this success but will diverge from its 2002 predecessor in that it will: (1) Amplify the scientific and external success LLNL has enjoyed because of the investments made in 2002 (MCR, 11 TF) and 2004 (Thunder, 23 TF). (2) Describe in detail the nature of additional investments that are important to meet both the institutional objectives of advanced capability for breakthrough science and the scientists clearly stated request for adequate capacity and more rapid access to moderate-sized resources. (3) Put these requirements in the context of an overall strategy for simulation science and external collaboration. While our strategy for Multiprogrammatic and Institutional Computing (M&IC) has worked well, three challenges must be addressed to assure and enhance our position. The first is that while we now have over 50 important classified and unclassified simulation codes available for use by our computational scientists, we find ourselves coping with high demand for access and long queue wait times. This point was driven home in the 2005 Institutional Computing Executive Group (ICEG) 'Report Card' to the Deputy Director for Science and Technology (DDST) Office and Computation Directorate management. The second challenge is related to the balance that should be maintained in the simulation environment. With the advent of Thunder, the institution directed a change in course from past practice. Instead of making Thunder available to the large body of scientists, as was MCR, and effectively using it as a capacity system, the intent was to make it available to perhaps ten projects so that these teams could run very aggressive problems for breakthrough science. This usage model established Thunder as a capability system. The challenge this strategy raises is that the majority of scientists have not seen an improvement in capacity computing resources since MCR, thus creating significant tension in the system. The question then is: 'How do we address the institution's desire to maintain the potential for breakthrough science and also meet the legitimate requests from the ICEG to achieve balance?' Both the capability and the capacity environments must be addressed through this one procurement. The third challenge is to reach out more aggressively to the national science community to encourage access to LLNL resources as part of a strategy for sharpening our science through collaboration. Related to this, LLNL has been unable in the past to provide access for sensitive foreign nationals (SFNs) to the Livermore Computing (LC) unclassified 'yellow' network. Identifying some mechanism for data sharing between LLNL computational scientists and SFNs would be a first practical step in fostering cooperative, collaborative relationships with an important and growing sector of the American science community.« less

Approximate Computing Techniques for Iterative Graph Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh

Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with lowmore » impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.« less

An introduction to computer forensics.

PubMed

Furneaux, Nick

2006-07-01

This paper provides an introduction to the discipline of Computer Forensics. With computers being involved in an increasing number, and type, of crimes the trace data left on electronic media can play a vital part in the legal process. To ensure acceptance by the courts, accepted processes and procedures have to be adopted and demonstrated which are not dissimilar to the issues surrounding traditional forensic investigations. This paper provides a straightforward overview of the three steps involved in the examination of digital media: Acquisition of data. Investigation of evidence. Reporting and presentation of evidence. Although many of the traditional readers of Medicine, Science and the Law are those involved in the biological aspects of forensics, I believe that both disciplines can learn from each other, with electronic evidence being more readily sought and considered by the legal community and the long, tried and tested scientific methods of the forensic community being shared and adopted by the computer forensic world.

Integrating Laptop Computers into Classroom: Attitudes, Needs, and Professional Development of Science Teachers—A Case Study

NASA Astrophysics Data System (ADS)

Klieger, Aviva; Ben-Hur, Yehuda; Bar-Yossef, Nurit

2010-04-01

The study examines the professional development of junior-high-school teachers participating in the Israeli "Katom" (Computer for Every Class, Student and Teacher) Program, begun in 2004. A three-circle support and training model was developed for teachers' professional development. The first circle applies to all teachers in the program; the second, to all teachers at individual schools; the third to teachers of specific disciplines. The study reveals and describes the attitudes of science teachers to the integration of laptop computers and to the accompanying professional development model. Semi-structured interviews were conducted with eight science teachers from the four schools participating in the program. The interviews were analyzed according to the internal relational framework taken from the information that arose from the interviews. Two factors influenced science teachers' professional development: (1) Introduction of laptops to the teachers and students. (2) The support and training system. Interview analysis shows that the disciplinary training is most relevant to teachers and they are very interested in belonging to the professional science teachers' community. They also prefer face-to-face meetings in their school. Among the difficulties they noted were the new learning environment, including control of student computers, computer integration in laboratory work and technical problems. Laptop computers contributed significantly to teachers' professional and personal development and to a shift from teacher-centered to student-centered teaching. One-to-One laptops also changed the schools' digital culture. The findings are important for designing concepts and models for professional development when introducing technological innovation into the educational system.

Mastering cognitive development theory in computer science education

NASA Astrophysics Data System (ADS)

Gluga, Richard; Kay, Judy; Lister, Raymond; Simon; Kleitman, Sabina

2013-03-01

To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that classified activities and assessments are comparable across the subjects of a degree, and, ideally, comparable across institutions. One widespread approach to supporting this is to write learning objects in terms of Bloom's Taxonomy. This, or other such classifications, is likely to be more effective if educators can use them consistently, in the way experts would use them. To this end, we present the design and evaluation of our online interactive web-based tutorial system, which can be configured and used to offer training in different classification schemes. We report on results from three evaluations. First, 17 computer science educators complete a tutorial on using Bloom's Taxonomy to classify programming examination questions. Second, 20 computer science educators complete a Neo-Piagetian tutorial. Third evaluation was a comparison of inter-rater reliability scores of computer science educators classifying programming questions using Bloom's Taxonomy, before and after taking our tutorial. Based on the results from these evaluations, we discuss the effectiveness of our tutorial system design for teaching computer science educators how to systematically and consistently classify programming examination questions. We also discuss the suitability of Bloom's Taxonomy and Neo-Piagetian theory for achieving this goal. The Bloom's and Neo-Piagetian tutorials are made available as a community resource. The contributions of this paper are the following: the tutorial system for learning classification schemes for the purpose of coding the difficulty of computing learning materials; its evaluation; new insights into the consistency that computing educators can achieve using Bloom; and first insights into the use of Neo-Piagetian theory by a group of classifiers.

Computer network access to scientific information systems for minority universities

NASA Astrophysics Data System (ADS)

Thomas, Valerie L.; Wakim, Nagi T.

1993-08-01

The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.

Towards Test Driven Development for Computational Science with pFUnit

NASA Technical Reports Server (NTRS)

Rilee, Michael L.; Clune, Thomas L.

2014-01-01

Developers working in Computational Science & Engineering (CSE)/High Performance Computing (HPC) must contend with constant change due to advances in computing technology and science. Test Driven Development (TDD) is a methodology that mitigates software development risks due to change at the cost of adding comprehensive and continuous testing to the development process. Testing frameworks tailored for CSE/HPC, like pFUnit, can lower the barriers to such testing, yet CSE software faces unique constraints foreign to the broader software engineering community. Effective testing of numerical software requires a comprehensive suite of oracles, i.e., use cases with known answers, as well as robust estimates for the unavoidable numerical errors associated with implementation with finite-precision arithmetic. At first glance these concerns often seem exceedingly challenging or even insurmountable for real-world scientific applications. However, we argue that this common perception is incorrect and driven by (1) a conflation between model validation and software verification and (2) the general tendency in the scientific community to develop relatively coarse-grained, large procedures that compound numerous algorithmic steps.We believe TDD can be applied routinely to numerical software if developers pursue fine-grained implementations that permit testing, neatly side-stepping concerns about needing nontrivial oracles as well as the accumulation of errors. We present an example of a successful, complex legacy CSE/HPC code whose development process shares some aspects with TDD, which we contrast with current and potential capabilities. A mix of our proposed methodology and framework support should enable everyday use of TDD by CSE-expert developers.

Understanding Scientific Ideas: An Honors Course.

ERIC Educational Resources Information Center

Capps, Joan; Schueler, Paul

At Raritan Valley Community College (RVCC) in New Jersey, an honors philosophy course was developed which taught mathematics and science concepts independent of computational skill. The course required that students complete a weekly writing assignment designed as a continuous refinement of logical reasoning development. This refinement was…

[Activities of Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2001-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

The JASMIN Cloud: specialised and hybrid to meet the needs of the Environmental Sciences Community

NASA Astrophysics Data System (ADS)

Kershaw, Philip; Lawrence, Bryan; Churchill, Jonathan; Pritchard, Matt

2014-05-01

Cloud computing provides enormous opportunities for the research community. The large public cloud providers provide near-limitless scaling capability. However, adapting Cloud to scientific workloads is not without its problems. The commodity nature of the public cloud infrastructure can be at odds with the specialist requirements of the research community. Issues such as trust, ownership of data, WAN bandwidth and costing models make additional barriers to more widespread adoption. Alongside the application of public cloud for scientific applications, a number of private cloud initiatives are underway in the research community of which the JASMIN Cloud is one example. Here, cloud service models are being effectively super-imposed over more established services such as data centres, compute cluster facilities and Grids. These have the potential to deliver the specialist infrastructure needed for the science community coupled with the benefits of a Cloud service model. The JASMIN facility based at the Rutherford Appleton Laboratory was established in 2012 to support the data analysis requirements of the climate and Earth Observation community. In its first year of operation, the 5PB of available storage capacity was filled and the hosted compute capability used extensively. JASMIN has modelled the concept of a centralised large-volume data analysis facility. Key characteristics have enabled success: peta-scale fast disk connected via low latency networks to compute resources and the use of virtualisation for effective management of the resources for a range of users. A second phase is now underway funded through NERC's (Natural Environment Research Council) Big Data initiative. This will see significant expansion to the resources available with a doubling of disk-based storage to 12PB and an increase of compute capacity by a factor of ten to over 3000 processing cores. This expansion is accompanied by a broadening in the scope for JASMIN, as a service available to the entire UK environmental science community. Experience with the first phase demonstrated the range of user needs. A trade-off is needed between access privileges to resources, flexibility of use and security. This has influenced the form and types of service under development for the new phase. JASMIN will deploy a specialised private cloud organised into "Managed" and "Unmanaged" components. In the Managed Cloud, users have direct access to the storage and compute resources for optimal performance but for reasons of security, via a more restrictive PaaS (Platform-as-a-Service) interface. The Unmanaged Cloud is deployed in an isolated part of the network but co-located with the rest of the infrastructure. This enables greater liberty to tenants - full IaaS (Infrastructure-as-a-Service) capability to provision customised infrastructure - whilst at the same time protecting more sensitive parts of the system from direct access using these elevated privileges. The private cloud will be augmented with cloud-bursting capability so that it can exploit the resources available from public clouds, making it effectively a hybrid solution. A single interface will overlay the functionality of both the private cloud and external interfaces to public cloud providers giving users the flexibility to migrate resources between infrastructures as requirements dictate.

The Challenges and Benefits of Using Computer Technology for Communication and Teaching in the Geosciences

NASA Astrophysics Data System (ADS)

Fairley, J. P.; Hinds, J. J.

2003-12-01

The advent of the World Wide Web in the early 1990s not only revolutionized the exchange of ideas and information within the scientific community, but also provided educators with a new array of teaching, informational, and promotional tools. Use of computer graphics and animation to explain concepts and processes can stimulate classroom participation and student interest in the geosciences, which has historically attracted students with strong spatial and visualization skills. In today's job market, graduates are expected to have knowledge of computers and the ability to use them for acquiring, processing, and visually analyzing data. Furthermore, in addition to promoting visibility and communication within the scientific community, computer graphics and the Internet can be informative and educational for the general public. Although computer skills are crucial for earth science students and educators, many pitfalls exist in implementing computer technology and web-based resources into research and classroom activities. Learning to use these new tools effectively requires a significant time commitment and careful attention to the source and reliability of the data presented. Furthermore, educators have a responsibility to ensure that students and the public understand the assumptions and limitations of the materials presented, rather than allowing them to be overwhelmed by "gee-whiz" aspects of the technology. We present three examples of computer technology in the earth sciences classroom: 1) a computer animation of water table response to well pumping, 2) a 3-D fly-through animation of a fault controlled valley, and 3) a virtual field trip for an introductory geology class. These examples demonstrate some of the challenges and benefits of these new tools, and encourage educators to expand the responsible use of computer technology for teaching and communicating scientific results to the general public.

ISCR FY2005 Annual Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keyes, D E; McGraw, J R

2006-02-02

Large-scale scientific computation and all of the disciplines that support and help validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of simulation as a fundamental tool of scientific and engineering research is underscored in the President's Information Technology Advisory Committee (PITAC) June 2005 finding that ''computational science has become critical to scientific leadership, economic competitiveness, and nationalmore » security''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed, most notably the molecular dynamics simulation that sustained more than 100 Teraflop/s and won the 2005 Gordon Bell Prize. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use in an efficient manner. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to the core missions of LLNL than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In FY 2005, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for both brief and extended visits with the aim of encouraging long-term academic research agendas that address LLNL research priorities. Through these collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''hands and feet'' that carry those advances into the Laboratory and incorporate them into practice. ISCR research participants are integrated into LLNL's Computing Applications and Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other four institutes of the URP, the ISCR navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort. The pages of this annual report summarize the activities of the faculty members, postdoctoral researchers, students, and guests from industry and other laboratories who participated in LLNL's computational mission under the auspices of the ISCR during FY 2005.« less

Working Towards New Transformative Geoscience Analytics Enabled by Petascale Computing

NASA Astrophysics Data System (ADS)

Woodcock, R.; Wyborn, L.

2012-04-01

Currently the top 10 supercomputers in the world are petascale and already exascale computers are being planned. Cloud computing facilities are becoming mainstream either as private or commercial investments. These computational developments will provide abundant opportunities for the earth science community to tackle the data deluge which has resulted from new instrumentation enabling data to be gathered at a greater rate and at higher resolution. Combined, the new computational environments should enable the earth sciences to be transformed. However, experience in Australia and elsewhere has shown that it is not easy to scale existing earth science methods, software and analytics to take advantage of the increased computational capacity that is now available. It is not simply a matter of 'transferring' current work practices to the new facilities: they have to be extensively 'transformed'. In particular new Geoscientific methods will need to be developed using advanced data mining, assimilation, machine learning and integration algorithms. Software will have to be capable of operating in highly parallelised environments, and will also need to be able to scale as the compute systems grow. Data access will have to improve and the earth science community needs to move from the file discovery, display and then locally download paradigm to self describing data cubes and data arrays that are available as online resources from either major data repositories or in the cloud. In the new transformed world, rather than analysing satellite data scene by scene, sensor agnostic data cubes of calibrated earth observation data will enable researchers to move across data from multiple sensors at varying spatial data resolutions. In using geophysics to characterise basement and cover, rather than analysing individual gridded airborne geophysical data sets, and then combining the results, petascale computing will enable analysis of multiple data types, collected at varying resolutions with integration and validation across data type boundaries. Increased capacity of storage and compute will mean that uncertainty and reliability of individual observations will consistently be taken into account and propagated throughout the processing chain. If these data access difficulties can be overcome, the increased compute capacity will also mean that larger scale, more complex models can be run at higher resolution and instead of single pass modelling runs. Ensembles of models will be able to be run to simultaneously test multiple hypotheses. Petascale computing and high performance data offer more than "bigger, faster": it is an opportunity for a transformative change in the way in which geoscience research is routinely conducted.

Science Outreach for the Thousands: Coe College's Playground of Science

NASA Astrophysics Data System (ADS)

Watson, D. E.; Franke, M.; Affatigato, M.; Feller, S.

2011-12-01

Coe College is a private liberal arts college nestled in the northeast quadrant of Cedar Rapids, IA. Coe takes pride in the outreach it does in the local community. The sciences at Coe find enjoyment in educating the children and families of this community through a diverse set of venues; from performing science demonstrations for children at Cedar Rapids' Fourth of July Freedom Festival to hosting summer forums and talks to invigorate the minds of its more mature audiences. Among these events, the signature event of the year is the Coe Playground of Science. On the last Thursday of October, before Halloween, the science departments at Coe invite nearly two thousand children from pre elementary to high school ages, along with their parents to participate in a night filled with science demos, haunted halls, and trick-or-treating for more than just candy. The demonstrations are performed by professors and students alike from a raft of cooperative departments including physics, chemistry, biology, math, computer science, nursing, ROTC, and psychology. This event greatly strengthens the relationships between institution members and community members. The sciences at Coe understand the importance of imparting the thrill and hunger for exploration and discovery into the future generations. More importantly they recognize that this cannot start and end at the collegiate level, but the American public must be reached at younger ages and continue to be encouraged beyond the college experience. The Playground of Science unites these two groups under the common goal of elevating scientific interest in the American people.

Downscaling seasonal to centennial simulations on distributed computing infrastructures using WRF model. The WRF4G project

NASA Astrophysics Data System (ADS)

Cofino, A. S.; Fernández Quiruelas, V.; Blanco Real, J. C.; García Díez, M.; Fernández, J.

2013-12-01

Nowadays Grid Computing is powerful computational tool which is ready to be used for scientific community in different areas (such as biomedicine, astrophysics, climate, etc.). However, the use of this distributed computing infrastructures (DCI) is not yet common practice in climate research, and only a few teams and applications in this area take advantage of this infrastructure. Thus, the WRF4G project objective is to popularize the use of this technology in the atmospheric sciences area. In order to achieve this objective, one of the most used applications has been taken (WRF; a limited- area model, successor of the MM5 model), that has a user community formed by more than 8000 researchers worldwide. This community develop its research activity on different areas and could benefit from the advantages of Grid resources (case study simulations, regional hind-cast/forecast, sensitivity studies, etc.). The WRF model is used by many groups, in the climate research community, to carry on downscaling simulations. Therefore this community will also benefit. However, Grid infrastructures have some drawbacks for the execution of applications that make an intensive use of CPU and memory for a long period of time. This makes necessary to develop a specific framework (middleware). This middleware encapsulates the application and provides appropriate services for the monitoring and management of the simulations and the data. Thus,another objective of theWRF4G project consists on the development of a generic adaptation of WRF to DCIs. It should simplify the access to the DCIs for the researchers, and also to free them from the technical and computational aspects of the use of theses DCI. Finally, in order to demonstrate the ability of WRF4G solving actual scientific challenges with interest and relevance on the climate science (implying a high computational cost) we will shown results from different kind of downscaling experiments, like ERA-Interim re-analysis, CMIP5 models, or seasonal. WRF4G is been used to run WRF simulations which are contributing to the CORDEX initiative and others projects like SPECS and EUPORIAS. This work is been partially funded by the European Regional Development Fund (ERDF) and the Spanish National R&D Plan 2008-2011 (CGL2011-28864)

Sundials in the shade: A study of women's persistence in the first year of a computer science program in a selective university

NASA Astrophysics Data System (ADS)

Powell, Rita Manco

Currently women are underrepresented in departments of computer science, making up approximately 18% of the undergraduate enrollment in selective universities. Most attrition in computer science occurs early in this major, in the freshman and sophomore years, and women drop out in disproportionately greater numbers than their male counterparts. Taking an ethnographic approach to investigating women's experiences and progress in the first year courses in the computer science major at the University of Pennsylvania, this study examined the pre-college influences that led these women to the major and the nature of their experiences in and outside of class with faculty, peers, and academic support services. This study sought an understanding of the challenges these women faced in the first year of the major with the goal of informing institutional practice about how to best support their persistence. The research reviewed for this study included patterns of leaving majors in science, math and engineering (Seymour & Hewitt 1997), the high school preparation needed to pursue math and engineering majors in college (Strenta, Elliott, Adair, Matier, & Scott, 1994), and intervention programs that have positively impacted persistence of women in computer science (Margolis & Fisher, 2002). The research method of this study employed a series of personal interviews over the course of one calendar year with fourteen first year women who had either declared on intended to declare the computer science major in the School of Engineering and Applied Science at the University of Pennsylvania. Other data sources were focus groups and personal interviews with faculty, administrators, admissions and student life professionals, teaching assistants, female graduate students, and male first year students at the University of Pennsylvania. This study found that the women in this study group came to the University of Pennsylvania with a thorough grounding in mathematics, but many either had an inadequate background in computer science, or at least perceived inadequacies in their background, which prevented them from beginning the major on an equal footing with their mostly male peers and caused some to lose confidence and consequently interest in the major. Issues also emanated from their gender-minority status in the Computer and Information Science Department, causing them to be socially isolated from their peers and further weakening their resolve to persist. These findings suggest that female first year students could benefit from multiple pathways into the major designed for students with varying degrees of prior experience with computer science. In addition, a computer science community within the department characterized by more frequent interaction and collaboration with faculty and peers could positively impact women's persistence in the major.

Promoting Interests in Atmospheric Science at a Liberal Arts Institution

NASA Astrophysics Data System (ADS)

Roussev, S.; Sherengos, P. M.; Limpasuvan, V.; Xue, M.

2007-12-01

Coastal Carolina University (CCU) students in Computer Science participated in a project to set up an operational weather forecast for the local community. The project involved the construction of two computing clusters and the automation of daily forecasting. Funded by NSF-MRI, two high-performance clusters were successfully established to run the University of Oklahoma's Advance Regional Prediction System (ARPS). Daily weather predictions are made over South Carolina and North Carolina at 3-km horizontal resolution (roughly 1.9 miles) using initial and boundary condition data provided by UNIDATA. At this high resolution, the model is cloud- resolving, thus providing detailed picture of heavy thunderstorms and precipitation. Forecast results are displayed on CCU's website (https://marc.coastal.edu/HPC) to complement observations at the National Weather Service in Wilmington N.C. Present efforts include providing forecasts at 1-km resolution (or finer), comparisons with other models like Weather Research and Forecasting (WRF) model, and the examination of local phenomena (like water spouts and tornadoes). Through these activities the students learn about shell scripting, cluster operating systems, and web design. More importantly, students are introduced to Atmospheric Science, the processes involved in making weather forecasts, and the interpretation of their forecasts. Simulations generated by the forecasts will be integrated into the contents of CCU's course like Fluid Dynamics, Atmospheric Sciences, Atmospheric Physics, and Remote Sensing. Operated jointly between the departments of Applied Physics and Computer Science, the clusters are expected to be used by CCU faculty and students for future research and inquiry-based projects in Computer Science, Applied Physics, and Marine Science.

Lattice QCD Application Development within the US DOE Exascale Computing Project

NASA Astrophysics Data System (ADS)

Brower, Richard; Christ, Norman; DeTar, Carleton; Edwards, Robert; Mackenzie, Paul

2018-03-01

In October, 2016, the US Department of Energy launched the Exascale Computing Project, which aims to deploy exascale computing resources for science and engineering in the early 2020's. The project brings together application teams, software developers, and hardware vendors in order to realize this goal. Lattice QCD is one of the applications. Members of the US lattice gauge theory community with significant collaborators abroad are developing algorithms and software for exascale lattice QCD calculations. We give a short description of the project, our activities, and our plans.

A Queue Simulation Tool for a High Performance Scientific Computing Center

NASA Technical Reports Server (NTRS)

Spear, Carrie; McGalliard, James

2007-01-01

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

Lattice QCD Application Development within the US DOE Exascale Computing Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brower, Richard; Christ, Norman; DeTar, Carleton

In October, 2016, the US Department of Energy launched the Exascale Computing Project, which aims to deploy exascale computing resources for science and engineering in the early 2020's. The project brings together application teams, software developers, and hardware vendors in order to realize this goal. Lattice QCD is one of the applications. Members of the US lattice gauge theory community with significant collaborators abroad are developing algorithms and software for exascale lattice QCD calculations. We give a short description of the project, our activities, and our plans.

GET21: Geoinformatics Training and Education for the 21st Century Geoscience Workforce

NASA Astrophysics Data System (ADS)

Baru, C.; Allison, L.; Fox, P.; Keane, C.; Keller, R.; Richard, S.

2012-04-01

The integration of advanced information technologies (referred to as cyberinfrastructure) into scientific research and education creates a synergistic situation. On the one hand, science begins to move at the speed of information technology, with science applications having to move rapidly to keep apace with the latest innovations in hardware and software. On the other hand, information technology moves at the pace of science, requiring rapid prototyping and rapid development of software and systems to serve the immediate needs of the application. The 21st century geoscience workforce must be adept at both sides of this equation to be able to make the best use of the available cyber-tools for their science and education endeavors. To reach different segments of the broad geosciences community, an education program in geoinformatics must be multi-faceted, ranging from areas dealing with modeling, computational science, and high performance computing, to those dealing with data collection, data science, and data-intensive computing. Based on our experience in geoinformatics and data science education, we propose a multi-pronged approach with a number of different components, including summer institutes typically aimed at graduate students, postdocs and researchers; graduate and undergraduate curriculum development in geoinformatics; development of online course materials to facilitate asynchronous learning, especially for geoscience professionals in the field; provision of internship at geoinformatics-related facilities for graduate students, so that they can observe and participate in geoinformatics "in action"; creation of online communities and networks to facilitate planned as well as serendipitous collaborations and for linking users with experts in the different areas of geoscience and geoinformatics. We will describe some of our experiences and the lessons learned over the years from the Cyberinfrastructure Summer Institute for Geoscientists (CSIG), which is a 1-week institute that has been held each summer (August) at the San Diego Supercomputer Center, University of California, San Diego, since 2005. We will also discuss these opportunities for GET21 and geoinformatics education in the context of the newly launched EarthCube initiative at the US National Science Foundation.

Information dynamics algorithm for detecting communities in networks

NASA Astrophysics Data System (ADS)

Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

2012-11-01

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

Management Information Systems, Planning, and Public Community Colleges.

ERIC Educational Resources Information Center

Ritch, Stephen W.; Munro, Robert J.

Management Information Systems (MIS), originally developed in the areas of accounting, management science, and computer processing, are now being applied to decision-making in educational settings. Definitions of MIS are numerous and often vague, but management systems (as distinguished from other information systems) should promote real-time…

Interactive Technologies and the Social Studies. Emerging Issues and Applications.

ERIC Educational Resources Information Center

Martorella, Peter H., Ed.

This book includes contributions from seven authors with diverse backgrounds, whose specializations include the area of social studies education, software development, computer science, and visual design. The chapters are: (1) "Online Learning Communities: Implications for the Social Studies" (Lynn A. Fontana); (2) "Bringing Preservice Teachers…

US GeoData: Digital cartographic and geographic data

USGS Publications Warehouse

,

1985-01-01

The increasing use of computers for storing and analyzing earth science information has sparked a growth in the demand for various types of cartographic data in digital form. The production of map data in computerized form is called digital cartography, and it involves the collection, storage, processing, analysis, and display of map data with the aid of computers. The U.S. Geological Survey, the Nation's largest earth science research agency, has expanded its national mapping program to incorporate operations associated with digital cartography, including the collection of planimetric, elevation, and geographic names information in digital form. This digital information is available for use in meeting the multipurpose needs and applications of the map user community.

Visualization Techniques in Space and Atmospheric Sciences

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P. (Editor); Bredekamp, Joseph H. (Editor)

1995-01-01

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

Grid Technology as a Cyberinfrastructure for Delivering High-End Services to the Earth and Space Science Community

NASA Technical Reports Server (NTRS)

Hinke, Thomas H.

2004-01-01

Grid technology consists of middleware that permits distributed computations, data and sensors to be seamlessly integrated into a secure, single-sign-on processing environment. In &is environment, a user has to identify and authenticate himself once to the grid middleware, and then can utilize any of the distributed resources to which he has been,panted access. Grid technology allows resources that exist in enterprises that are under different administrative control to be securely integrated into a single processing environment The grid community has adopted commercial web services technology as a means for implementing persistent, re-usable grid services that sit on top of the basic distributed processing environment that grids provide. These grid services can then form building blocks for even more complex grid services. Each grid service is characterized using the Web Service Description Language, which provides a description of the interface and how other applications can access it. The emerging Semantic grid work seeks to associates sufficient semantic information with each grid service such that applications wii1 he able to automatically select, compose and if necessary substitute available equivalent services in order to assemble collections of services that are most appropriate for a particular application. Grid technology has been used to provide limited support to various Earth and space science applications. Looking to the future, this emerging grid service technology can provide a cyberinfrastructures for both the Earth and space science communities. Groups within these communities could transform those applications that have community-wide applicability into persistent grid services that are made widely available to their respective communities. In concert with grid-enabled data archives, users could easily create complex workflows that extract desired data from one or more archives and process it though an appropriate set of widely distributed grid services discovered using semantic grid technology. As required, high-end computational resources could be drawn from available grid resource pools. Using grid technology, this confluence of data, services and computational resources could easily be harnessed to transform data from many different sources into a desired product that is delivered to a user's workstation or to a web portal though which it could be accessed by its intended audience.

Indiana Wesleyan University SPS Physics Outreach to Rural Middle School and High School Students

NASA Astrophysics Data System (ADS)

Ostrander, Joshua; Rose, Heath; Burchell, Robert; Ramos, Roberto

2013-03-01

The Society of Physics Students chapter at Indiana Wesleyan University is unusual in that it has no physics major, only physics minors. Yet while just over a year old, IWU-SPS has been active in performing physics outreach to middle school and high school students, and the rural community of Grant County. Our year-old SPS chapter consists of majors from Chemistry, Nursing, Biology, Exercise Science, Computer Science, Psychology, Pastoral Studies, and Science Education, who share a common interest in physics and service to the community. IWU currently has a physics minor and is currently working to build a physics major program. Despite the intrinsic challenges, our multi-disciplinary group has been successful at using physics demonstration equipment and hands-on activities and their universal appeal to raise the interest in physics in Grant County. We report our experience, challenges, and successes with physics outreach. We describe in detail our two-pronged approach: raising the level of physics appreciation among the IWU student community and among pre-college students in a rural community of Indiana. Acknowledgements: We acknowledge the support of the Society of Physics Students through a Marsh White Outreach Award and a Blake Lilly Prize.

Science, Society, and Social Networking

NASA Astrophysics Data System (ADS)

White, K. S.; Lohwater, T.

2009-12-01

The increased use of social networking is changing the way that scientific societies interact with their members and others. The American Association for the Advancement of Science (AAAS) uses a variety of online networks to engage its members and the broader scientific community. AAAS members and non-members can interact with AAAS staff and each other on AAAS sites on Facebook, YouTube, and Twitter, as well as blogs and forums on the AAAS website (www.aaas.org). These tools allow scientists to more readily become engaged in policy by providing information on current science policy topics as well as methods of involvement. For example, members and the public can comment on policy-relevant stories from Science magazine’s ScienceInsider blog, download a weekly policy podcast, receive a weekly email update of policy issues affecting the scientific community, or watch a congressional hearing from their computer. AAAS resource websites and outreach programs, including Communicating Science (www.aaas.org/communicatingscience), Working with Congress (www.aaas.org/spp/cstc/) and Science Careers (http://sciencecareers.sciencemag.org) also provide tools for scientists to become more personally engaged in communicating their findings and involved in the policy process.

Unidata: Community, Science, and Technology; in that order.

NASA Astrophysics Data System (ADS)

Young, J. W.; Ramamurthy, M. K.; Davis, E.

2015-12-01

Unidata's mission is to provide the data services, tools, and cyberinfrastructure leadership that advance Earth system science, enhance educational opportunities, and broaden participation. The Unidata community has grown from around 250 individual participants in the early years to tens of thousands of users in over 150 countries. Today, Unidata's products and services are used on every continent and by every sector of the geoscience enterprise: universities, government agencies, private sector, and other non-governmental organizations. Certain traits and ethos are shared by and common to most successful organizations. They include a healthy organizational culture grounded by some core values and guiding principles. In that environment, there is an implicit awareness of the connection between mission of an organization, its values, and its day-to-day activities, and behaviours of a passionate staff. Distinguishing characteristics include: vigorous engagement of the community served by those organizations backed by strong and active governance, unwavering commitment to seek input and feedback from users, and trust of those users, earned over many years through consistent, dependable, and high-quality service. Meanwhile, changing data volumes and standards, new computing power, and expanding scientific questions sound continue to shape the geoscience community. These issues were the drivers for founding Unidata, a cornerstone data facility, in 1984. Advances in geoscience occur at the junction of community, science, and technology and this submission will feature lessons from Unidata's thirty year history operating at this nexus. Specifically, this presentation will feature guiding principles for the program, governance mechanisms, and approaches for balancing science and technology in a community-driven program.

Collaborative workbench for cyberinfrastructure to accelerate science algorithm development

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Maskey, M.; Kuo, K.; Lynnes, C.

2013-12-01

There are significant untapped resources for information and knowledge creation within the Earth Science community in the form of data, algorithms, services, analysis workflows or scripts, and the related knowledge about these resources. Despite the huge growth in social networking and collaboration platforms, these resources often reside on an investigator's workstation or laboratory and are rarely shared. A major reason for this is that there are very few scientific collaboration platforms, and those that exist typically require the use of a new set of analysis tools and paradigms to leverage the shared infrastructure. As a result, adoption of these collaborative platforms for science research is inhibited by the high cost to an individual scientist of switching from his or her own familiar environment and set of tools to a new environment and tool set. This presentation will describe an ongoing project developing an Earth Science Collaborative Workbench (CWB). The CWB approach will eliminate this barrier by augmenting a scientist's current research environment and tool set to allow him or her to easily share diverse data and algorithms. The CWB will leverage evolving technologies such as commodity computing and social networking to design an architecture for scalable collaboration that will support the emerging vision of an Earth Science Collaboratory. The CWB is being implemented on the robust and open source Eclipse framework and will be compatible with widely used scientific analysis tools such as IDL. The myScience Catalog built into CWB will capture and track metadata and provenance about data and algorithms for the researchers in a non-intrusive manner with minimal overhead. Seamless interfaces to multiple Cloud services will support sharing algorithms, data, and analysis results, as well as access to storage and computer resources. A Community Catalog will track the use of shared science artifacts and manage collaborations among researchers.

Community Capacity Building as a vital mechanism for enhancing the growth and efficacy of a sustainable scientific software ecosystem: experiences running a real-time bi-coastal "Open Science for Synthesis" Training Institute for young Earth and Environmental scientists

NASA Astrophysics Data System (ADS)

Schildhauer, M.; Jones, M. B.; Bolker, B.; Lenhardt, W. C.; Hampton, S. E.; Idaszak, R.; Rebich Hespanha, S.; Ahalt, S.; Christopherson, L.

2014-12-01

Continuing advances in computational capabilities, access to Big Data, and virtual collaboration technologies are creating exciting new opportunities for accomplishing Earth science research at finer resolutions, with much broader scope, using powerful modeling and analytical approaches that were unachievable just a few years ago. Yet, there is a perceptible lag in the abilities of the research community to capitalize on these new possibilities, due to lacking the relevant skill-sets, especially with regards to multi-disciplinary and integrative investigations that involve active collaboration. UC Santa Barbara's National Center for Ecological Analysis and Synthesis (NCEAS), and the University of North Carolina's Renaissance Computing Institute (RENCI), were recipients of NSF OCI S2I2 "Conceptualization awards", charged with helping define the needs of the research community relative to enabling science and education through "sustained software infrastructure". Over the course of our activities, a consistent request from Earth scientists was for "better training in software that enables more effective, reproducible research." This community-based feedback led to creation of an "Open Science for Synthesis" Institute— a innovative, three-week, bi-coastal training program for early career researchers. We provided a mix of lectures, hands-on exercises, and working group experience on topics including: data discovery and preservation; code creation, management, sharing, and versioning; scientific workflow documentation and reproducibility; statistical and machine modeling techniques; virtual collaboration mechanisms; and methods for communicating scientific results. All technologies and quantitative tools presented were suitable for advancing open, collaborative, and reproducible synthesis research. In this talk, we will report on the lessons learned from running this ambitious training program, that involved coordinating classrooms among two remote sites, and included developing original synthesis research activities as part of the course. We also report on the feedback provided by participants as to the learning approaches and topical issues they found most engaging, and why.

An analysis of United States K-12 stem education versus STEM workforce at the dawn of the digital revolution

NASA Astrophysics Data System (ADS)

Cataldo, Franca

The world is at the dawn of a third industrial revolution, the digital revolution, that brings great changes the world over. Today, computing devices, the Internet, and the World Wide Web are vital technology tools that affect every aspect of everyday life and success. While computing technologies offer enormous benefits, there are equally enormous safety and security risks that have been growing exponentially since they became widely available to the public in 1994. Cybercriminals are increasingly implementing sophisticated and serious hack attacks and breaches upon our nation's government, financial institutions, organizations, communities, and private citizens. There is a great need for computer scientists to carry America's innovation and economic growth forward and for cybersecurity professionals to keep our nation safe from criminal hacking. In this digital age, computer science and cybersecurity are essential foundational ingredients of technological innovation, economic growth, and cybersecurity that span all industries. Yet, America's K-12 education institutions are not teaching the computer science and cybersecurity skills required to produce a technologically-savvy 21st century workforce. Education is the key to preparing students to enter the workforce and, therefore, American K-12 STEM education must be reformed to accommodate the teachings required in the digital age. Keywords: Cybersecurity Education, Cybersecurity Education Initiatives, Computer Science Education, Computer Science Education Initiatives, 21 st Century K-12 STEM Education Reform, 21st Century Digital Literacies, High-Tech Innovative Problem-Solving Skills, 21st Century Digital Workforce, Standardized Testing, Foreign Language and Culture Studies, Utica College, Professor Chris Riddell.

Computable visually observed phenotype ontological framework for plants

PubMed Central

2011-01-01

Background The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research. Conclusions The Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community. PMID:21702966

The Argonne Leadership Computing Facility 2010 annual report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drugan, C.

Researchers found more ways than ever to conduct transformative science at the Argonne Leadership Computing Facility (ALCF) in 2010. Both familiar initiatives and innovative new programs at the ALCF are now serving a growing, global user community with a wide range of computing needs. The Department of Energy's (DOE) INCITE Program remained vital in providing scientists with major allocations of leadership-class computing resources at the ALCF. For calendar year 2011, 35 projects were awarded 732 million supercomputer processor-hours for computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering. Argonne also continued tomore » provide Director's Discretionary allocations - 'start up' awards - for potential future INCITE projects. And DOE's new ASCR Leadership Computing (ALCC) Program allocated resources to 10 ALCF projects, with an emphasis on high-risk, high-payoff simulations directly related to the Department's energy mission, national emergencies, or for broadening the research community capable of using leadership computing resources. While delivering more science today, we've also been laying a solid foundation for high performance computing in the future. After a successful DOE Lehman review, a contract was signed to deliver Mira, the next-generation Blue Gene/Q system, to the ALCF in 2012. The ALCF is working with the 16 projects that were selected for the Early Science Program (ESP) to enable them to be productive as soon as Mira is operational. Preproduction access to Mira will enable ESP projects to adapt their codes to its architecture and collaborate with ALCF staff in shaking down the new system. We expect the 10-petaflops system to stoke economic growth and improve U.S. competitiveness in key areas such as advancing clean energy and addressing global climate change. Ultimately, we envision Mira as a stepping-stone to exascale-class computers that will be faster than petascale-class computers by a factor of a thousand. Pete Beckman, who served as the ALCF's Director for the past few years, has been named director of the newly created Exascale Technology and Computing Institute (ETCi). The institute will focus on developing exascale computing to extend scientific discovery and solve critical science and engineering problems. Just as Pete's leadership propelled the ALCF to great success, we know that that ETCi will benefit immensely from his expertise and experience. Without question, the future of supercomputing is certainly in good hands. I would like to thank Pete for all his effort over the past two years, during which he oversaw the establishing of ALCF2, the deployment of the Magellan project, increases in utilization, availability, and number of projects using ALCF1. He managed the rapid growth of ALCF staff and made the facility what it is today. All the staff and users are better for Pete's efforts.« less

Enlarging the STEM pipeline working with youth-serving organizations

NASA Astrophysics Data System (ADS)

Porro, I.

2005-12-01

The After-School Astronomy Project (ASAP) is a comprehensive initiative to promote the pursuit of science learning among underrepresented youth. To this end ASAP specifically aims at building the capacity of urban community-based centers to deliver innovative science out-of-school programming to their youth. ASAP makes use of a modular curriculum consisting of a combination of hands-on activities and youth-led explorations of the night sky using MicroObservatory. Through project-based investigations students reinforce learning in astronomy and develop an understanding of science as inquiry, while also develop communication and computer skills. Through MicroObservatory students gain access to a network of educational telescopes, that they control over the Internet, software analysis tools and an online community of users. An integral part of ASAP is to provide professional development opportunities for after-school workers. This promotes a self-sustainable implementation of ASAP long-term and fosters the creation of a cadre of after-school professionals dedicated to facilitating science-based programs.

The 3d International Workshop on Computational Electronics

NASA Astrophysics Data System (ADS)

Goodnick, Stephen M.

1994-09-01

The Third International Workshop on Computational Electronics (IWCE) was held at the Benson Hotel in downtown Portland, Oregon, on May 18, 19, and 20, 1994. The workshop was devoted to a broad range of topics in computational electronics related to the simulation of electronic transport in semiconductors and semiconductor devices, particularly those which use large computational resources. The workshop was supported by the National Science Foundation (NSF), the Office of Naval Research and the Army Research Office, as well as local support from the Oregon Joint Graduate Schools of Engineering and the Oregon Center for Advanced Technology Education. There were over 100 participants in the Portland workshop, of which more than one quarter represented research groups outside of the United States from Austria, Canada, France, Germany, Italy, Japan, Switzerland, and the United Kingdom. There were a total 81 papers presented at the workshop, 9 invited talks, 26 oral presentations and 46 poster presentations. The emphasis of the contributions reflected the interdisciplinary nature of computational electronics with researchers from the Chemistry, Computer Science, Mathematics, Engineering, and Physics communities participating in the workshop.

Adult Literacy and Technology Newsletter. Vol. 3, Nos. 1-4.

ERIC Educational Resources Information Center

Gueble, Ed, Ed.

1989-01-01

This document consists of four issues of a newsletter focused on the spectrum of technology use in literacy instruction. The first issue contains the following articles: "Five 'Big' Systems and One 'Little' Option" (Weisberg); "Computer Use Patterns at Blackfeet Community College" (Hill); "Software Review: Educational Activities' Science Series"…

Richard Feynman and computation

NASA Astrophysics Data System (ADS)

Hey, Tony

1999-04-01

The enormous contribution of Richard Feynman to modern physics is well known, both to teaching through his famous Feynman Lectures on Physics, and to research with his Feynman diagram approach to quantum field theory and his path integral formulation of quantum mechanics. Less well known perhaps is his long-standing interest in the physics of computation and this is the subject of this paper. Feynman lectured on computation at Caltech for most of the last decade of his life, first with John Hopfield and Carver Mead, and then with Gerry Sussman. The story of how these lectures came to be written up as the Feynman Lectures on Computation is briefly recounted. Feynman also discussed the fundamentals of computation with other legendary figures of the computer science and physics community such as Ed Fredkin, Rolf Landauer, Carver Mead, Marvin Minsky and John Wheeler. He was also instrumental in stimulating developments in both nanotechnology and quantum computing. During the 1980s Feynman re-visited long-standing interests both in parallel computing with Geoffrey Fox and Danny Hillis, and in reversible computation and quantum computing with Charles Bennett, Norman Margolus, Tom Toffoli and Wojciech Zurek. This paper records Feynman's links with the computational community and includes some reminiscences about his involvement with the fundamentals of computing.

ISMB 2016 offers outstanding science, networking, and celebration

PubMed Central

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392

ISMB 2016 offers outstanding science, networking, and celebration.

PubMed

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

LSST Resources for the Community

NASA Astrophysics Data System (ADS)

Jones, R. Lynne

2011-01-01

LSST will generate 100 petabytes of images and 20 petabytes of catalogs, covering 18,000-20,000 square degrees of area sampled every few days, throughout a total of ten years of time -- all publicly available and exquisitely calibrated. The primary access to this data will be through Data Access Centers (DACs). DACs will provide access to catalogs of sources (single detections from individual images) and objects (associations of sources from multiple images). Simple user interfaces or direct SQL queries at the DAC can return user-specified portions of data from catalogs or images. More complex manipulations of the data, such as calculating multi-point correlation functions or creating alternative photo-z measurements on terabyte-scale data, can be completed with the DAC's own resources. Even more data-intensive computations requiring access to large numbers of image pixels on petabyte-scale could also be conducted at the DAC, using compute resources allocated in a similar manner to a TAC. DAC resources will be available to all individuals in member countries or institutes and LSST science collaborations. DACs will also assist investigators with requests for allocations at national facilities such as the Petascale Computing Facility, TeraGrid, and Open Science Grid. Using data on this scale requires new approaches to accessibility and analysis which are being developed through interactions with the LSST Science Collaborations. We are producing simulated images (as might be acquired by LSST) based on models of the universe and generating catalogs from these images (as well as from the base model) using the LSST data management framework in a series of data challenges. The resulting images and catalogs are being made available to the science collaborations to verify the algorithms and develop user interfaces. All LSST software is open source and available online, including preliminary catalog formats. We encourage feedback from the community.

Advances in Machine Learning and Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

Way, Michael J.; Scargle, Jeffrey D.; Ali, Kamal M.; Srivastava, Ashok N.

2012-03-01

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

Data stewardship - a fundamental part of the scientific method (Invited)

NASA Astrophysics Data System (ADS)

Foster, C.; Ross, J.; Wyborn, L. A.

2013-12-01

This paper emphasises the importance of data stewardship as a fundamental part of the scientific method, and the need to effect cultural change to ensure engagement by earth scientists. It is differentiated from the science of data stewardship per se. Earth System science generates vast quantities of data, and in the past, data analysis has been constrained by compute power, such that sub-sampling of data often provided the only way to reach an outcome. This is analogous to Kahneman's System 1 heuristic, with its simplistic and often erroneous outcomes. The development of HPC has liberated earth sciences such that the complexity and heterogeneity of natural systems can be utilised in modelling at any scale, global, or regional, or local; for example, movement of crustal fluids. Paradoxically, now that compute power is available, it is the stewardship of the data that is presenting the main challenges. There is a wide spectrum of issues: from effectively handling and accessing acquired data volumes [e.g. satellite feeds per day/hour]; through agreed taxonomy to effect machine to machine analyses; to idiosyncratic approaches by individual scientists. Except for the latter, most agree that data stewardship is essential. Indeed it is an essential part of the science workflow. As science struggles to engage and inform on issues of community importance, such as shale gas and fraccing, all parties must have equal access to data used for decision making; without that, there will be no social licence to operate or indeed access to additional science funding (Heidorn, 2008). The stewardship of scientific data is an essential part of the science process; but often it is regarded, wrongly, as entirely in the domain of data custodians or stewards. Geoscience Australia has developed a set of six principles that apply to all science activities within the agency: Relevance to Government Collaborative science Quality science Transparent science Communicated science Sustained science capability Every principle includes data stewardship: this is to effect cultural change at both collective and individual levels to ensure that our science outcomes and technical advice are effective for the Government and community.

NSI customer service representatives and user support office: NASA Science Internet

NASA Technical Reports Server (NTRS)

1991-01-01

The NASA Science Internet, (NSI) was established in 1987 to provide NASA's Offices of Space Science and Applications (OSSA) missions with transparent wide-area data connectivity to NASA's researchers, computational resources, and databases. The NSI Office at NASA/Ames Research Center has the lead responsibility for implementing a total, open networking program to serve the OSSA community. NSI is a full-service communications provider whose services include science network planning, network engineering, applications development, network operations, and network information center/user support services. NSI's mission is to provide reliable high-speed communications to the NASA science community. To this end, the NSI Office manages and operates the NASA Science Internet, a multiprotocol network currently supporting both DECnet and TCP/IP protocols. NSI utilizes state-of-the-art network technology to meet its customers' requirements. THe NASA Science Internet interconnects with other national networks including the National Science Foundation's NSFNET, the Department of Energy's ESnet, and the Department of Defense's MILNET. NSI also has international connections to Japan, Australia, New Zealand, Chile, and several European countries. NSI cooperates with other government agencies as well as academic and commercial organizations to implement networking technologies which foster interoperability, improve reliability and performance, increase security and control, and expedite migration to the OSI protocols.

Grids for Dummies: Featuring Earth Science Data Mining Application

NASA Technical Reports Server (NTRS)

Hinke, Thomas H.

2002-01-01

This viewgraph presentation discusses the concept and advantages of linking computers together into data grids, an emerging technology for managing information across institutions, and potential users of data grids. The logistics of access to a grid, including the use of the World Wide Web to access grids, and security concerns are also discussed. The potential usefulness of data grids to the earth science community is also discussed, as well as the Global Grid Forum, and other efforts to establish standards for data grids.

SPICE: A Geometry Information System Supporting Planetary Mapping, Remote Sensing and Data Mining

NASA Technical Reports Server (NTRS)

Acton, C.; Bachman, N.; Semenov, B.; Wright, E.

2013-01-01

SPICE is an information system providing space scientists ready access to a wide assortment of space geometry useful in planning science observations and analyzing the instrument data returned therefrom. The system includes software used to compute many derived parameters such as altitude, LAT/LON and lighting angles, and software able to find when user-specified geometric conditions are obtained. While not a formal standard, it has achieved widespread use in the worldwide planetary science community

Citizen Science for Post-disaster Sustainable Community Development in Ecologically Fragiel Regions - A Case from China

NASA Astrophysics Data System (ADS)

Liu, Wei; Ming, Meng; Lu, Ye; Jin, Wei

2016-04-01

The world's mountains host some of the most complex, dynamic, and diverse ecosystems and are also hotspots for natural disasters, such as earthquake, landslide and flood. One factor that limits the mountain communities to recover from disasters and pursue sustainable development is the lack of locally relevant scientific knowledge, which is hard to gain from global and regional scale observations and models. The rapid advances in ICT, computing, communication technologies and the emergence of citizen science is changing the situation. Here we report a case from Sichuan Giant Panda Sanctuary World Natural Heritage in China on the application of citizen science in a community reconstruction project. Dahe, a mountainous community (ca. 8000 ha in size) is located covering part of the World Heritage's core and buffer zones, with an elevation range of 1000-3000 meters. The community suffered from two major earthquakes of 7.9 and 6.9 Mw in 2008 and 2013 respectively. Landslides and flooding threat the community and significantly limit their livelihood options. We integrated participatory disaster risk mapping (e.g., community vulnerability and capacity assessment) and mobile assisted natural hazards and natural resources mapping (e.g., using free APP GeoODK) into more conventional community reconstruction and livelihood building activities. We showed that better decisions are made based on results from these activities and local residents have a high level of buy-in in these new knowledge. We suggest that initiatives like this, if successfully scale-up, can also help generate much needed data and knowledge in similar less-developed and data deficient regions of the world.

Science Gateways, Scientific Workflows and Open Community Software

NASA Astrophysics Data System (ADS)

Pierce, M. E.; Marru, S.

2014-12-01

Science gateways and scientific workflows occupy different ends of the spectrum of user-focused cyberinfrastructure. Gateways, sometimes called science portals, provide a way for enabling large numbers of users to take advantage of advanced computing resources (supercomputers, advanced storage systems, science clouds) by providing Web and desktop interfaces and supporting services. Scientific workflows, at the other end of the spectrum, support advanced usage of cyberinfrastructure that enable "power users" to undertake computational experiments that are not easily done through the usual mechanisms (managing simulations across multiple sites, for example). Despite these different target communities, gateways and workflows share many similarities and can potentially be accommodated by the same software system. For example, pipelines to process InSAR imagery sets or to datamine GPS time series data are workflows. The results and the ability to make downstream products may be made available through a gateway, and power users may want to provide their own custom pipelines. In this abstract, we discuss our efforts to build an open source software system, Apache Airavata, that can accommodate both gateway and workflow use cases. Our approach is general, and we have applied the software to problems in a number of scientific domains. In this talk, we discuss our applications to usage scenarios specific to earth science, focusing on earthquake physics examples drawn from the QuakSim.org and GeoGateway.org efforts. We also examine the role of the Apache Software Foundation's open community model as a way to build up common commmunity codes that do not depend upon a single "owner" to sustain. Pushing beyond open source software, we also see the need to provide gateways and workflow systems as cloud services. These services centralize operations, provide well-defined programming interfaces, scale elastically, and have global-scale fault tolerance. We discuss our work providing Apache Airavata as a hosted service to provide these features.

Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Leary, Patrick

The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time ofmore » the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.« less

Practical Steps toward Computational Unification: Helpful Perspectives for New Systems, Adding Functionality to Existing Ones

NASA Astrophysics Data System (ADS)

Troy, R. M.

2005-12-01

With ever increasing amounts of Earth-Science funding being diverted to the war in Iraq, the Earth-Science community must now more than ever wring every bit of utility out of every dollar. We're not likely to get funded any projects perceived by others as "pie in the sky", so we have to look at already funded programs within our community and directing new programs in a unifying direction. We have not yet begun the transition to a computationally unifying, general-purpose Earth Science computing paradigm, though it was proposed at the Fall 2002 AGU meeting in San Francisco, and perhaps earlier. Encouragingly, we do see a recognition that more commonality is needed as various projects have as funded goals the addition of the processing and dissemination of new datatypes, or data-sets, if you prefer, to their existing repertoires. Unfortunately, the timelines projected for adding a datatype to an existing system are typically estimated at around two years each. Further, many organizations have the perception that they can only use their dollars to support exclusively their own needs as they don't have the money to support the goals of others, thus overlooking opportunities to satisfy their own needs while at the same time aiding the creation of a global GeoScience cyber-infrastructure. While Computational Unification appears to be an unfunded, impossible dream, at least for now, individual projects can take steps that are compatible with a unified community and can help build one over time. This session explores these opportunities. The author will discuss the issues surrounding this topic, outlining alternative perspectives on the points of difficulty, and proposing straight-forward solutions which every Earth Science data processing system should consider. Sub-topics include distributed meta-data, distributed processing, distributed data objects, interdisciplinary concerns, and scientific defensibility with an overall emphasis on how previously written processes and functions may be integrated into a system efficiently, with minimal effort, and with an eye toward an eventual Computational Unification of the Earth Sciences. A fundamental to such systems is meta-data which describe not only the content of data but also how intricate relationships are represented and used to good advantage. Retrieval techniques will be discussed including trade-offs in using externally managed meta-data versus embedded meta-data, how the two may be integrated, and how "simplifying assumptions" may or may not actually be helpful. The perspectives presented in this talk or poster session are based upon the experience of the Sequoia 2000 and BigSur research projects at the University of California, Berkeley, which sought to unify NASA's Mission To Planet Earth's EOS-DIS, and on-going experience developed by Science Tools corporation, of which the author is a principal. NOTE: These ideas are most easily shared in the form of a talk, and we suspect that this session will generate a lot of interest. We would therefore prefer to have this session accepted as a talk as opposed to a poster session.

Application of Database Approaches to the Study of Earth's Aeolian Environments: Community Needs and Goals

NASA Astrophysics Data System (ADS)

Scuderi, Louis A.; Weissmann, Gary S.; Hartley, Adrian J.; Yang, Xiaoping; Lancaster, Nicholas

2017-08-01

Aeolian science is faced with significant challenges that impact its ability to benefit from recent advances in information technology. The discipline deals with high-end systems in the form of ground and satellite based sensors, computer modeling and simulation, and wind tunnel experiments. Aeolian scientists also collect field data manually with observational methods that may differ significantly between studies with little agreement on even basic morphometric parameters and terminology. Data produced from these studies, while forming the core of research papers and reports, is rarely available to the community at large. Recent advances are also superimposed on an underlying semantic structure that dates to the 1800's or earlier that is confusing, with ambiguously defined, and at times even contradictory, meanings. The aeolian "world-view" does not always fit within neat increments nor is defined by crisp objects. Instead change is continuous and features are fuzzy. Development of an ontological framework to guide spatiotemporal research is the fundamental starting point for organizing data in aeolian science. This requires a "rethinking" of how we define, collect, process, store and share data along with the development of a community-wide collaborative approach designed to bring the discipline into a data rich future. There is also a pressing need to develop efficient methods to integrate, analyze and manage spatial and temporal data and to promote data produced by aeolian scientists so it is available for preparing diagnostic studies, as input into a range of environmental models, and for advising national and international bodies that drive research agendas. This requires the establishment of working groups within the discipline to deal with content, format, processing pipelines, knowledge discovery tools and database access issues unique to aeolian science. Achieving this goal requires the development of comprehensive and highly-organized databases, tools that allow aeolian scientists as well as those in related disciplines to access and analyze the wealth of data available, and a supporting infrastructure and community-wide effort that allows aeolian scientists to communicate their results in replicable ways to scientists and decision and policy makers. Fortunately, much of the groundwork required to move aeolian science into a data rich future has been developed in other data rich physical science fields, and within the computer science and information technology disciplines.

Climate change and health research: has it served rural communities?

PubMed

Bell, Erica J

2013-01-01

If climate change is the 21st Century's biggest public health threat, research faces the major challenge of providing adequate evidence for vulnerable communities to adapt to the health effects of climate change. Available information about best practice in climate adaptation suggests it is inclusive of socio-economic disadvantage and local community factors such as access to health services. Since 1995, at least 19 164 papers have been published on climate change in the health sciences and social sciences. This body of literature has not yet been systematically examined for how well it serves rural communities. The ultimate aim of the study was to contribute to better understandings about what climate adaptation research has been done and is needed for rural communities. The two research questions were: 'What kinds of content define climate change research in disciplines that could potentially contribute to adaptation for health?' and 'How is content about rural and Aboriginal communities and best practice in adaptation related to this content?' A quantitative content analysis was performed using 'computational linguistics' Leximancer software. The analysis included 19 164 health and social sciences abstracts, batched by years, from 1 January 1995 to 31 July 2012. The relative frequency and co-occurrence of 52 concepts in these abstracts were mapped, as well as associations with positive or negative sentiment for selected concepts. Aboriginal' concepts tend to be relatively infrequent (3% and 5% overall likelihood of occurrence, respectively) and are more associated with socio-economic concepts in the social sciences than the health sciences. Multiple concepts in the health sciences literature are typically connected with 'disease' and ultimately 'science' storylines, with a 38% likelihood of paired co-occurrence of 'health' and 'disease' concepts alone. The social sciences appear more focused on the local and particular issues of community in climate change than the health sciences. 'Rural' and 'Aboriginal' concepts have increased by 1% across both discipline areas, since 2011 for the 'rural' concept and since 2004 for the 'Aboriginal' concept. 'Health' concepts in the health sciences and 'economic' concepts in the social sciences, as well as 'urban' concepts, are referred to more positively than either the 'rural' or 'Aboriginal' concepts. While care needs to be taken in interpreting the results of this study too negatively for rural and Aboriginal communities, they suggest that a disease focus dominates climate and health research typically unconnected to wider socio-economic and human system factors. This finding needs to be considered in light of the accumulating evidence of the importance of such contextual systemic factors in understanding climate and health effects and responses. The study adds some support to the view that a key priority is bringing the learnings of applied community-based researchers, from those in rural health to those in the social sciences, to climate research. There is a need to build confidence, including in the rural health sector which has arguably been slow to participate in programs of climate change research, that community-based research could make a difference to rural health in a climate-changing world.

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets.

PubMed

McKinney, Bill; Meyer, Peter A; Crosas, Mercè; Sliz, Piotr

2017-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension-functionality supporting preservation of file system structure within Dataverse-which is essential for both in-place computation and supporting non-HTTP data transfers. © 2016 New York Academy of Sciences.

Overview of NASA communications infrastructure

NASA Technical Reports Server (NTRS)

Arnold, Ray J.; Fuechsel, Charles

1991-01-01

The infrastructure of NASA communications systems for effecting coordination across NASA offices and with the national and international research and technological communities is discussed. The offices and networks of the communication system include the Office of Space Science and Applications (OSSA), which manages all NASA missions, and the Office of Space Operations, which furnishes communication support through the NASCOM, the mission critical communications support network, and the Program Support Communications network. The NASA Science Internet was established by OSSA to centrally manage, develop, and operate an integrated computer network service dedicated to NASA's space science and application research. Planned for the future is the National Research and Education Network, which will provide communications infrastructure to enhance science resources at a national level.

Scout: high-performance heterogeneous computing made simple

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

Machine learning for Big Data analytics in plants.

PubMed

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

NASA Advanced Supercomputing Facility Expansion

NASA Technical Reports Server (NTRS)

Thigpen, William W.

2017-01-01

The NASA Advanced Supercomputing (NAS) Division enables advances in high-end computing technologies and in modeling and simulation methods to tackle some of the toughest science and engineering challenges facing NASA today. The name "NAS" has long been associated with leadership and innovation throughout the high-end computing (HEC) community. We play a significant role in shaping HEC standards and paradigms, and provide leadership in the areas of large-scale InfiniBand fabrics, Lustre open-source filesystems, and hyperwall technologies. We provide an integrated high-end computing environment to accelerate NASA missions and make revolutionary advances in science. Pleiades, a petaflop-scale supercomputer, is used by scientists throughout the U.S. to support NASA missions, and is ranked among the most powerful systems in the world. One of our key focus areas is in modeling and simulation to support NASA's real-world engineering applications and make fundamental advances in modeling and simulation methods.

Preface: SciDAC 2008

NASA Astrophysics Data System (ADS)

Stevens, Rick

2008-07-01

The fourth annual Scientific Discovery through Advanced Computing (SciDAC) Conference was held June 13-18, 2008, in Seattle, Washington. The SciDAC conference series is the premier communitywide venue for presentation of results from the DOE Office of Science's interdisciplinary computational science program. Started in 2001 and renewed in 2006, the DOE SciDAC program is the country's - and arguably the world's - most significant interdisciplinary research program supporting the development of advanced scientific computing methods and their application to fundamental and applied areas of science. SciDAC supports computational science across many disciplines, including astrophysics, biology, chemistry, fusion sciences, and nuclear physics. Moreover, the program actively encourages the creation of long-term partnerships among scientists focused on challenging problems and computer scientists and applied mathematicians developing the technology and tools needed to address those problems. The SciDAC program has played an increasingly important role in scientific research by allowing scientists to create more accurate models of complex processes, simulate problems once thought to be impossible, and analyze the growing amount of data generated by experiments. To help further the research community's ability to tap into the capabilities of current and future supercomputers, Under Secretary for Science, Raymond Orbach, launched the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program in 2003. The INCITE program was conceived specifically to seek out computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering. The program encourages proposals from universities, other research institutions, and industry. During the first two years of the INCITE program, 10 percent of the resources at NERSC were allocated to INCITE awardees. However, demand for supercomputing resources far exceeded available systems; and in 2003, the Office of Science identified increasing computing capability by a factor of 100 as the second priority on its Facilities of the Future list. The goal was to establish leadership-class computing resources to support open science. As a result of a peer reviewed competition, the first leadership computing facility was established at Oak Ridge National Laboratory in 2004. A second leadership computing facility was established at Argonne National Laboratory in 2006. This expansion of computational resources led to a corresponding expansion of the INCITE program. In 2008, Argonne, Lawrence Berkeley, Oak Ridge, and Pacific Northwest national laboratories all provided resources for INCITE. By awarding large blocks of computer time on the DOE leadership computing facilities, the INCITE program enables the largest-scale computations to be pursued. In 2009, INCITE will award over half a billion node-hours of time. The SciDAC conference celebrates progress in advancing science through large-scale modeling and simulation. Over 350 participants attended this year's talks, poster sessions, and tutorials, spanning the disciplines supported by DOE. While the principal focus was on SciDAC accomplishments, this year's conference also included invited presentations and posters from DOE INCITE awardees. Another new feature in the SciDAC conference series was an electronic theater and video poster session, which provided an opportunity for the community to see over 50 scientific visualizations in a venue equipped with many high-resolution large-format displays. To highlight the growing international interest in petascale computing, this year's SciDAC conference included a keynote presentation by Herman Lederer from the Max Planck Institut, one of the leaders of DEISA (Distributed European Infrastructure for Supercomputing Applications) project and a member of the PRACE consortium, Europe's main petascale project. We also heard excellent talks from several European groups, including Laurent Gicquel of CERFACS, who spoke on `Large-Eddy Simulations of Turbulent Reacting Flows of Real Burners: Status and Challenges', and Jean-Francois Hamelin from EDF, who presented a talk on `Getting Ready for Petaflop Capacities and Beyond: A Utility Perspective'. Two other compelling addresses gave attendees a glimpse into the future. Tomas Diaz de la Rubia of Lawrence Livermore National Laboratory spoke on a vision for a fusion/fission hybrid reactor known as the `LIFE Engine' and discussed some of the materials and modeling challenges that need to be overcome to realize the vision for a 1000-year greenhouse-gas-free power source. Dan Reed from Microsoft gave a capstone talk on the convergence of technology, architecture, and infrastructure for cloud computing, data-intensive computing, and exascale computing (1018 flops/sec). High-performance computing is making rapid strides. The SciDAC community's computational resources are expanding dramatically. In the summer of 2008 the first general purpose petascale system (IBM Cell-based RoadRunner at Los Alamos National Laboratory) was recognized in the top 500 list of fastest machines heralding in the dawning of the petascale era. The DOE's leadership computing facility at Argonne reached number three on the Top 500 and is at the moment the most capable open science machine based on an IBM BG/P system with a peak performance of over 550 teraflops/sec. Later this year Oak Ridge is expected to deploy a 1 petaflops/sec Cray XT system. And even before the scientific community has had an opportunity to make significant use of petascale systems, the computer science research community is forging ahead with ideas and strategies for development of systems that may by the end of the next decade sustain exascale performance. Several talks addressed barriers to, and strategies for, achieving exascale capabilities. The last day of the conference was devoted to tutorials hosted by Microsoft Research at a new conference facility in Redmond, Washington. Over 90 people attended the tutorials, which covered topics ranging from an introduction to BG/P programming to advanced numerical libraries. The SciDAC and INCITE programs and the DOE Office of Advanced Scientific Computing Research core program investments in applied mathematics, computer science, and computational and networking facilities provide a nearly optimum framework for advancing computational science for DOE's Office of Science. At a broader level this framework also is benefiting the entire American scientific enterprise. As we look forward, it is clear that computational approaches will play an increasingly significant role in addressing challenging problems in basic science, energy, and environmental research. It takes many people to organize and support the SciDAC conference, and I would like to thank as many of them as possible. The backbone of the conference is the technical program; and the task of selecting, vetting, and recruiting speakers is the job of the organizing committee. I thank the members of this committee for all the hard work and the many tens of conference calls that enabled a wonderful program to be assembled. This year the following people served on the organizing committee: Jim Ahrens, LANL; David Bader, LLNL; Bryan Barnett, Microsoft; Peter Beckman, ANL; Vincent Chan, GA; Jackie Chen, SNL; Lori Diachin, LLNL; Dan Fay, Microsoft; Ian Foster, ANL; Mark Gordon, Ames; Mohammad Khaleel, PNNL; David Keyes, Columbia University; Bob Lucas, University of Southern California; Tony Mezzacappa, ORNL; Jeff Nichols, ORNL; David Nowak, ANL; Michael Papka, ANL; Thomas Schultess, ORNL; Horst Simon, LBNL; David Skinner, LBNL; Panagiotis Spentzouris, Fermilab; Bob Sugar, UCSB; and Kathy Yelick, LBNL. I owe a special thanks to Mike Papka and Jim Ahrens for handling the electronic theater. I also thank all those who submitted videos. It was a highly successful experiment. Behind the scenes an enormous amount of work is required to make a large conference go smoothly. First I thank Cheryl Zidel for her tireless efforts as organizing committee liaison and posters chair and, in general, handling all of my end of the program and keeping me calm. I also thank Gail Pieper for her work in editing the proceedings, Beth Cerny Patino for her work on the Organizing Committee website and electronic theater, and Ken Raffenetti for his work in keeping that website working. Jon Bashor and John Hules did an excellent job in handling conference communications. I thank Caitlin Youngquist for the striking graphic design; Dan Fay for tutorials arrangements; and Lynn Dory, Suzanne Stevenson, Sarah Pebelske and Sarah Zidel for on-site registration and conference support. We all owe Yeen Mankin an extra-special thanks for choosing the hotel, handling contracts, arranging menus, securing venues, and reassuring the chair that everything was under control. We are pleased to have obtained corporate sponsorship from Cray, IBM, Intel, HP, and SiCortex. I thank all the speakers and panel presenters. I also thank the former conference chairs Tony Metzzacappa, Bill Tang, and David Keyes, who were never far away for advice and encouragement. Finally, I offer my thanks to Michael Strayer, without whose leadership, vision, and persistence the SciDAC program would not have come into being and flourished. I am honored to be part of his program and his friend. Rick Stevens Seattle, Washington July 18, 2008

Computational oncology.

PubMed

Lefor, Alan T

2011-08-01

Oncology research has traditionally been conducted using techniques from the biological sciences. The new field of computational oncology has forged a new relationship between the physical sciences and oncology to further advance research. By applying physics and mathematics to oncologic problems, new insights will emerge into the pathogenesis and treatment of malignancies. One major area of investigation in computational oncology centers around the acquisition and analysis of data, using improved computing hardware and software. Large databases of cellular pathways are being analyzed to understand the interrelationship among complex biological processes. Computer-aided detection is being applied to the analysis of routine imaging data including mammography and chest imaging to improve the accuracy and detection rate for population screening. The second major area of investigation uses computers to construct sophisticated mathematical models of individual cancer cells as well as larger systems using partial differential equations. These models are further refined with clinically available information to more accurately reflect living systems. One of the major obstacles in the partnership between physical scientists and the oncology community is communications. Standard ways to convey information must be developed. Future progress in computational oncology will depend on close collaboration between clinicians and investigators to further the understanding of cancer using these new approaches.

Adaptation of XMM-Newton SAS to GRID and VO architectures via web

NASA Astrophysics Data System (ADS)

Ibarra, A.; de La Calle, I.; Gabriel, C.; Salgado, J.; Osuna, P.

2008-10-01

The XMM-Newton Scientific Analysis Software (SAS) is a robust software that has allowed users to produce good scientific results since the beginning of the mission. This has been possible given the SAS capability to evolve with the advent of new technologies and adapt to the needs of the scientific community. The prototype of the Remote Interface for Science Analysis (RISA) presented here, is one such example, which provides remote analysis of XMM-Newton data with access to all the existing SAS functionality, while making use of GRID computing technology. This new technology has recently emerged within the astrophysical community to tackle the ever lasting problem of computer power for the reduction of large amounts of data.

Computer-assisted instruction: a library service for the community teaching hospital.

PubMed

McCorkel, J; Cook, V

1986-04-01

This paper reports on five years of experience with computer-assisted instruction (CAI) at Winthrop-University Hospital, a major affiliate of the SUNY at Stony Brook School of Medicine. It compares CAI programs available from Ohio State University and Massachusetts General Hospital (accessed by telephone and modem), and software packages purchased from the Health Sciences Consortium (MED-CAPS) and Scientific American (DISCOTEST). The comparison documents one library's experience of the cost of these programs and the use made of them by medical students, house staff, and attending physicians. It describes the space allocated for necessary equipment, as well as the marketing of CAI. Finally, in view of the decision of the National Board of Medical Examiners to administer the Part III examination on computer (the so-called CBX) starting in 1988, the paper speculates on the future importance of CAI in the community teaching hospital.

seismo-live: Training in Computational Seismology using Jupyter Notebooks

NASA Astrophysics Data System (ADS)

Igel, H.; Krischer, L.; van Driel, M.; Tape, C.

2016-12-01

Practical training in computational methodologies is still underrepresented in Earth science curriculae despite the increasing use of sometimes highly sophisticated simulation technologies in research projects. At the same time well-engineered community codes make it easy to return simulation-based results yet with the danger that the inherent traps of numerical solutions are not well understood. It is our belief that training with highly simplified numerical solutions (here to the equations describing elastic wave propagation) with carefully chosen elementary ingredients of simulation technologies (e.g., finite-differencing, function interpolation, spectral derivatives, numerical integration) could substantially improve this situation. For this purpose we have initiated a community platform (www.seismo-live.org) where Python-based Jupyter notebooks can be accessed and run without and necessary downloads or local software installations. The increasingly popular Jupyter notebooks allow combining markup language, graphics, equations with interactive, executable python codes. We demonstrate the potential with training notebooks for the finite-difference method, pseudospectral methods, finite/spectral element methods, the finite-volume and the discontinuous Galerkin method. The platform already includes general Python training, introduction to the ObsPy library for seismology as well as seismic data processing and noise analysis. Submission of Jupyter notebooks for general seismology are encouraged. The platform can be used for complementary teaching in Earth Science courses on compute-intensive research areas.

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.

Microelectronic Information Processing Systems: Computing Systems. Summary of Awards Fiscal Year 1994.

ERIC Educational Resources Information Center

National Science Foundation, Arlington, VA. Directorate for Computer and Information Science and Engineering.

The purpose of this summary of awards is to provide the scientific and engineering communities with a summary of the grants awarded in 1994 by the National Science Foundation's Division of Microelectronic Information Processing Systems. Similar areas of research are grouped together. Grantee institutions and principal investigators are identified…

Providing Computer-Based Information Services to an Academic Community. Final Technical Report.

ERIC Educational Resources Information Center

Bayer, Bernard

The Mechanized Information Center (MIC) at the Ohio State University conducts retrospective and current awareness searches for faculty, students, and staff using data bases for agriculture, chemistry, education, psychology, and social sciences, as well as a multidisciplinary data base. The final report includes (1) a description of the background…

Equity: Ownership by Minorities and Women of Research Projects.

ERIC Educational Resources Information Center

Wilkinson, Patricia; Sher, Lawrence

Beginning in 1987, a reform movement was heavily funded by the National Science Foundation (NSF) to change the teaching of calculus. Borough of Manhattan Community College (BMCC) received seven NSF grants over an eight-year period, allowing the college to: establish a state-of-the-art calculus computer lab; purchase calculators, graphing…

seismo-live: Training in Seismology using Jupyter Notebooks

NASA Astrophysics Data System (ADS)

Igel, Heiner; Krischer, Lion; van Driel, Martin; Tape, Carl

2017-04-01

Practical training in computational methodologies is still underrepresented in Earth science curriculae despite the increasing use of sometimes highly sophisticated simulation and data processing technologies in research projects. At the same time well-engineered community codes make it easy to return results yet with the danger that the inherent traps of black-box solutions are not well understood. For this purpose we have initiated a community platform (www.seismo-live.org) where Python-based Jupyter notebooks can be accessed and run without necessary downloads or local software installations. The increasingly popular Jupyter notebooks allow combining markup language, graphics, equations, with interactive, executable python codes. The platform already includes general Python training, introduction to the ObsPy library for seismology as well as seismic data processing, noise analysis, and a variety of forward solvers for seismic wave propagation. In addition, an example is shown how Jupyter notebooks can be used to increase reproducibility of published results. Submission of Jupyter notebooks for general seismology are encouraged. The platform can be used for complementary teaching in Earth Science courses on compute-intensive research areas. We present recent developments and new features.

The quantum computer game: citizen science

NASA Astrophysics Data System (ADS)

Damgaard, Sidse; Mølmer, Klaus; Sherson, Jacob

2013-05-01

Progress in the field of quantum computation is hampered by daunting technical challenges. Here we present an alternative approach to solving these by enlisting the aid of computer players around the world. We have previously examined a quantum computation architecture involving ultracold atoms in optical lattices and strongly focused tweezers of light. In The Quantum Computer Game (see http://www.scienceathome.org/), we have encapsulated the time-dependent Schrödinger equation for the problem in a graphical user interface allowing for easy user input. Players can then search the parameter space with real-time graphical feedback in a game context with a global high-score that rewards short gate times and robustness to experimental errors. The game which is still in a demo version has so far been tried by several hundred players. Extensions of the approach to other models such as Gross-Pitaevskii and Bose-Hubbard are currently under development. The game has also been incorporated into science education at high-school and university level as an alternative method for teaching quantum mechanics. Initial quantitative evaluation results are very positive. AU Ideas Center for Community Driven Research, CODER.

NCI HPC Scaling and Optimisation in Climate, Weather, Earth system science and the Geosciences

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Bermous, I.; Freeman, J.; Roberts, D. S.; Ward, M. L.; Yang, R.

2016-12-01

The Australian National Computational Infrastructure (NCI) has a national focus in the Earth system sciences including climate, weather, ocean, water management, environment and geophysics. NCI leads a Program across its partners from the Australian science agencies and research communities to identify priority computational models to scale-up. Typically, these cases place a large overall demand on the available computer time, need to scale to higher resolutions, use excessive scarce resources such as large memory or bandwidth that limits, or in some cases, need to meet requirements for transition to a separate operational forecasting system, with set time-windows. The model codes include the UK Met Office Unified Model atmospheric model (UM), GFDL's Modular Ocean Model (MOM), both the UK Met Office's GC3 and Australian ACCESS coupled-climate systems (including sea ice), 4D-Var data assimilation and satellite processing, the Regional Ocean Model (ROMS), and WaveWatch3 as well as geophysics codes including hazards, magentuellerics, seismic inversions, and geodesy. Many of these codes use significant compute resources both for research applications as well as within the operational systems. Some of these models are particularly complex, and their behaviour had not been critically analysed for effective use of the NCI supercomputer or how they could be improved. As part of the Program, we have established a common profiling methodology that uses a suite of open source tools for performing scaling analyses. The most challenging cases are profiling multi-model coupled systems where the component models have their own complex algorithms and performance issues. We have also found issues within the current suite of profiling tools, and no single tool fully exposes the nature of the code performance. As a result of this work, international collaborations are now in place to ensure that improvements are incorporated within the community models, and our effort can be targeted in a coordinated way. The coordinations have involved user stakeholders, the model developer community, and dependent software libraries. For example, we have spent significant time characterising I/O scalability, and improving the use of libraries such as NetCDF and HDF5.

Computational Materials Program for Alloy Design

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo

2005-01-01

The research program sponsored by this grant, "Computational Materials Program for Alloy Design", covers a period of time of enormous change in the emerging field of computational materials science. The computational materials program started with the development of the BFS method for alloys, a quantum approximate method for atomistic analysis of alloys specifically tailored to effectively deal with the current challenges in the area of atomistic modeling and to support modern experimental programs. During the grant period, the program benefited from steady growth which, as detailed below, far exceeds its original set of goals and objectives. Not surprisingly, by the end of this grant, the methodology and the computational materials program became an established force in the materials communitiy, with substantial impact in several areas. Major achievements during the duration of the grant include the completion of a Level 1 Milestone for the HITEMP program at NASA Glenn, consisting of the planning, development and organization of an international conference held at the Ohio Aerospace Institute in August of 2002, finalizing a period of rapid insertion of the methodology in the research community worlwide. The conference, attended by citizens of 17 countries representing various fields of the research community, resulted in a special issue of the leading journal in the area of applied surface science. Another element of the Level 1 Milestone was the presentation of the first version of the Alloy Design Workbench software package, currently known as "adwTools". This software package constitutes the first PC-based piece of software for atomistic simulations for both solid alloys and surfaces in the market.Dissemination of results and insertion in the materials community worldwide was a primary focus during this period. As a result, the P.I. was responsible for presenting 37 contributed talks, 19 invited talks, and publishing 71 articles in peer-reviewed journals, as detailed later in this Report.

Transiting Exoplanet Survey Satellite (TESS) Community Observer Program including the Science Enhancement Option Box (SEO Box) - 12 TB On-board Flash Memory for Serendipitous Science

NASA Astrophysics Data System (ADS)

Schingler, Robert; Villasenor, J. N.; Ricker, G. R.; Latham, D. W.; Vanderspek, R. K.; Ennico, K. A.; Lewis, B. S.; Bakos, G.; Brown, T. M.; Burgasser, A. J.; Charbonneau, D.; Clampin, M.; Deming, L. D.; Doty, J. P.; Dunham, E. W.; Elliot, J. L.; Holman, M. J.; Ida, S.; Jenkins, J. M.; Jernigan, J. G.; Kawai, N.; Laughlin, G. P.; Lissauer, J. J.; Martel, F.; Sasselov, D. D.; Seager, S.; Torres, G.; Udry, S.; Winn, J. N.; Worden, S. P.

2010-01-01

The Transiting Exoplanet Survey Satellite (TESS) will perform an all-sky survey in a low-inclination, low-Earth orbit. TESS's 144 GB of raw data collected each orbit will be stacked, cleaned, cut, compressed and downloaded. The Community Observer Program is a Science Enhancement Option (SEO) that takes advantage of the low-radiation environment, technology advances in flash memory, and the vast amount of astronomical data collected by TESS. The Community Observer Program requires the addition of a 12 TB "SEO Box” inside the TESS Bus. The hardware can be built using low-cost Commercial Off-The-Shelf (COTS) components and fits within TESS's margins while accommodating GSFC gold rules. The SEO Box collects and stores a duplicate of the TESS camera data at a "raw” stage ( 4.3 GB/orbit, after stacking and cleaning) and makes them available for on-board processing. The sheer amount of onboard storage provided by the SEO Box allows the stacking and storing of several months of data, allowing the investigator to probe deeper in time prior to a given event. Additionally, with computation power and data in standard formats, investigators can utilize data-mining techniques to investigate serendipitous phenomenon, including pulsating stars, eclipsing binaries, supernovae or other transient phenomena. The Community Observer Program enables ad-hoc teams of citizen scientists to propose, test, refine and rank algorithms for on-board analysis to support serendipitous science. Combining "best practices” of online collaboration, with careful moderation and community management, enables this `crowd sourced’ participatory exploration with a minimal risk and impact on the core TESS Team. This system provides a powerful and independent tool opening a wide range of opportunity for science enhancement and secondary science. Support for this work has been provided by NASA, the Kavli Foundation, Google, and the Smithsonian Institution.

Careers in Data Science: A Berkeley Perspective

NASA Astrophysics Data System (ADS)

Koy, K.

2015-12-01

Last year, I took on an amazing opportunity to serve as the Executive Director of the new Berkeley Institute for Data Science (BIDS). After a 15-year career working with geospatial data to advance our understanding of the environment, I have been presented with a unique opportunity through BIDS to work with talented researchers from a wide variety of backgrounds. Founded in 2013, BIDS is a central hub of research and education at UC Berkeley designed to facilitate and nurture data-intensive science. We are building a community centered on a cohort of talented data science fellows and senior fellows who are representative of the world-class researchers from across our campus and are leading the data science revolution within their disciplines. Our initiatives are designed to bring together broad constituents of the data science community, including domain experts from the life, social, and physical sciences and methodological experts from computer science, statistics, and applied mathematics. While many of these individuals rarely cross professional paths, BIDS actively seeks new and creative ways to engage and foster collaboration across these different research fields. In this presentation, I will share my own story, along with some insights into how BIDS is supporting the careers of data scientists, including graduate students, postdocs, faculty, and research staff. I will also describe how these individuals we are helping support are working to address a number of data science-related challenges in scientific research.

Community Petascale Project for Accelerator Science and Simulation: Advancing Computational Science for Future Accelerators and Accelerator Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spentzouris, P.; /Fermilab; Cary, J.

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The ComPASS organization for software development and applications accounts for the natural domain areas (beam dynamics, electromagnetics, and advanced acceleration), and all areas depend on the enabling technologies activities, such as solvers and component technology, to deliver the desired performance and integrated simulation environment. The ComPASS applications focus on computationally challenging problems important for design or performance optimization to all major HEP, NP, and BES accelerator facilities. With the cost and complexity of particle accelerators rising, the use of computation to optimize their designs and find improved operating regimes becomes essential, potentially leading to significant cost savings with modest investment.« less

The Open Science Grid - Support for Multi-Disciplinary Team Science - the Adolescent Years

NASA Astrophysics Data System (ADS)

Bauerdick, Lothar; Ernst, Michael; Fraser, Dan; Livny, Miron; Pordes, Ruth; Sehgal, Chander; Würthwein, Frank; Open Science Grid

2012-12-01

As it enters adolescence the Open Science Grid (OSG) is bringing a maturing fabric of Distributed High Throughput Computing (DHTC) services that supports an expanding HEP community to an increasingly diverse spectrum of domain scientists. Working closely with researchers on campuses throughout the US and in collaboration with national cyberinfrastructure initiatives, we transform their computing environment through new concepts, advanced tools and deep experience. We discuss examples of these including: the pilot-job overlay concepts and technologies now in use throughout OSG and delivering 1.4 Million CPU hours/day; the role of campus infrastructures- built out from concepts of sharing across multiple local faculty clusters (made good use of already by many of the HEP Tier-2 sites in the US); the work towards the use of clouds and access to high throughput parallel (multi-core and GPU) compute resources; and the progress we are making towards meeting the data management and access needs of non-HEP communities with general tools derived from the experience of the parochial tools in HEP (integration of Globus Online, prototyping with IRODS, investigations into Wide Area Lustre). We will also review our activities and experiences as HTC Service Provider to the recently awarded NSF XD XSEDE project, the evolution of the US NSF TeraGrid project, and how we are extending the reach of HTC through this activity to the increasingly broad national cyberinfrastructure. We believe that a coordinated view of the HPC and HTC resources in the US will further expand their impact on scientific discovery.

Developing a Science Commons for Geosciences

NASA Astrophysics Data System (ADS)

Lenhardt, W. C.; Lander, H.

2016-12-01

Many scientific communities, recognizing the research possibilities inherent in data sets, have created domain specific archives such as the Incorporated Research Institutions for Seismology (iris.edu) and ClinicalTrials.gov. Though this is an important step forward, most scientists, including geoscientists, also use a variety of software tools and at least some amount of computation to conduct their research. While the archives make it simpler for scientists to locate the required data, provisioning disk space, compute resources, and network bandwidth can still require significant efforts. This challenge exists despite the wealth of resources available to researchers, namely lab IT resources, institutional IT resources, national compute resources (XSEDE, OSG), private clouds, public clouds, and the development of cyberinfrastructure technologies meant to facilitate use of those resources. Further tasks include obtaining and installing required tools for analysis and visualization. If the research effort is a collaboration or involves certain types of data, then the partners may well have additional non-scientific tasks such as securing the data and developing secure sharing methods for the data. These requirements motivate our investigations into the "Science Commons". This paper will present a working definition of a science commons, compare and contrast examples of existing science commons, and describe a project based at RENCI to implement a science commons for risk analytics. We will then explore what a similar tool might look like for the geosciences.

Realizing Scientific Methods for Cyber Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carroll, Thomas E.; Manz, David O.; Edgar, Thomas W.

There is little doubt among cyber security researchers about the lack of scientic rigor that underlies much of the liter-ature. The issues are manifold and are well documented. Further complicating the problem is insufficient scientic methods to address these issues. Cyber security melds man and machine: we inherit the challenges of computer science, sociology, psychology, and many other elds and create new ones where these elds interface. In this paper we detail a partial list of challenges imposed by rigorous science and survey how other sciences have tackled them, in the hope of applying a similar approach to cyber securitymore » science. This paper is by no means comprehensive: its purpose is to foster discussion in the community on how we can improve rigor in cyber security science.« less

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Building the interspace: Digital library infrastructure for a University Engineering Community

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schatz, B.

A large-scale digital library is being constructed and evaluated at the University of Illinois, with the goal of bringing professional search and display to Internet information services. A testbed planned to grow to 10K documents and 100K users is being constructed in the Grainger Engineering Library Information Center, as a joint effort of the University Library and the National Center for Supercomputing Applications (NCSA), with evaluation and research by the Graduate School of Library and Information Science and the Department of Computer Science. The electronic collection will be articles from engineering and science journals and magazines, obtained directly from publishersmore » in SGML format and displayed containing all text, figures, tables, and equations. The publisher partners include IEEE Computer Society, AIAA (Aerospace Engineering), American Physical Society, and Wiley & Sons. The software will be based upon NCSA Mosaic as a network engine connected to commercial SGML displayers and full-text searchers. The users will include faculty/students across the midwestern universities in the Big Ten, with evaluations via interviews, surveys, and transaction logs. Concurrently, research into scaling the testbed is being conducted. This includes efforts in computer science, information science, library science, and information systems. These efforts will evaluate different semantic retrieval technologies, including automatic thesaurus and subject classification graphs. New architectures will be designed and implemented for a next generation digital library infrastructure, the Interspace, which supports interaction with information spread across information spaces within the Net.« less

Cloud computing approaches to accelerate drug discovery value chain.

PubMed

Garg, Vibhav; Arora, Suchir; Gupta, Chitra

2011-12-01

Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

Designing highly flexible and usable cyberinfrastructures for convergence.

PubMed

Herr, Bruce W; Huang, Weixia; Penumarthy, Shashikant; Börner, Katy

2006-12-01

This article presents the results of a 7-year-long quest into the development of a "dream tool" for our research in information science and scientometrics and more recently, network science. The results are two cyberinfrastructures (CI): The Cyberinfrastructure for Information Visualization and the Network Workbench that enjoy a growing national and interdisciplinary user community. Both CIs use the cyberinfrastructure shell (CIShell) software specification, which defines interfaces between data sets and algorithms/services and provides a means to bundle them into powerful tools and (Web) services. In fact, CIShell might be our major contribution to progress in convergence. Just as Wikipedia is an "empty shell" that empowers lay persons to share text, a CIShell implementation is an "empty shell" that empowers user communities to plug-and-play, share, compare and combine data sets, algorithms, and compute resources across national and disciplinary boundaries. It is argued here that CIs will not only transform the way science is conducted but also will play a major role in the diffusion of expertise, data sets, algorithms, and technologies across multiple disciplines and business sectors leading to a more integrative science.

Big Computing in Astronomy: Perspectives and Challenges

NASA Astrophysics Data System (ADS)

Pankratius, Victor

2014-06-01

Hardware progress in recent years has led to astronomical instruments gathering large volumes of data. In radio astronomy for instance, the current generation of antenna arrays produces data at Tbits per second, and forthcoming instruments will expand these rates much further. As instruments are increasingly becoming software-based, astronomers will get more exposed to computer science. This talk therefore outlines key challenges that arise at the intersection of computer science and astronomy and presents perspectives on how both communities can collaborate to overcome these challenges.Major problems are emerging due to increases in data rates that are much larger than in storage and transmission capacity, as well as humans being cognitively overwhelmed when attempting to opportunistically scan through Big Data. As a consequence, the generation of scientific insight will become more dependent on automation and algorithmic instrument control. Intelligent data reduction will have to be considered across the entire acquisition pipeline. In this context, the presentation will outline the enabling role of machine learning and parallel computing.BioVictor Pankratius is a computer scientist who joined MIT Haystack Observatory following his passion for astronomy. He is currently leading efforts to advance astronomy through cutting-edge computer science and parallel computing. Victor is also involved in projects such as ALMA Phasing to enhance the ALMA Observatory with Very-Long Baseline Interferometry capabilities, the Event Horizon Telescope, as well as in the Radio Array of Portable Interferometric Detectors (RAPID) to create an analysis environment using parallel computing in the cloud. He has an extensive track record of research in parallel multicore systems and software engineering, with contributions to auto-tuning, debugging, and empirical experiments studying programmers. Victor has worked with major industry partners such as Intel, Sun Labs, and Oracle. He holds a distinguished doctorate and a Habilitation degree in Computer Science from the University of Karlsruhe. Contact him at pankrat@mit.edu, victorpankratius.com, or Twitter @vpankratius.

Z-Score-Based Modularity for Community Detection in Networks

PubMed Central

Miyauchi, Atsushi; Kawase, Yasushi

2016-01-01

Identifying community structure in networks is an issue of particular interest in network science. The modularity introduced by Newman and Girvan is the most popular quality function for community detection in networks. In this study, we identify a problem in the concept of modularity and suggest a solution to overcome this problem. Specifically, we obtain a new quality function for community detection. We refer to the function as Z-modularity because it measures the Z-score of a given partition with respect to the fraction of the number of edges within communities. Our theoretical analysis shows that Z-modularity mitigates the resolution limit of the original modularity in certain cases. Computational experiments using both artificial networks and well-known real-world networks demonstrate the validity and reliability of the proposed quality function. PMID:26808270

Unraveling the Complexities of Life Sciences Data.

PubMed

Higdon, Roger; Haynes, Winston; Stanberry, Larissa; Stewart, Elizabeth; Yandl, Gregory; Howard, Chris; Broomall, William; Kolker, Natali; Kolker, Eugene

2013-03-01

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.

University participation via UNIDATA, part 1

NASA Technical Reports Server (NTRS)

Dutton, J.

1986-01-01

The UNIDATA Project is a cooperative university project, operated by the University Corporation for Atmospheric Research (UCAR) with National Science Foundation (NSF) funding, aimed at providing interactive communication and computations to the university community in the atmospheric and oceanic sciences. The initial focus has been on providing access to data for weather analysis and prediction. However, UNIDATA is in the process of expanding and possibly providing access to the Pilot Climate Data System (PCDS) through the UNIDATA system in an effort to develop prototypes for an Earth science information system. The notion of an Earth science information system evolved from discussions within NASA and several advisory committees in anticipation of receiving data from the many Earth observing instruments on the space station complex (Earth Observing System).

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, Wes

2016-07-24

The primary challenge motivating this team’s work is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who are able to perform analysis only on a small fraction of the data they compute, resulting in the very real likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, an approach that is known as in situ processing. The idea in situ processing wasmore » not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by DOE science projects. In large, our objective was produce and enable use of production-quality in situ methods and infrastructure, at scale, on DOE HPC facilities, though we expected to have impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve that objective, we assembled a unique team of researchers consisting of representatives from DOE national laboratories, academia, and industry, and engaged in software technology R&D, as well as engaged in close partnerships with DOE science code teams, to produce software technologies that were shown to run effectively at scale on DOE HPC platforms.« less

The Development of Pre-Service Science Teachers' Professional Knowledge in Utilizing ICT to Support Professional Lives

ERIC Educational Resources Information Center

Arnold, Savittree Rochanasmita; Padilla, Michael J.; Tunhikorn, Bupphachart

2009-01-01

In the rapidly developing digital world, technology is and will be a force in workplaces, communities, and everyday lives in the 21st century. Information and Communication Technology (ICT) including computer hardware/software, networking and other technologies such as audio, video, and other multimedia tools became learning tools for students in…

Shaping Software Engineering Curricula Using Open Source Communities: A Case Study

ERIC Educational Resources Information Center

Bowring, James; Burke, Quinn

2016-01-01

This paper documents four years of a novel approach to teaching a two-course sequence in software engineering as part of the ABET-accredited computer science curriculum at the College of Charleston. This approach is team-based and centers on learning software engineering in the context of open source software projects. In the first course, teams…

The Seeds of Artificial Intelligence. SUMEX-AIM.

ERIC Educational Resources Information Center

Research Resources Information Center, Rockville, MD.

Written to provide an understanding of the broad base of information on which the artificial intelligence (AI) branch of computer science rests, this publication presents a general view of AI, the concepts from which it evolved, its current abilities, and its promise for research. The focus is on a community of projects that use the SUMEX-AIM…

Communicating forest management science and practices through visualized and animated media approaches to community presentations: An exploration and assessment

Treesearch

Donald E. Zimmerman; Carol Akerelrea; Jane Kapler Smith; Garrett J. O' Keefe

2006-01-01

Natural-resource managers have used a variety of computer-mediated presentation methods to communicate management practices to diverse publics. We explored the effects of visualizing and animating predictions from mathematical models in computerized presentations explaining forest succession (forest growth and change through time), fire behavior, and management options...

Campus Community Partnerships with People Who Are Deaf or Hard-of-Hearing

ERIC Educational Resources Information Center

Matteson, Jamie; Kha, Christine K.; Hu, Diane J.; Cheng, Chih-Chieh; Saul, Lawrence; Sadler, Georgia Robins

2008-01-01

In 1997, the Moores University of California, San Diego (UCSD) Cancer Center and advocacy groups for people who are deaf and hard of hearing launched a highly hearing, successful cancer control collaborative. In 2006, faculty from the Computer Science Department at UCSD invited the collaborative to help develop a new track in their doctoral…

[The Durkheim Test. Remarks on Susan Leigh Star's Boundary Objects].

PubMed

Gießmann, Sebastian

2015-09-01

The article reconstructs Susan Leigh Star's conceptual work on the notion of 'boundary objects'. It traces the emergence of the concept, beginning with her PhD thesis and its publication as Regions of the Mind in 1989. 'Boundary objects' attempt to represent the distributed, multifold nature of scientific work and its mediations between different 'social worlds'. Being addressed to several 'communities of practice', the term responded to questions from Distributed Artificial Intelligence in Computer Science, Workplace Studies and Computer Supported Cooperative Work (CSCW), and microhistorical approaches inside the growing Science and Technology Studies. Yet the interdisciplinary character and interpretive flexibility of Star’s invention has rarely been noticed as a conceptual tool for media theory. I therefore propose to reconsider Star's 'Durkheim test' for sociotechnical media practices.

Land Cover Change Community-based Processing and Analysis System (LC-ComPS): Lessons Learned from Technology Infusion

NASA Astrophysics Data System (ADS)

Masek, J.; Rao, A.; Gao, F.; Davis, P.; Jackson, G.; Huang, C.; Weinstein, B.

2008-12-01

The Land Cover Change Community-based Processing and Analysis System (LC-ComPS) combines grid technology, existing science modules, and dynamic workflows to enable users to complete advanced land data processing on data available from local and distributed archives. Changes in land cover represent a direct link between human activities and the global environment, and in turn affect Earth's climate. Thus characterizing land cover change has become a major goal for Earth observation science. Many science algorithms exist to generate new products (e.g., surface reflectance, change detection) used to study land cover change. The overall objective of the LC-ComPS is to release a set of tools and services to the land science community that can be implemented as a flexible LC-ComPS to produce surface reflectance and land-cover change information with ground resolution on the order of Landsat-class instruments. This package includes software modules for pre-processing Landsat-type satellite imagery (calibration, atmospheric correction, orthorectification, precision registration, BRDF correction) for performing land-cover change analysis and includes pre-built workflow chains to automatically generate surface reflectance and land-cover change products based on user input. In order to meet the project objectives, the team created the infrastructure (i.e., client-server system with graphical and machine interfaces) to expand the use of these existing science algorithm capabilities in a community with distributed, large data archives and processing centers. Because of the distributed nature of the user community, grid technology was chosen to unite the dispersed community resources. At that time, grid computing was not used consistently and operationally within the Earth science research community. Therefore, there was a learning curve to configure and implement the underlying public key infrastructure (PKI) interfaces, required for the user authentication, secure file transfer and remote job execution on the grid network of machines. In addition, science support was needed to vet that the grid technology did not have any adverse affects of the science module outputs. Other open source, unproven technologies, such as a workflow package to manage jobs submitted by the user, were infused into the overall system with successful results. This presentation will discuss the basic capabilities of LC-ComPS, explain how the technology was infused, and provide lessons learned for using and integrating the various technologies while developing and operating the system, and finally outline plans moving forward (maintenance and operations decisions) based on the experience to date.

Virality Prediction and Community Structure in Social Networks

NASA Astrophysics Data System (ADS)

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-08-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Virality Prediction and Community Structure in Social Networks

PubMed Central

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

Virality prediction and community structure in social networks.

PubMed

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities

NASA Technical Reports Server (NTRS)

Bonan, Gordon; Santanello, Joseph A., Jr.

2013-01-01

Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.

The Teaching of Anthropogenic Climate Change and Earth Science via Technology-Enabled Inquiry Education

NASA Technical Reports Server (NTRS)

Bush, Drew; Sieber, Renee; Seiler, Gale; Chandler, Mark

2016-01-01

A gap has existed between the tools and processes of scientists working on anthropogenic global climate change (AGCC) and the technologies and curricula available to educators teaching the subject through student inquiry. Designing realistic scientific inquiry into AGCC poses a challenge because research on it relies on complex computer models, globally distributed data sets, and complex laboratory and data collection procedures. Here we examine efforts by the scientific community and educational researchers to design new curricula and technology that close this gap and impart robust AGCC and Earth Science understanding. We find technology-based teaching shows promise in promoting robust AGCC understandings if associated curricula address mitigating factors such as time constraints in incorporating technology and the need to support teachers implementing AGCC and Earth Science inquiry. We recommend the scientific community continue to collaborate with educational researchers to focus on developing those inquiry technologies and curricula that use realistic scientific processes from AGCC research and/or the methods for determining how human society should respond to global change.

Enabling interoperability in planetary sciences and heliophysics: The case for an information model

NASA Astrophysics Data System (ADS)

Hughes, J. Steven; Crichton, Daniel J.; Raugh, Anne C.; Cecconi, Baptiste; Guinness, Edward A.; Isbell, Christopher E.; Mafi, Joseph N.; Gordon, Mitchell K.; Hardman, Sean H.; Joyner, Ronald S.

2018-01-01

The Planetary Data System has developed the PDS4 Information Model to enable interoperability across diverse science disciplines. The Information Model is based on an integration of International Organization for Standardization (ISO) level standards for trusted digital archives, information model development, and metadata registries. Where controlled vocabularies provides a basic level of interoperability by providing a common set of terms for communication between both machines and humans the Information Model improves interoperability by means of an ontology that provides semantic information or additional related context for the terms. The information model was defined by team of computer scientists and science experts from each of the diverse disciplines in the Planetary Science community, including Atmospheres, Geosciences, Cartography and Imaging Sciences, Navigational and Ancillary Information, Planetary Plasma Interactions, Ring-Moon Systems, and Small Bodies. The model was designed to be extensible beyond the Planetary Science community, for example there are overlaps between certain PDS disciplines and the Heliophysics and Astrophysics disciplines. "Interoperability" can apply to many aspects of both the developer and the end-user experience, for example agency-to-agency, semantic level, and application level interoperability. We define these types of interoperability and focus on semantic level interoperability, the type of interoperability most directly enabled by an information model.

The changing landscape of astrostatistics and astroinformatics

NASA Astrophysics Data System (ADS)

Feigelson, Eric D.

2017-06-01

The history and current status of the cross-disciplinary fields of astrostatistics and astroinformatics are reviewed. Astronomers need a wide range of statistical methods for both data reduction and science analysis. With the proliferation of high-throughput telescopes, efficient large scale computational methods are also becoming essential. However, astronomers receive only weak training in these fields during their formal education. Interest in the fields is rapidly growing with conferences organized by scholarly societies, textbooks and tutorial workshops, and research studies pushing the frontiers of methodology. R, the premier language of statistical computing, can provide an important software environment for the incorporation of advanced statistical and computational methodology into the astronomical community.

Integrated environmental modeling: a vision and roadmap for the future

USGS Publications Warehouse

Laniak, Gerard F.; Olchin, Gabriel; Goodall, Jonathan; Voinov, Alexey; Hill, Mary; Glynn, Pierre; Whelan, Gene; Geller, Gary; Quinn, Nigel; Blind, Michiel; Peckham, Scott; Reaney, Sim; Gaber, Noha; Kennedy, Philip R.; Hughes, Andrew

2013-01-01

Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).

Sustaining Open Source Communities through Hackathons - An Example from the ASPECT Community

NASA Astrophysics Data System (ADS)

Heister, T.; Hwang, L.; Bangerth, W.; Kellogg, L. H.

2016-12-01

The ecosystem surrounding a successful scientific open source software package combines both social and technical aspects. Much thought has been given to the technology side of writing sustainable software for large infrastructure projects and software libraries, but less about building the human capacity to perpetuate scientific software used in computational modeling. One effective format for building capacity is regular multi-day hackathons. Scientific hackathons bring together a group of science domain users and scientific software contributors to make progress on a specific software package. Innovation comes through the chance to work with established and new collaborations. Especially in the domain sciences with small communities, hackathons give geographically distributed scientists an opportunity to connect face-to-face. They foster lively discussions amongst scientists with different expertise, promote new collaborations, and increase transparency in both the technical and scientific aspects of code development. ASPECT is an open source, parallel, extensible finite element code to simulate thermal convection, that began development in 2011 under the Computational Infrastructure for Geodynamics. ASPECT hackathons for the past 3 years have grown the number of authors to >50, training new code maintainers in the process. Hackathons begin with leaders establishing project-specific conventions for development, demonstrating the workflow for code contributions, and reviewing relevant technical skills. Each hackathon expands the developer community. Over 20 scientists add >6,000 lines of code during the >1 week event. Participants grow comfortable contributing to the repository and over half continue to contribute afterwards. A high return rate of participants ensures continuity and stability of the group as well as mentoring for novice members. We hope to build other software communities on this model, but anticipate each to bring their own unique challenges.

Challenges in integrating multidisciplinary data into a single e-infrastructure

NASA Astrophysics Data System (ADS)

Atakan, Kuvvet; Jeffery, Keith G.; Bailo, Daniele; Harrison, Matthew

2015-04-01

The European Plate Observing System (EPOS) aims to create a pan-European infrastructure for solid Earth science to support a safe and sustainable society. The mission of EPOS is to monitor and understand the dynamic and complex Earth system by relying on new e-science opportunities and integrating diverse and advanced Research Infrastructures in Europe for solid Earth Science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. EPOS will improve our ability to better manage the use of the subsurface of the Earth. Through integration of data, models and facilities EPOS will allow the Earth Science community to make a step change in developing new concepts and tools for key answers to scientific and socio-economic questions concerning geo-hazards and geo-resources as well as Earth sciences applications to the environment and to human welfare. EPOS is now getting into its Implementation Phase (EPOS-IP). One of the main challenges during the implementation phase is the integration of multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. TCS data, data products and services will be integrated into a platform "the ICS system" that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. This requires dedicated tasks for interactions with the various TCS-WPs, as well as the various distributed ICS (ICS-Ds), such as High Performance Computing (HPC) facilities, large scale data storage facilities, complex processing and visualization tools etc. Computational Earth Science (CES) services are identified as a transversal activity and as such need to be harmonized and provided within the ICS. In order to develop a metadata catalogue and the ICS system, the content from the entire spectrum of services included in TCS, ICS-Ds as well as CES activities, need to be organized in a systematic manner taking into account global and European IT-standards, while complying with the user needs and data provider requirements.

Damsel: A Data Model Storage Library for Exascale Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhary, Alok; Liao, Wei-keng

Computational science applications have been described as having one of seven motifs (the “seven dwarfs”), each having a particular pattern of computation and communication. From a storage and I/O perspective, these applications can also be grouped into a number of data model motifs describing the way data is organized and accessed during simulation, analysis, and visualization. Major storage data models developed in the 1990s, such as Network Common Data Format (netCDF) and Hierarchical Data Format (HDF) projects, created support for more complex data models. Development of both netCDF and HDF5 was influenced by multi-dimensional dataset storage requirements, but their accessmore » models and formats were designed with sequential storage in mind (e.g., a POSIX I/O model). Although these and other high-level I/O libraries have had a beneficial impact on large parallel applications, they do not always attain a high percentage of peak I/O performance due to fundamental design limitations, and they do not address the full range of current and future computational science data models. The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. The project consists of three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community. The product of this project, Damsel library, is openly available for download from http://cucis.ece.northwestern.edu/projects/DAMSEL. Several case studies and application programming interface reference are also available to assist new users to learn to use the library.« less

Havery Mudd 2014-2015 Computer Science Conduit Clinic Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aspesi, G; Bai, J; Deese, R

2015-05-12

Conduit, a new open-source library developed at Lawrence Livermore National Laboratories, provides a C++ application programming interface (API) to describe and access scientific data. Conduit’s primary use is for inmemory data exchange in high performance computing (HPC) applications. Our team tested and improved Conduit to make it more appealing to potential adopters in the HPC community. We extended Conduit’s capabilities by prototyping four libraries: one for parallel communication using MPI, one for I/O functionality, one for aggregating performance data, and one for data visualization.

Virtual Geophysics Laboratory: Exploiting the Cloud and Empowering Geophysicsts

NASA Astrophysics Data System (ADS)

Fraser, Ryan; Vote, Josh; Goh, Richard; Cox, Simon

2013-04-01

Over the last five decades geoscientists from Australian state and federal agencies have collected and assembled around 3 Petabytes of geoscience data sets under public funding. As a consequence of technological progress, data is now being acquired at exponential rates and in higher resolution than ever before. Effective use of these big data sets challenges the storage and computational infrastructure of most organizations. The Virtual Geophysics Laboratory (VGL) is a scientific workflow portal addresses some of the resulting issues by providing Australian geophysicists with access to a Web 2.0 or Rich Internet Application (RIA) based integrated environment that exploits eResearch tools and Cloud computing technology, and promotes collaboration between the user community. VGL simplifies and automates large portions of what were previously manually intensive scientific workflow processes, allowing scientists to focus on the natural science problems, rather than computer science and IT. A number of geophysical processing codes are incorporated to support multiple workflows. For example a gravity inversion can be performed by combining the Escript/Finley codes (from the University of Queensland) with the gravity data registered in VGL. Likewise, tectonic processes can also be modeled by combining the Underworld code (from Monash University) with one of the various 3D models available to VGL. Cloud services provide scalable and cost effective compute resources. VGL is built on top of mature standards-compliant information services, many deployed using the Spatial Information Services Stack (SISS), which provides direct access to geophysical data. A large number of data sets from Geoscience Australia assist users in data discovery. GeoNetwork provides a metadata catalog to store workflow results for future use, discovery and provenance tracking. VGL has been developed in collaboration with the research community using incremental software development practices and open source tools. While developed to provide the geophysics research community with a sustainable platform and scalable infrastructure; VGL has also developed a number of concepts, patterns and generic components of which have been reused for cases beyond geophysics, including natural hazards, satellite processing and other areas requiring spatial data discovery and processing. Future plans for VGL include a number of improvements in both functional and non-functional areas in response to its user community needs and advancement in information technologies. In particular, research is underway in the following areas (a) distributed and parallel workflow processing in the cloud, (b) seamless integration with various cloud providers, and (c) integration with virtual laboratories representing other science domains. Acknowledgements: VGL was developed by CSIRO in collaboration with Geoscience Australia, National Computational Infrastructure, Australia National University, Monash University and University of Queensland, and has been supported by the Australian Government's Education Investment Funds through NeCTAR.

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.« less

Exposing the Science in Citizen Science: Fitness to Purpose and Intentional Design.

PubMed

Parrish, Julia K; Burgess, Hillary; Weltzin, Jake F; Fortson, Lucy; Wiggins, Andrea; Simmons, Brooke

2018-05-21

Citizen science is a growing phenomenon. With millions of people involved and billions of in-kind dollars contributed annually, this broad extent, fine grain approach to data collection should be garnering enthusiastic support in the mainstream science and higher education communities. However, many academic researchers demonstrate distinct biases against the use of citizen science as a source of rigorous information. To engage the public in scientific research, and the research community in the practice of citizen science, a mutual understanding is needed of accepted quality standards in science, and the corresponding specifics of project design and implementation when working with a broad public base. We define a science-based typology focused on the degree to which projects deliver the type(s) and quality of data/work needed to produce valid scientific outcomes directly useful in science and natural resource management. Where project intent includes direct contribution to science and the public is actively involved either virtually or hands-on, we examine the measures of quality assurance (methods to increase data quality during the design and implementation phases of a project) and quality control (post hoc methods to increase the quality of scientific outcomes). We suggest that high quality science can be produced with massive, largely one-off, participation if data collection is simple and quality control includes algorithm voting, statistical pruning and/or computational modeling. Small to mid-scale projects engaging participants in repeated, often complex, sampling can advance quality through expert-led training and well-designed materials, and through independent verification. Both approaches - simplification at scale and complexity with care - generate more robust science outcomes.

Bridging Informatics and Earth Science: a Look at Gregory Leptoukh's Contributions

NASA Technical Reports Server (NTRS)

2012-01-01

With the tragic passing this year of Gregory Leptoukh, the Earth and Space Sciences community lost a tireless participant in--and advocate for--science informatics. Throughout his career at NASA, Dr. Leptoukh established a theme of bridging the gulf between the informatics and science communities. Nowhere is this more evident than his leadership in the development of Giovanni (GES DISC Interactive Online Visualization ANd aNalysis Infrastructure). Giovanni is an online tool that serves to hide the often-complex technical details of data format and structure, making science data easier to explore and use by Earth scientists. To date Giovanni has been acknowledged as a contributor in 500-odd scientific articles. In recent years, Leptoukh concentrated his efforts on multi-sensor data inter-comparison, merging and fusion. This work exposed several challenges at the intersection of data and science. One of these was the ease with which a naive user might generate spurious comparisons, a potential hazard that was the genesis of the Multi-sensor Data Synergy Advisor (MDSA). The MDSA uses semantic ontologies and inference rules to organize knowledge about dataset quality and other salient characteristics in order to advise users on potential caveats for comparing or merging two datasets. Recently, Leptoukh also led the development of AeroStat, an online Giovanni instance to investigate aerosols via statistics from station and satellite comparisons and merged maps of data from more than one instrument. Aerostat offers a neural net based bias adjustment to harmonize the data by removing systematic offsets between datasets before merging. These examples exhibit Leptoukh's talent for adopting advanced computer technologies in the service of making science data more accessible to researchers. In this, he set an example that is at once both vital and challenging for the ESSI community to emulate.

Bridging Informatics and Earth Science: a Look at Gregory Leptoukh's Contributions

NASA Astrophysics Data System (ADS)

Lynnes, C.

2012-12-01

With the tragic passing this year of Gregory Leptoukh, the Earth and Space Sciences community lost a tireless participant in--and advocate for--science informatics. Throughout his career at NASA, Dr. Leptoukh established a theme of bridging the gulf between the informatics and science communities. Nowhere is this more evident than his leadership in the development of Giovanni (GES DISC Interactive Online Visualization ANd aNalysis Infrastructure). Giovanni is an online tool that serves to hide the often-complex technical details of data format and structure, making science data easier to explore and use by Earth scientists. To date Giovanni has been acknowledged as a contributor in 500-odd scientific articles. In recent years, Leptoukh concentrated his efforts on multi-sensor data inter-comparison, merging and fusion. This work exposed several challenges at the intersection of data and science. One of these was the ease with which a naive user might generate spurious comparisons, a potential hazard that was the genesis of the Multi-sensor Data Synergy Advisor (MDSA). The MDSA uses semantic ontologies and inference rules to organize knowledge about dataset quality and other salient characteristics in order to advise users on potential caveats for comparing or merging two datasets. Recently, Leptoukh also led the development of AeroStat, an online Giovanni instance to investigate aerosols via statistics from station and satellite comparisons and merged maps of data from more than one instrument. Aerostat offers a neural net based bias adjustment to "harmonize" the data by removing systematic offsets between datasets before merging. These examples exhibit Leptoukh's talent for adopting advanced computer technologies in the service of making science data more accessible to researchers. In this, he set an example that is at once both vital and challenging for the ESSI community to emulate.

The VERCE Science Gateway: Enabling User Friendly HPC Seismic Wave Simulations.

NASA Astrophysics Data System (ADS)

Casarotti, E.; Spinuso, A.; Matser, J.; Leong, S. H.; Magnoni, F.; Krause, A.; Garcia, C. R.; Muraleedharan, V.; Krischer, L.; Anthes, C.

2014-12-01

The EU-funded project VERCE (Virtual Earthquake and seismology Research Community in Europe) aims to deploy technologies which satisfy the HPC and data-intensive requirements of modern seismology.As a result of VERCE official collaboration with the EU project SCI-BUS, access to computational resources, like local clusters and international infrastructures (EGI and PRACE), is made homogeneous and integrated within a dedicated science gateway based on the gUSE framework. In this presentation we give a detailed overview on the progress achieved with the developments of the VERCE Science Gateway, according to a use-case driven implementation strategy. More specifically, we show how the computational technologies and data services have been integrated within a tool for Seismic Forward Modelling, whose objective is to offer the possibility to performsimulations of seismic waves as a service to the seismological community.We will introduce the interactive components of the OGC map based web interface and how it supports the user with setting up the simulation. We will go through the selection of input data, which are either fetched from federated seismological web services, adopting community standards, or provided by the users themselves by accessing their own document data store. The HPC scientific codes can be selected from a number of waveform simulators, currently available to the seismological community as batch tools or with limited configuration capabilities in their interactive online versions.The results will be staged out via a secure GridFTP transfer to a VERCE data layer managed by iRODS. The provenance information of the simulation will be automatically cataloged by the data layer via NoSQL techonologies.Finally, we will show the example of how the visualisation output of the gateway could be enhanced by the connection with immersive projection technology at the Virtual Reality and Visualisation Centre of Leibniz Supercomputing Centre (LRZ).

A new approach to the rationale discovery of polymeric biomaterials

PubMed Central

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

Computational biology and bioinformatics in Nigeria.

PubMed

Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-04-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

Computational Biology and Bioinformatics in Nigeria

PubMed Central

Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-01-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310

Benefits of Exchange Between Computer Scientists and Perceptual Scientists: A Panel Discussion

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Null, Cynthia H. (Technical Monitor)

1995-01-01

We have established several major goals for this panel: 1) Introduce the computer graphics community to some specific leaders in the use of perceptual psychology relating to computer graphics; 2) Enumerate the major results that are known, and provide a set of resources for finding others; 3) Identify research areas where knowledge of perceptual psychology can help computer system designers improve their systems; and 4) Provide advice to researchers on how they can establish collaborations in their own research programs. We believe this will be a very important panel. In addition to generating lively discussion, we hope to point out some of the fundamental issues that occur at the boundary between computer science and perception, and possibly help researchers avoid some of the common pitfalls.

From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity.

PubMed

Cristescu, Melania E

2014-10-01

DNA-based species identification, known as barcoding, transformed the traditional approach to the study of biodiversity science. The field is transitioning from barcoding individuals to metabarcoding communities. This revolution involves new sequencing technologies, bioinformatics pipelines, computational infrastructure, and experimental designs. In this dynamic genomics landscape, metabarcoding studies remain insular and biodiversity estimates depend on the particular methods used. In this opinion article, I discuss the need for a coordinated advancement of DNA-based species identification that integrates taxonomic and barcoding information. Such an approach would facilitate access to almost 3 centuries of taxonomic knowledge and 1 decade of building repository barcodes. Conservation projects are time sensitive, research funding is becoming restricted, and informed decisions depend on our ability to embrace integrative approaches to biodiversity science. Copyright © 2014 Elsevier Ltd. All rights reserved.

European grid services for global earth science

NASA Astrophysics Data System (ADS)

Brewer, S.; Sipos, G.

2012-04-01

This presentation will provide an overview of the distributed computing services that the European Grid Infrastructure (EGI) offers to the Earth Sciences community and also explain the processes whereby Earth Science users can engage with the infrastructure. One of the main overarching goals for EGI over the coming year is to diversify its user-base. EGI therefore - through the National Grid Initiatives (NGIs) that provide the bulk of resources that make up the infrastructure - offers a number of routes whereby users, either individually or as communities, can make use of its services. At one level there are two approaches to working with EGI: either users can make use of existing resources and contribute to their evolution and configuration; or alternatively they can work with EGI, and hence the NGIs, to incorporate their own resources into the infrastructure to take advantage of EGI's monitoring, networking and managing services. Adopting this approach does not imply a loss of ownership of the resources. Both of these approaches are entirely applicable to the Earth Sciences community. The former because researchers within this field have been involved with EGI (and previously EGEE) as a Heavy User Community and the latter because they have very specific needs, such as incorporating HPC services into their workflows, and these will require multi-skilled interventions to fully provide such services. In addition to the technical support services that EGI has been offering for the last year or so - the applications database, the training marketplace and the Virtual Organisation services - there now exists a dynamic short-term project framework that can be utilised to establish and operate services for Earth Science users. During this talk we will present a summary of various on-going projects that will be of interest to Earth Science users with the intention that suggestions for future projects will emerge from the subsequent discussions: • The Federated Cloud Task Force is already providing a cloud infrastructure through a few committed NGIs. This is being made available to research communities participating in the Task Force and the long-term aim is to integrate these national clouds into a pan-European infrastructure for scientific communities. • The MPI group provides support for application developers to port and scale up parallel applications to the global European Grid Infrastructure. • A lively portal developer and provider community that is able to setup and operate custom, application and/or community specific portals for members of the Earth Science community to interact with EGI. • A project to assess the possibilities for federated identity management in EGI and the readiness of EGI member states for federated authentication and authorisation mechanisms. • Operating resources and user support services to process data with new types of services and infrastructures, such as desktop grids, map-reduce frameworks, GPU clusters.

ISTP Science Data Systems and Products

NASA Astrophysics Data System (ADS)

Mish, William H.; Green, James L.; Reph, Mary G.; Peredo, Mauricio

1995-02-01

The International Solar-Terrestrial Physics (ISTP) program will provide simultaneous coordinated scientific measurements from most of the major areas of geospace including specific locations on the Earth's surface. This paper describes the comprehensive ISTP ground science data handling system which has been developed to promote optimal mission planning and efficient data processing, analysis and distribution. The essential components of this ground system are the ISTP Central Data Handling Facility (CDHF), the Information Processing Division's Data Distribution Facility (DDF), the ISTP/Global Geospace Science (GGS) Science Planning and Operations Facility (SPOF) and the NASA Data Archive and Distribution Service (NDADS). The ISTP CDHF is the one place in the program where measurements from this wide variety of geospace and ground-based instrumentation and theoretical studies are brought together. Subsequently, these data will be distributed, along with ancillary data, in a unified fashion to the ISTP Principal Investigator (PI) and Co-Investigator (CoI) teams for analysis on their local systems. The CDHF ingests the telemetry streams, orbit, attitude, and command history from the GEOTAIL, WIND, POLAR, SOHO, and IMP-8 Spacecraft; computes summary data sets, called Key Parameters (KPs), for each scientific instrument; ingests pre-computed KPs from other spacecraft and ground basel investigations; provides a computational platform for parameterized modeling; and provides a number of ‘data services” for the ISTP community of investigators. The DDF organizes the KPs, decommutated telemetry, and associated ancillary data into products for duistribution to the ISTP community on CD-ROMs. The SPOF is the component of the GGS program responsible for the development and coordination of ISTP science planning operations. The SPOF operates under the direction of the ISTP Project Scientist and is responsible for the development and coordination of the science plan for ISTP spacecraft. Instrument command requests for the WIND and POLAR investigations are submitted by the PIs to the SPOF where they are checked for science conflicts, forwarded to the GSFC Command Management Syntem/Payload Operations Control Center (CMS/POCC) for engineering conflict validation, and finally incorporated into the conflict-free science operations plan. Conflict resolution is accomplished through iteration between the PIs, SPOF and CMS and in consultation with the Project Scientist when necessary. The long term archival of ISTP KP and level-zero data will be undertaken by NASA's National Space Science Data Center using the NASA Data Archive and Distribution Service (NDADS). This on-line archive facility will provide rapid access to archived KPs and event data and includes security features to restrict access to the data during the time they are proprietary.

Place-based Learning About Climate with Elementary GLOBE

NASA Astrophysics Data System (ADS)

Hatheway, B.; Gardiner, L. S.; Harte, T.; Stanitski, D.; Taylor, J.

2017-12-01

Place-based education - helping students make connections between themselves, their community, and their local environment - is an important tool to help young learners understand their regional climate and start to learn about climate and environmental change. Elementary GLOBE storybooks and learning activities allow opportunities for place-based education instructional strategies about climate. In particular, two modules in the Elementary GLOBE unit - Seasons and Climate - provide opportunities for students to explore their local climate and environment. The storybooks and activities also make connections to other parts of elementary curriculum, such as arts, geography, and math. Over the long term, place-based education can also encourage students to be stewards of their local environment. A strong sense of place may help students to see themselves as stakeholders in their community and its resilience. In places that are particularly vulnerable to the impacts of climate and environmental change and the economic, social, and environmental tradeoffs of community decisions, helping young students developing a sense of place and to see the connection between Earth science, local community, and their lives can have a lasting impact on how a community evolves for decades to come. Elementary GLOBE was designed to help elementary teachers (i.e., grades K-4) integrate Earth system science topics into their curriculum as they teach literacy skills to students. This suite of instructional materials includes seven modules. Each module contains a science-based storybook and learning activities that support the science content addressed in the storybooks. Elementary GLOBE modules feature air quality, climate, clouds, Earth system, seasons, soil, and water. New eBooks allow students to read stories on computers or tablets, with the option of listening to each story with an audio recording. A new Elementary GLOBE Teacher Implementation Guide, published in 2017, provides educators with information and strategies how Elementary GLOBE modules can be effectively applied in classrooms, how Elementary GLOBE modules are aligned with national standards, and how student literacy and science inquiry skills can be strengthened while learning about the Earth system.

The European Plate Observing System (EPOS): Integrating Thematic Services for Solid Earth Science

NASA Astrophysics Data System (ADS)

Atakan, Kuvvet; Bailo, Daniele; Consortium, Epos

2016-04-01

The mission of EPOS is to monitor and understand the dynamic and complex Earth system by relying on new e-science opportunities and integrating diverse and advanced Research Infrastructures in Europe for solid Earth Science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. Through integration of data, models and facilities EPOS will allow the Earth Science community to make a step change in developing new concepts and tools for key answers to scientific and socio-economic questions concerning geo-hazards and geo-resources as well as Earth sciences applications to the environment and to human welfare. EPOS, during its Implementation Phase (EPOS-IP), will integrate multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. These include Data, Data-products, Services and Software (DDSS), from seismology, near fault observatories, geodetic observations, volcano observations, satellite observations, geomagnetic observations, as well as data from various anthropogenic hazard episodes, geological information and modelling. In addition, transnational access to multi-scale laboratories and geo-energy test-beds for low-carbon energy will be provided. TCS DDSS will be integrated into Integrated Core Services (ICS), a platform that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. This requires dedicated tasks for interactions with the various TCS-WPs, as well as the various distributed ICS (ICS-Ds), such as High Performance Computing (HPC) facilities, large scale data storage facilities, complex processing and visualization tools etc. Computational Earth Science (CES) services are identified as a transversal activity and is planned to be harmonized and provided within the ICS. Currently a comprehensive requirements and use cases elicitation process is started through interactions with the ten different Thematic Core Service work packages. The results of this will be used to harmonize the DDSS elements and prepare for interoperability across the various disciplines. For this purpose a dedicated workshop is planned where the representatives of all the TCS communities will jointly discuss and agree upon the harmonization process. The technical integration of the DDSS elements to a metadata structure adopting CERIF (Common European Research Information Format) standards will start after the harmonization process is completed. Various levels of maturity in the handling and availability of TCS specific DDSS elements among the different TCS groups, is one of the most challenging aspects of this integration. For this reason a roadmap for integration is being prepared where most mature DDSS elements will be implemented during the next 2 years after a community driven testing and validation process. Integration of the remaining DDSS elements will be a continuously evolving process in the coming years.

Building the Petascale National Environmental Research Interoperability Data Platform (NERDIP): Minimizing the 'Trough of Disillusionment' and Accelerating Pathways to the 'Plateau of Productivity'

NASA Astrophysics Data System (ADS)

Wyborn, L. A.; Evans, B. J. K.

2015-12-01

The National Computational Infrastructure (NCI) at the Australian National University (ANU) has evolved to become Australia's peak computing centre for national computational and Data-intensive Earth system science. More recently NCI collocated 10 Petabytes of 34 major national and international environmental, climate, earth system, geophysics and astronomy data collections to create the National Environmental Research Interoperability Data Platform (NERDIP). Spatial scales of the collections range from global to local ultra-high resolution, whilst sizes range from 3PB down to a few GB. The data is highly connected to both NCI HPC and cloud resources via low latency internal networks with massive bandwidth. Now that the collections are collocated on a single data platform, the 'Hype' and expectations around potential use cases for the NERDIP are high. Not unexpected issues are emerging such as access, licensing issues, ownership, and incompatible data standards. Many communities are standardised within their domain, but achieving true interdisciplinary science will require all communities to move towards open interoperable data formats such as NetCDF4/HDF5. This transition will impact on software using proprietary or non-open standards. But before we reach the 'Plateau of Productivity', there needs to be greater 'Enlightenment' of users to encourage them to realise that this unprecedented Earth system science platform provides a rich mine of opportunities for discovery and innovation for a diverse range of both domain-specific and interdisciplinary investigations including climate and weather research, impact analysis, environment, remote sensing and geophysics and develop new and innovative interdisciplinary use cases that will guide those architecting the system and help minimise the amplitude of the 'Trough of Disillusionment' and ensure greater productivity and uptake of the collections that make NERDIP unique in the next generation of Data-intensive Science.

Multi-Relational Characterization of Dynamic Social Network Communities

NASA Astrophysics Data System (ADS)

Lin, Yu-Ru; Sundaram, Hari; Kelliher, Aisling

The emergence of the mediated social web - a distributed network of participants creating rich media content and engaging in interactive conversations through Internet-based communication technologies - has contributed to the evolution of powerful social, economic and cultural change. Online social network sites and blogs, such as Facebook, Twitter, Flickr and LiveJournal, thrive due to their fundamental sense of "community". The growth of online communities offers both opportunities and challenges for researchers and practitioners. Participation in online communities has been observed to influence people's behavior in diverse ways ranging from financial decision-making to political choices, suggesting the rich potential for diverse applications. However, although studies on the social web have been extensive, discovering communities from online social media remains challenging, due to the interdisciplinary nature of this subject. In this article, we present our recent work on characterization of communities in online social media using computational approaches grounded on the observations from social science.

The winding road to being a code monkey

NASA Astrophysics Data System (ADS)

Sarahan, Michael

2017-09-01

I am now a software engineer at a company that provides data analytics services, and helps support the open source data science community. I have been a computer nerd for a very long time, but it was my CEU experience at Texas A&M with Sherry Yennello (2003-2005) that helped me put my nerd skills to productive use. My project then was simulation of pulse shape discrimination electronics, and it was an excellent introduction to core computational concerns, such as digitization: when you see a line on the screen, that's not really how the computer sees it. I wandered in graduate school through a chemistry program into using electron microscopes. My programming interest got me into image and signal processing, which led naturally to jobs in analyzing data, and also in acquiring data. Throughout, it was always difficult just to make software work. I got pretty good at making it work. That's what I do for a living now - package software so that it is easy for other people to do great science with.

P3: a practice focused learning environment

NASA Astrophysics Data System (ADS)

Irving, Paul W.; Obsniuk, Michael J.; Caballero, Marcos D.

2017-09-01

There has been an increased focus on the integration of practices into physics curricula, with a particular emphasis on integrating computation into the undergraduate curriculum of scientists and engineers. In this paper, we present a university-level, introductory physics course for science and engineering majors at Michigan State University called P3 (projects and practices in physics) that is centred around providing introductory physics students with the opportunity to appropriate various science and engineering practices. The P3 design integrates computation with analytical problem solving and is built upon a curriculum foundation of problem-based learning, the principles of constructive alignment and the theoretical framework of community of practice. The design includes an innovative approach to computational physics instruction, instructional scaffolds, and a unique approach to assessment that enables instructors to guide students in the development of the practices of a physicist. We present the very positive student related outcomes of the design gathered via attitudinal and conceptual inventories and research interviews of students’ reflecting on their experiences in the P3 classroom.

A Federal Vision for Future Computing: A Nanotechnology-Inspired Grand Challenge

DTIC Science & Technology

2016-07-29

Science Foundation (NSF), Department of Defense (DOD), National Institute of Standards and Technology (NIST), Intelligence Community (IC) Introduction...multiple Federal agencies: • Intelligent big data sensors that act autonomously and are programmable via the network for increased flexibility, and... intelligence for scientific discovery enabled by rapid extreme-scale data analysis, capable of understanding and making sense of results and thereby

A DS106 Thing Happened on the Way to the 3M Tech Forum

ERIC Educational Resources Information Center

Lockridge, Rochelle; Levine, Alan; Funes, Mariana

2014-01-01

This case study illustrates how DS106, a computer science course in Digital Storytelling from the University of Mary Washington (UMW) and accessible as an open course on the web, is being explored in a corporate environment at 3M, an American multinational corporation based in St. Paul, Minnesota, to build community, collaboration, and more…

An Evaluation of Applying Blended Practices to Employ Studio-Based Learning in a Large-Enrollment Design Thinking Course

ERIC Educational Resources Information Center

Brown, Sydney E.; Karle, Sarah Thomas; Kelly, Brian

2015-01-01

DSGN110 was a multidisciplinary course teaching first year students enrolled in in a variety of majors about design thinking. The course is offered for the majors of architecture, landscape architecture, interior design, community and regional planning, along with computer science and business students. By blending face-to-face and online…

e-Infrastructures for e-Sciences 2013 A CHAIN-REDS Workshop organised under the aegis of the European Commission

NASA Astrophysics Data System (ADS)

The CHAIN-REDS Project is organising a workshop on "e-Infrastructures for e-Sciences" focusing on Cloud Computing and Data Repositories under the aegis of the European Commission and in co-location with the International Conference on e-Science 2013 (IEEE2013) that will be held in Beijing, P.R. of China on October 17-22, 2013. The core objective of the CHAIN-REDS project is to promote, coordinate and support the effort of a critical mass of non-European e-Infrastructures for Research and Education to collaborate with Europe addressing interoperability and interoperation of Grids and other Distributed Computing Infrastructures (DCI). From this perspective, CHAIN-REDS will optimise the interoperation of European infrastructures with those present in 6 other regions of the world, both from a development and use point of view, and catering to different communities. Overall, CHAIN-REDS will provide input for future strategies and decision-making regarding collaboration with other regions on e-Infrastructure deployment and availability of related data; it will raise the visibility of e-Infrastructures towards intercontinental audiences, covering most of the world and will provide support to establish globally connected and interoperable infrastructures, in particular between the EU and the developing regions. Organised by IHEP, INFN and Sigma Orionis with the support of all project partners, this workshop will aim at: - Presenting the state of the art of Cloud computing in Europe and in China and discussing the opportunities offered by having interoperable and federated e-Infrastructures; - Exploring the existing initiatives of Data Infrastructures in Europe and China, and highlighting the Data Repositories of interest for the Virtual Research Communities in several domains such as Health, Agriculture, Climate, etc.

Entropy Masking

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Stone, Leland (Technical Monitor)

1997-01-01

This paper details two projects that use the World Wide Web (WWW) for dissemination of curricula that focus on remote sensing. 1) Presenting grade-school students with the concepts used in remote sensing involves educating the teacher and then providing the teacher with lesson plans. In a NASA-sponsored project designed to introduce students in grades 4 through 12 to some of the ideas and terminology used in remote sensing, teachers from local grade schools and middle schools were recruited to write lessons about remote sensing concepts they could use in their classrooms. Twenty-two lessons were produced and placed in seven modules that include: the electromagnetic spectrum, two- and three-dimensional perception, maps and topography, scale, remote sensing, biotic and abiotic concepts, and landscape chi rise. Each lesson includes a section that evaluates what students have learned by doing the exercise. The lessons, instead of being published in a workbook and distributed to a limited number of teachers, have been placed on a WWW server, enabling much broader access to the package. This arrangement also allows for the lessons to be modified after feedback from teachers accessing the package. 2) Two-year colleges serve to teach trade skills, prepare students for enrollment in senior institutions of learning, and more and more, retrain students who have college degrees in new technologies and skills. A NASA-sponsored curriculum development project is producing a curriculum using remote sensing analysis an Earth science applications. The project has three major goals. First, it will implement the use of remote sensing data in a broad range of community college courses. Second, it will create curriculum modules and classes that are transportable to other community colleges. Third, the project will be an ongoing source of data and curricular materials to other community colleges. The curriculum will have these course pathways to a certificate; a) a Science emphasis, b) an Arts and Letters emphasis, and c) a Computer Science emphasis Each pathway includes course work in remote sensing, geographical information systems (GIS), computer science, Earth science, software and technology utilization, and communication. Distribution of products from this project to other two-year colleges will be accomplished using the WWW.

An Integrated Approach to Engineering Education in a Minority Community

NASA Technical Reports Server (NTRS)

Taylor, Bill

1998-01-01

Northeastern New Mexico epitomizes regions which are economically depressed, rural, and predominantly Hispanic. New Mexico Highlands University (NMHU), with a small student population of approximately 2800, offers a familiar environment attracting students who might otherwise not attend college. An outreach computer network of minority schools was created in northeastern New Mexico with NASA funding. Rural and urban minority schools gained electronic access to each other, to computer resources, to technical help at New Mexico Highlands University and gained access to the world via the Internet. This outreach program was initiated in the fall of 1992 in an effort to attract and to involve minority students in Engineering and the Mathematical Sciences. We installed 56 Kbs Internet connections to eight elementary schools, two middle schools, two high schools, a public library (servicing the home schooling community) and an International Baccalaureate school. For another fourteen rural schools, we provided computers and free dial-up service to servers on the New Mexico Highlands University campus.

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

The open science grid

NASA Astrophysics Data System (ADS)

Pordes, Ruth; OSG Consortium; Petravick, Don; Kramer, Bill; Olson, Doug; Livny, Miron; Roy, Alain; Avery, Paul; Blackburn, Kent; Wenaus, Torre; Würthwein, Frank; Foster, Ian; Gardner, Rob; Wilde, Mike; Blatecky, Alan; McGee, John; Quick, Rob

2007-07-01

The Open Science Grid (OSG) provides a distributed facility where the Consortium members provide guaranteed and opportunistic access to shared computing and storage resources. OSG provides support for and evolution of the infrastructure through activities that cover operations, security, software, troubleshooting, addition of new capabilities, and support for existing and engagement with new communities. The OSG SciDAC-2 project provides specific activities to manage and evolve the distributed infrastructure and support it's use. The innovative aspects of the project are the maintenance and performance of a collaborative (shared & common) petascale national facility over tens of autonomous computing sites, for many hundreds of users, transferring terabytes of data a day, executing tens of thousands of jobs a day, and providing robust and usable resources for scientific groups of all types and sizes. More information can be found at the OSG web site: www.opensciencegrid.org.

Science For Sendai - Bridging the gap between research and application

NASA Astrophysics Data System (ADS)

Rees, J.

2015-12-01

Disasters have an enormous cost in lives and livelihoods, but the use of rigorous evidence-based scientific approaches to minimise their impact remains poor. Vast amounts of science which could be readily applied for disaster risk reduction (DRR) is under-utilised, if used at all. Previous international agreements have failed to change this picture, but there is a clear call from the international community that the 2015 Sendai framework should make a difference; it is thus re-appraising how to bridge the chasm that exists between DRR relevant scientists and potential users of their research. There is widespread recognition of the need for risk affected countries and communities to engage in science-based decision-making, but several barriers, such as a lack of infrastructure or necessary skills, institutions, and enforcement of science-based policies require significant attention. There are now incentives for governments to respond: the framework has science embedded throughout and it sets-out national targets against which science uptake can be monitored; similarly, widening access to insurance also demands sound science. Advances such as open-data and models, increasing computational capacity, expanding networks, evolving diverse mobile technologies and the other multiple facets of the big data agenda, also should drive change. So, how does the scientific community need to adapt? Whilst vast amounts of 'DRR-relevant' science has been produced, too little of it can be readily used in DRR science. Much remains highly disciplinary and focused on analysis of limited distributions or single processes with a small number of agents; by contrast real-world DRR problems are commonly complex, with multiple drivers and uncertainties. There is a major need for a trans-disciplinary DRR-focused risk research agenda to evolve. Not only do research funders need to develop and resource risk research, but researchers themselves need to identify that focussing on the bigger risk picture is commonly more important than addressing the traditional disciplinary topics that they have commonly engaged.

EarthRef.org: Exploring aspects of a Cyber Infrastructure in Earth Science and Education

NASA Astrophysics Data System (ADS)

Staudigel, H.; Koppers, A.; Tauxe, L.; Constable, C.; Helly, J.

2004-12-01

EarthRef.org is the common host and (co-) developer of a range of earth science databases and IT resources providing a test bed for a Cyberinfrastructure in Earth Science and Education (CIESE). EarthRef.org data base efforts include in particular the Geochemical Earth Reference Model (GERM), the Magnetics Information Consortium (MagIC), the Educational Resources for Earth Science Education (ERESE) project, the Seamount Catalog, the Mid-Ocean Ridge Catalog, the Radio-Isotope Geochronology (RiG) initiative for CHRONOS, and the Microbial Observatory for Fe oxidizing microbes on Loihi Seamount (FeMO; the most recent development). These diverse databases are developed under a single database umbrella and webserver at the San Diego Supercomputing Center. All the data bases have similar structures, with consistent metadata concepts, a common database layout, and automated upload wizards. Shared resources include supporting databases like an address book, a reference/publication catalog, and a common digital archive making database development and maintenance cost-effective, while guaranteeing interoperability. The EarthRef.org CIESE provides a common umbrella for synthesis information as well as sample-based data, and it bridges the gap between science and science education in middle and high schools, validating the potential for a system wide data infrastructure in a CIESE. EarthRef.org experiences have shown that effective communication with the respective communities is a key part of a successful CIESE facilitating both utility and community buy-in. GERM has been particularly successful at developing a metadata scheme for geochemistry and in the development of a new electronic journal (G-cubed) that has made much progress in data publication and linkages between journals and community data bases. GERM also has worked, through editors and publishers, towards interfacing databases with the publication process, to accomplish a more scholarly and database friendly data publication environment, and to interface with the respective science communities. MagIC has held several workshops that have resulted in an integrated data archival environment using metadata that are interchangeable with the geochemical metadata. MagIC archives a wide array of paleo and rock magnetic directional, intensity and magnetic property data as well as integrating computational tools. ERESE brought together librarians, teachers, and scientists to create an educational environment that supports inquiry driven education and the use of science data. Experiences in EarthRef.org demonstrates the feasibility of an effective, community wide CIESE for data publication, archival and modeling, as well as the outreach to the educational community.

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology.

PubMed

Koch, Julian; Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics.

Climate simulations and services on HPC, Cloud and Grid infrastructures

NASA Astrophysics Data System (ADS)

Cofino, Antonio S.; Blanco, Carlos; Minondo Tshuma, Antonio

2017-04-01

Cloud, Grid and High Performance Computing have changed the accessibility and availability of computing resources for Earth Science research communities, specially for Climate community. These paradigms are modifying the way how climate applications are being executed. By using these technologies the number, variety and complexity of experiments and resources are increasing substantially. But, although computational capacity is increasing, traditional applications and tools used by the community are not good enough to manage this large volume and variety of experiments and computing resources. In this contribution, we evaluate the challenges to run climate simulations and services on Grid, Cloud and HPC infrestructures and how to tackle them. The Grid and Cloud infrastructures provided by EGI's VOs ( esr , earth.vo.ibergrid and fedcloud.egi.eu) will be evaluated, as well as HPC resources from PRACE infrastructure and institutional clusters. To solve those challenges, solutions using DRM4G framework will be shown. DRM4G provides a good framework to manage big volume and variety of computing resources for climate experiments. This work has been supported by the Spanish National R&D Plan under projects WRF4G (CGL2011-28864), INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R) ; the IS-ENES2 project from the 7FP of the European Commission (grant agreement no. 312979); the European Regional Development Fund—ERDF and the Programa de Personal Investigador en Formación Predoctoral from Universidad de Cantabria and Government of Cantabria.

Color engineering in the age of digital convergence

NASA Astrophysics Data System (ADS)

MacDonald, Lindsay W.

1998-09-01

Digital color imaging has developed over the past twenty years from specialized scientific applications into the mainstream of computing. In addition to the phenomenal growth of computer processing power and storage capacity, great advances have been made in the capabilities and cost-effectiveness of color imaging peripherals. The majority of imaging applications, including the graphic arts, video and film have made the transition from analogue to digital production methods. Digital convergence of computing, communications and television now heralds new possibilities for multimedia publishing and mobile lifestyles. Color engineering, the application of color science to the design of imaging products, is an emerging discipline that poses exciting challenges to the international color imaging community for training, research and standards.

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

PubMed

Das, Abhiram; Schneider, Hannah; Burridge, James; Ascanio, Ana Karine Martinez; Wojciechowski, Tobias; Topp, Christopher N; Lynch, Jonathan P; Weitz, Joshua S; Bucksch, Alexander

2015-01-01

Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.

An Overview of New Technologies Driving Innovation in the Airborne Science Community

NASA Technical Reports Server (NTRS)

Fladeland, Matthew M.

2017-01-01

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

A Overview of New Technologies Driving Innovation in the Airborne Science Community

NASA Technical Reports Server (NTRS)

Fladeland, Matthew M.

2017-01-01

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

VERCE: a productive e-Infrastructure and e-Science environment for data-intensive seismology research

NASA Astrophysics Data System (ADS)

Vilotte, Jean-Pierre; Atkinson, Malcolm; Carpené, Michele; Casarotti, Emanuele; Frank, Anton; Igel, Heiner; Rietbrock, Andreas; Schwichtenberg, Horst; Spinuso, Alessandro

2016-04-01

Seismology pioneers global and open-data access -- with internationally approved data, metadata and exchange standards facilitated worldwide by the Federation of Digital Seismic Networks (FDSN) and in Europe the European Integrated Data Archives (EIDA). The growing wealth of data generated by dense observation and monitoring systems and recent advances in seismic wave simulation capabilities induces a change in paradigm. Data-intensive seismology research requires a new holistic approach combining scalable high-performance wave simulation codes and statistical data analysis methods, and integrating distributed data and computing resources. The European E-Infrastructure project "Virtual Earthquake and seismology Research Community e-science environment in Europe" (VERCE) pioneers the federation of autonomous organisations providing data and computing resources, together with a comprehensive, integrated and operational virtual research environment (VRE) and E-infrastructure devoted to the full path of data use in a research-driven context. VERCE delivers to a broad base of seismology researchers in Europe easily used high-performance full waveform simulations and misfit calculations, together with a data-intensive framework for the collaborative development of innovative statistical data analysis methods, all of which were previously only accessible to a small number of well-resourced groups. It balances flexibility with new integrated capabilities to provide a fluent path from research innovation to production. As such, VERCE is a major contribution to the implementation phase of the ``European Plate Observatory System'' (EPOS), the ESFRI initiative of the solid-Earth community. The VRE meets a range of seismic research needs by eliminating chores and technical difficulties to allow users to focus on their research questions. It empowers researchers to harvest the new opportunities provided by well-established and mature high-performance wave simulation codes of the community. It enables active researchers to invent and refine scalable methods for innovative statistical analysis of seismic waveforms in a wide range of application contexts. The VRE paves the way towards a flexible shared framework for seismic waveform inversion, lowering the barriers to uptake for the next generation of researchers. The VRE can be accessed through the science gateway that puts together computational and data-intensive research into the same framework, integrating multiple data sources and services. It provides a context for task-oriented and data-streaming workflows, and maps user actions to the full gamut of the federated platform resources and procurement policies, activating the necessary behind-the-scene automation and transformation. The platform manages and produces domain metadata, coupling them with the provenance information describing the relationships and the dependencies, which characterise the whole workflow process. This dynamic knowledge base, can be explored for validation purposes via a graphical interface and a web API. Moreover, it fosters the assisted selection and re-use of the data within each phase of the scientific analysis. These phases can be identified as Simulation, Data Access, Preprocessing, Misfit and data processing, and are presented to the users of the gateway as dedicated and interactive workspaces. By enabling researchers to share results and provenance information, VERCE steers open-science behaviour, allowing researchers to discover and build on prior work and thereby to progress faster. A key asset is the agile strategy that VERCE deployed in a multi-organisational context, engaging seismologists, data scientists, ICT researchers, HPC and data resource providers, system administrators into short-lived tasks each with a goal that is a seismology priority, and intimately coupling research thinking with technical innovation. This changes the focus from HPC production environments and community data services to user-focused scenario, avoiding wasteful bouts of technology centricity where technologists collect requirements and develop a system that is not used because the ideas of the planned users have moved on. As such the technologies and concepts developed in VERCE are relevant to many other disciplines in computational and data driven Earth Sciences and can provide the key technologies for a European wide computational and data intensive framework in Earth Sciences.

BioSharing: curated and crowd-sourced metadata standards, databases and data policies in the life sciences.

PubMed

McQuilton, Peter; Gonzalez-Beltran, Alejandra; Rocca-Serra, Philippe; Thurston, Milo; Lister, Allyson; Maguire, Eamonn; Sansone, Susanna-Assunta

2016-01-01

BioSharing (http://www.biosharing.org) is a manually curated, searchable portal of three linked registries. These resources cover standards (terminologies, formats and models, and reporting guidelines), databases, and data policies in the life sciences, broadly encompassing the biological, environmental and biomedical sciences. Launched in 2011 and built by the same core team as the successful MIBBI portal, BioSharing harnesses community curation to collate and cross-reference resources across the life sciences from around the world. BioSharing makes these resources findable and accessible (the core of the FAIR principle). Every record is designed to be interlinked, providing a detailed description not only on the resource itself, but also on its relations with other life science infrastructures. Serving a variety of stakeholders, BioSharing cultivates a growing community, to which it offers diverse benefits. It is a resource for funding bodies and journal publishers to navigate the metadata landscape of the biological sciences; an educational resource for librarians and information advisors; a publicising platform for standard and database developers/curators; and a research tool for bench and computer scientists to plan their work. BioSharing is working with an increasing number of journals and other registries, for example linking standards and databases to training material and tools. Driven by an international Advisory Board, the BioSharing user-base has grown by over 40% (by unique IP address), in the last year thanks to successful engagement with researchers, publishers, librarians, developers and other stakeholders via several routes, including a joint RDA/Force11 working group and a collaboration with the International Society for Biocuration. In this article, we describe BioSharing, with a particular focus on community-led curation.Database URL: https://www.biosharing.org. © The Author(s) 2016. Published by Oxford University Press.

The Pilot Land Data System: Report of the Program Planning Workshops

NASA Technical Reports Server (NTRS)

1984-01-01

An advisory report to be used by NASA in developing a program plan for a Pilot Land Data System (PLDS) was developed. The purpose of the PLDS is to improve the ability of NASA and NASA sponsored researchers to conduct land-related research. The goal of the planning workshops was to provide and coordinate planning and concept development between the land related science and computer science disciplines, to discuss the architecture of the PLDs, requirements for information science technology, and system evaluation. The findings and recommendations of the Working Group are presented. The pilot program establishes a limited scale distributed information system to explore scientific, technical, and management approaches to satisfying the needs of the land science community. The PLDS paves the way for a land data system to improve data access, processing, transfer, and analysis, which land sciences information synthesis occurs on a scale not previously permitted because of limits to data assembly and access.

Decision-support systems for natural-hazards and land-management issues

USGS Publications Warehouse

Dinitz, Laura; Forney, William; Byrd, Kristin

2012-01-01

Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

Know Your Discipline: Teaching the Philosophy of Computer Science

ERIC Educational Resources Information Center

Tedre, Matti

2007-01-01

The diversity and interdisciplinarity of computer science and the multiplicity of its uses in other sciences make it hard to define computer science and to prescribe how computer science should be carried out. The diversity of computer science also causes friction between computer scientists from different branches. Computer science curricula, as…

Toward benchmarking in catalysis science: Best practices, challenges, and opportunities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bligaard, Thomas; Bullock, R. Morris; Campbell, Charles T.

Benchmarking is a community-based and (preferably) community-driven activity involving consensus-based decisions on how to make reproducible, fair, and relevant assessments. In catalysis science, important catalyst performance metrics include activity, selectivity, and the deactivation profile, which enable comparisons between new and standard catalysts. Benchmarking also requires careful documentation, archiving, and sharing of methods and measurements, to ensure that the full value of research data can be realized. Beyond these goals, benchmarking presents unique opportunities to advance and accelerate understanding of complex reaction systems by combining and comparing experimental information from multiple, in situ and operando techniques with theoretical insights derived frommore » calculations characterizing model systems. This Perspective describes the origins and uses of benchmarking and its applications in computational catalysis, heterogeneous catalysis, molecular catalysis, and electrocatalysis. As a result, it also discusses opportunities and challenges for future developments in these fields.« less

Leveraging the national cyberinfrastructure for biomedical research.

PubMed

LeDuc, Richard; Vaughn, Matthew; Fonner, John M; Sullivan, Michael; Williams, James G; Blood, Philip D; Taylor, James; Barnett, William

2014-01-01

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the 'Big Data' challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community.

Leveraging the national cyberinfrastructure for biomedical research

PubMed Central

LeDuc, Richard; Vaughn, Matthew; Fonner, John M; Sullivan, Michael; Williams, James G; Blood, Philip D; Taylor, James; Barnett, William

2014-01-01

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the ‘Big Data’ challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community. PMID:23964072

Toward benchmarking in catalysis science: Best practices, challenges, and opportunities

DOE PAGES

Bligaard, Thomas; Bullock, R. Morris; Campbell, Charles T.; ...

2016-03-07

Benchmarking is a community-based and (preferably) community-driven activity involving consensus-based decisions on how to make reproducible, fair, and relevant assessments. In catalysis science, important catalyst performance metrics include activity, selectivity, and the deactivation profile, which enable comparisons between new and standard catalysts. Benchmarking also requires careful documentation, archiving, and sharing of methods and measurements, to ensure that the full value of research data can be realized. Beyond these goals, benchmarking presents unique opportunities to advance and accelerate understanding of complex reaction systems by combining and comparing experimental information from multiple, in situ and operando techniques with theoretical insights derived frommore » calculations characterizing model systems. This Perspective describes the origins and uses of benchmarking and its applications in computational catalysis, heterogeneous catalysis, molecular catalysis, and electrocatalysis. As a result, it also discusses opportunities and challenges for future developments in these fields.« less

Can the behavioral sciences self-correct? A social epistemic study.

PubMed

Romero, Felipe

2016-12-01

Advocates of the self-corrective thesis argue that scientific method will refute false theories and find closer approximations to the truth in the long run. I discuss a contemporary interpretation of this thesis in terms of frequentist statistics in the context of the behavioral sciences. First, I identify experimental replications and systematic aggregation of evidence (meta-analysis) as the self-corrective mechanism. Then, I present a computer simulation study of scientific communities that implement this mechanism to argue that frequentist statistics may converge upon a correct estimate or not depending on the social structure of the community that uses it. Based on this study, I argue that methodological explanations of the "replicability crisis" in psychology are limited and propose an alternative explanation in terms of biases. Finally, I conclude suggesting that scientific self-correction should be understood as an interaction effect between inference methods and social structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

PubMed

Larsen, Peter; Hamada, Yuki; Gilbert, Jack

2012-07-31

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.

Simulating Earthquakes for Science and Society: Earthquake Visualizations Ideal for use in Science Communication and Education

NASA Astrophysics Data System (ADS)

de Groot, R.

2008-12-01

The Southern California Earthquake Center (SCEC) has been developing groundbreaking computer modeling capabilities for studying earthquakes. These visualizations were initially shared within the scientific community but have recently gained visibility via television news coverage in Southern California. Computers have opened up a whole new world for scientists working with large data sets, and students can benefit from the same opportunities (Libarkin & Brick, 2002). For example, The Great Southern California ShakeOut was based on a potential magnitude 7.8 earthquake on the southern San Andreas fault. The visualization created for the ShakeOut was a key scientific and communication tool for the earthquake drill. This presentation will also feature SCEC Virtual Display of Objects visualization software developed by SCEC Undergraduate Studies in Earthquake Information Technology interns. According to Gordin and Pea (1995), theoretically visualization should make science accessible, provide means for authentic inquiry, and lay the groundwork to understand and critique scientific issues. This presentation will discuss how the new SCEC visualizations and other earthquake imagery achieve these results, how they fit within the context of major themes and study areas in science communication, and how the efficacy of these tools can be improved.

A High School Level Course On Robot Design And Construction

NASA Astrophysics Data System (ADS)

Sadler, Paul M.; Crandall, Jack L.

1984-02-01

The Robotics Design and Construction Class at Sehome High School was developed to offer gifted and/or highly motivated students an in-depth introduction to a modern engineering topic. The course includes instruction in basic electronics, digital and radio electronics, construction skills, robotics literacy, construction of the HERO 1 Heathkit Robot, computer/ robot programming, and voice synthesis. A key element which leads to the success of the course is the involvement of various community assets including manpower and financial assistance. The instructors included a physics/electronics teacher, a computer science teacher, two retired engineers, and an electronics technician.

Separating Added Value from Hype: Some Experiences and Prognostications

NASA Astrophysics Data System (ADS)

Reed, Dan

2004-03-01

These are exciting times for the interplay of science and computing technology. As new data archives, instruments and computing facilities are connected nationally and internationally, a new model of distributed scientific collaboration is emerging. However, any new technology brings both opportunities and challenges -- Grids are no exception. In this talk, we will discuss some of the experiences deploying Grid software in production environments, illustrated with experiences from the NSF PACI Alliance, the NSF Extensible Terascale Facility (ETF) and other Grid projects. From these experiences, we derive some guidelines for deployment and some suggestions for community engagement, software development and infrastructure

PREFACE: International Conference on Applied Sciences 2015 (ICAS2015)

NASA Astrophysics Data System (ADS)

Lemle, Ludovic Dan; Jiang, Yiwen

2016-02-01

The International Conference on Applied Sciences ICAS2015 took place in Wuhan, China on June 3-5, 2015 at the Military Economics Academy of Wuhan. The conference is regularly organized, alternatively in Romania and in P.R. China, by Politehnica University of Timişoara, Romania, and Military Economics Academy of Wuhan, P.R. China, with the joint aims to serve as a platform for exchange of information between various areas of applied sciences, and to promote the communication between the scientists of different nations, countries and continents. The topics of the conference cover a comprehensive spectrum of issues from: >Economical Sciences and Defense: Management Sciences, Business Management, Financial Management, Logistics, Human Resources, Crisis Management, Risk Management, Quality Control, Analysis and Prediction, Government Expenditure, Computational Methods in Economics, Military Sciences, National Security, and others... >Fundamental Sciences and Engineering: Interdisciplinary applications of physics, Numerical approximation and analysis, Computational Methods in Engineering, Metallic Materials, Composite Materials, Metal Alloys, Metallurgy, Heat Transfer, Mechanical Engineering, Mechatronics, Reliability, Electrical Engineering, Circuits and Systems, Signal Processing, Software Engineering, Data Bases, Modeling and Simulation, and others... The conference gathered qualified researchers whose expertise can be used to develop new engineering knowledge that has applicability potential in Engineering, Economics, Defense, etc. The number of participants was 120 from 11 countries (China, Romania, Taiwan, Korea, Denmark, France, Italy, Spain, USA, Jamaica, and Bosnia and Herzegovina). During the three days of the conference four invited and 67 oral talks were delivered. Based on the work presented at the conference, 38 selected papers have been included in this volume of IOP Conference Series: Materials Science and Engineering. These papers present new research in the various fields of Materials Engineering, Mechanical Engineering, Computers Engineering, and Electrical Engineering. It's our great pleasure to present this volume of IOP Conference Series: Materials Science and Engineering to the scientific community to promote further research in these areas. We sincerely hope that the papers published in this volume will contribute to the advancement of knowledge in the respective fields.

PREFACE: International Conference on Computing in High Energy and Nuclear Physics (CHEP'07)

NASA Astrophysics Data System (ADS)

Sobie, Randall; Tafirout, Reda; Thomson, Jana

2007-07-01

The 2007 International Conference on Computing in High Energy and Nuclear Physics (CHEP) was held on 2-7 September 2007 in Victoria, British Columbia, Canada. CHEP is a major series of international conferences for physicists and computing professionals from the High Energy and Nuclear Physics community, Computer Science and Information Technology. The CHEP conference provides an international forum to exchange information on computing experience and needs for the community, and to review recent, ongoing, and future activities. The CHEP'07 conference had close to 500 attendees with a program that included plenary sessions of invited oral presentations, a number of parallel sessions comprising oral and poster presentations, and an industrial exhibition. Conference tracks covered topics in Online Computing, Event Processing, Software Components, Tools and Databases, Software Tools and Information Systems, Computing Facilities, Production Grids and Networking, Grid Middleware and Tools, Distributed Data Analysis and Information Management and Collaborative Tools. The conference included a successful whale-watching excursion involving over 200 participants and a banquet at the Royal British Columbia Museum. The next CHEP conference will be held in Prague in March 2009. We would like thank the sponsors of the conference and the staff at the TRIUMF Laboratory and the University of Victoria who made the CHEP'07 a success. Randall Sobie and Reda Tafirout CHEP'07 Conference Chairs

TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets

USGS Publications Warehouse

Hu, Hao; Hong, Xingchen; Terstriep, Jeff; Liu, Yan; Finn, Michael P.; Rush, Johnathan; Wendel, Jeffrey; Wang, Shaowen

2016-01-01

Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.

Science and Community Engagement: Connecting Science Students with the Community

ERIC Educational Resources Information Center

Lancor, Rachael; Schiebel, Amy

2018-01-01

In this article we describe a course on science outreach that was developed as part of our college's goal that all students participate in a meaningful community engagement experience. The Science & Community Engagement course provides a way for students with science or science-related majors to learn how to effectively communicate scientific…

Community centrality and social science research.

PubMed

Allman, Dan

2015-12-01

Community centrality is a growing requirement of social science. The field's research practices are increasingly expected to conform to prescribed relationships with the people studied. Expectations about community centrality influence scholarly activities. These expectations can pressure social scientists to adhere to models of community involvement that are immediate and that include community-based co-investigators, advisory boards, and liaisons. In this context, disregarding community centrality can be interpreted as failure. This paper considers evolving norms about the centrality of community in social science. It problematises community inclusion and discusses concerns about the impact of community centrality on incremental theory development, academic integrity, freedom of speech, and the value of liberal versus communitarian knowledge. Through the application of a constructivist approach, this paper argues that social science in which community is omitted or on the periphery is not failed science, because not all social science requires a community base to make a genuine and valuable contribution. The utility of community centrality is not necessarily universal across all social science pursuits. The practices of knowing within social science disciplines may be difficult to transfer to a community. These practices of knowing require degrees of specialisation and interest that not all communities may want or have.

Community centrality and social science research

PubMed Central

Allman, Dan

2015-01-01

Community centrality is a growing requirement of social science. The field's research practices are increasingly expected to conform to prescribed relationships with the people studied. Expectations about community centrality influence scholarly activities. These expectations can pressure social scientists to adhere to models of community involvement that are immediate and that include community-based co-investigators, advisory boards, and liaisons. In this context, disregarding community centrality can be interpreted as failure. This paper considers evolving norms about the centrality of community in social science. It problematises community inclusion and discusses concerns about the impact of community centrality on incremental theory development, academic integrity, freedom of speech, and the value of liberal versus communitarian knowledge. Through the application of a constructivist approach, this paper argues that social science in which community is omitted or on the periphery is not failed science, because not all social science requires a community base to make a genuine and valuable contribution. The utility of community centrality is not necessarily universal across all social science pursuits. The practices of knowing within social science disciplines may be difficult to transfer to a community. These practices of knowing require degrees of specialisation and interest that not all communities may want or have. PMID:26440071

The Canadian Astronomy Data Centre

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Schade, D.; Astronomy Data Centre, Canadian

2011-01-01

The Canadian Astronomy Data Centre (CADC) is the world's largest astronomical data center, holding over 0.5 Petabytes of information, and serving nearly 3000 astronomers worldwide. Its current data collections include BLAST, CFHT, CGPS, FUSE, Gemini, HST, JCMT, MACHO, MOST, and numerous other archives and services. It provides extensive data archiving, curation, and processing expertise, via projects such as MegaPipe, and enables substantial day-to-day collaboration between resident astronomers and computer specialists. It is a stable, powerful, persistent, and properly supported environment for the storage and processing of large volumes of data, a condition that is now absolutely vital for their science potential to be exploited by the community. Through initiatives such as the Common Archive Observation Model (CAOM), the Canadian Virtual Observatory (CVO), and the Canadian Advanced Network for Astronomical Research (CANFAR), the CADC is at the global forefront of advancing astronomical research through improved data services. The CAOM aims to provide homogeneous data access, and hence viable interoperability between a potentially unlimited number of different data collections, at many wavelengths. It is active in the definition of numerous emerging standards within the International Virtual Observatory, and several datasets are already available. The CANFAR project is an initiative to make cloud computing for storage and data-intensive processing available to the community. It does this via a Virtual Machine environment that is equivalent to managing a local desktop. Several groups are already processing science data. CADC is also at the forefront of advanced astronomical data analysis, driven by the science requirements of astronomers both locally and further afield. The emergence of 'Astroinformatics' promises to provide not only utility items like object classifications, but to directly enable new science by accessing previously undiscovered or intractable information. We are currently in the early stages of implementing Astroinformatics tools, such as machine learning, on CANFAR.

Apache Open Climate Workbench: Building Open Source Climate Science Tools and Community at the Apache Software Foundation

NASA Astrophysics Data System (ADS)

Joyce, M.; Ramirez, P.; Boustani, M.; Mattmann, C. A.; Khudikyan, S.; McGibbney, L. J.; Whitehall, K. D.

2014-12-01

Apache Open Climate Workbench (OCW; https://climate.apache.org/) is a Top-Level Project at the Apache Software Foundation that aims to provide a suite of tools for performing climate science evaluations using model outputs from a multitude of different sources (ESGF, CORDEX, U.S. NCA, NARCCAP) with remote sensing data from NASA, NOAA, and other agencies. Apache OCW is the second NASA project to become a Top-Level Project at the Apache Software Foundation. It grew out of the Jet Propulsion Laboratory's (JPL) Regional Climate Model Evaluation System (RCMES) project, a collaboration between JPL and the University of California, Los Angeles' Joint Institute for Regional Earth System Science and Engineering (JIFRESSE). Apache OCW provides scientists and developers with tools for data manipulation, metrics for dataset comparisons, and a visualization suite. In addition to a powerful low-level API, Apache OCW also supports a web application for quick, browser-controlled evaluations, a command line application for local evaluations, and a virtual machine for isolated experimentation with minimal setup. This talk will look at the difficulties and successes of moving a closed community research project out into the wild world of open source. We'll explore the growing pains Apache OCW went through to become a Top-Level Project at the Apache Software Foundation as well as the benefits gained by opening up development to the broader climate and computer science communities.

The Symbiotic Relationship between Scientific Workflow and Provenance (Invited)

NASA Astrophysics Data System (ADS)

Stephan, E.

2010-12-01

The purpose of this presentation is to describe the symbiotic nature of scientific workflows and provenance. We will also discuss the current trends and real world challenges facing these two distinct research areas. Although motivated differently, the needs of the international science communities are the glue that binds this relationship together. Understanding and articulating the science drivers to these communities is paramount as these technologies evolve and mature. Originally conceived for managing business processes, workflows are now becoming invaluable assets in both computational and experimental sciences. These reconfigurable, automated systems provide essential technology to perform complex analyses by coupling together geographically distributed disparate data sources and applications. As a result, workflows are capable of higher throughput in a shorter amount of time than performing the steps manually. Today many different workflow products exist; these could include Kepler and Taverna or similar products like MeDICI, developed at PNNL, that are standardized on the Business Process Execution Language (BPEL). Provenance, originating from the French term Provenir “to come from”, is used to describe the curation process of artwork as art is passed from owner to owner. The concept of provenance was adopted by digital libraries as a means to track the lineage of documents while standards such as the DublinCore began to emerge. In recent years the systems science community has increasingly expressed the need to expand the concept of provenance to formally articulate the history of scientific data. Communities such as the International Provenance and Annotation Workshop (IPAW) have formalized a provenance data model. The Open Provenance Model, and the W3C is hosting a provenance incubator group featuring the Proof Markup Language. Although both workflows and provenance have risen from different communities and operate independently, their mutual success is tied together, forming a symbiotic relationship where research and development advances in one effort can provide tremendous benefits to the other. For example, automating provenance extraction within scientific applications is still a relatively new concept; the workflow engine provides the framework to capture application specific operations, inputs, and resulting data. It provides a description of the process history and data flow by wrapping workflow components around the applications and data sources. On the other hand, a lack of cooperation between workflows and provenance can inhibit usefulness of both to science. Blindly tracking the execution history without having a true understanding of what kinds of questions end users may have makes the provenance indecipherable to the target users. Over the past nine years PNNL has been actively involved in provenance research in support of computational chemistry, molecular dynamics, biology, hydrology, and climate. PNNL has also been actively involved in efforts by the international community to develop open standards for provenance and the development of architectures to support provenance capture, storage, and querying. This presentation will provide real world use cases of how provenance and workflow can be leveraged and implemented to meet different needs and the challenges that lie ahead.

A JavaScript API for the Ice Sheet System Model (ISSM) 4.11: towards an online interactive model for the cryosphere community

NASA Astrophysics Data System (ADS)

Larour, Eric; Cheng, Daniel; Perez, Gilberto; Quinn, Justin; Morlighem, Mathieu; Duong, Bao; Nguyen, Lan; Petrie, Kit; Harounian, Silva; Halkides, Daria; Hayes, Wayne

2017-12-01

Earth system models (ESMs) are becoming increasingly complex, requiring extensive knowledge and experience to deploy and use in an efficient manner. They run on high-performance architectures that are significantly different from the everyday environments that scientists use to pre- and post-process results (i.e., MATLAB, Python). This results in models that are hard to use for non-specialists and are increasingly specific in their application. It also makes them relatively inaccessible to the wider science community, not to mention to the general public. Here, we present a new software/model paradigm that attempts to bridge the gap between the science community and the complexity of ESMs by developing a new JavaScript application program interface (API) for the Ice Sheet System Model (ISSM). The aforementioned API allows cryosphere scientists to run ISSM on the client side of a web page within the JavaScript environment. When combined with a web server running ISSM (using a Python API), it enables the serving of ISSM computations in an easy and straightforward way. The deep integration and similarities between all the APIs in ISSM (MATLAB, Python, and now JavaScript) significantly shortens and simplifies the turnaround of state-of-the-art science runs and their use by the larger community. We demonstrate our approach via a new Virtual Earth System Laboratory (VESL) website (http://vesl.jpl.nasa.gov, VESL(2017)).

Development and Performance of the Modularized, High-performance Computing and Hybrid-architecture Capable GEOS-Chem Chemical Transport Model

NASA Astrophysics Data System (ADS)

Long, M. S.; Yantosca, R.; Nielsen, J.; Linford, J. C.; Keller, C. A.; Payer Sulprizio, M.; Jacob, D. J.

2014-12-01

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been reengineered to serve as a platform for a range of computational atmospheric chemistry science foci and applications. Development included modularization for coupling to general circulation and Earth system models (ESMs) and the adoption of co-processor capable atmospheric chemistry solvers. This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of GEOS-Chem scientific code to permit seamless transition from the GEOS-Chem stand-alone serial CTM to deployment as a coupled ESM module. In this manner, the continual stream of updates contributed by the CTM user community is automatically available for broader applications, which remain state-of-science and directly referenceable to the latest version of the standard GEOS-Chem CTM. These developments are now available as part of the standard version of the GEOS-Chem CTM. The system has been implemented as an atmospheric chemistry module within the NASA GEOS-5 ESM. The coupled GEOS-5/GEOS-Chem system was tested for weak and strong scalability and performance with a tropospheric oxidant-aerosol simulation. Results confirm that the GEOS-Chem chemical operator scales efficiently for any number of processes. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemical operator means that the relative cost goes down with increasing number of processes, making fine-scale resolution simulations possible.

EVEREST: a virtual research environment for the Earth Sciences

NASA Astrophysics Data System (ADS)

Glaves, H. M.; Marelli, F.; Albani, M.

2015-12-01

There is an increasing requirement for researchers to work collaboratively using common resources whilst being geographically dispersed. By creating a virtual research environment (VRE) using a service oriented architecture (SOA) tailored to the needs of Earth Science (ES) communities, the EVEREST project will provide a range of both generic and domain specific data management services to support a dynamic approach to collaborative research. EVER-EST will provide the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. Data providers will be also able to monitor user experiences and collect feedback through the VRE, improving their capacity to adapt to the changing requirements of their end-users. The EVER-EST e-infrastructure will be validated by four virtual research communities (VRC) covering different multidisciplinary ES domains: including ocean monitoring, selected natural hazards (flooding, ground instability and extreme weather events), land monitoring and risk management (volcanoes and seismicity). Each of the VRC represents a different collaborative use case for the VRE according to its own specific requirements for data, software, best practice and community engagement. The diverse use cases will demonstrate how the VRE can be used for a range of activities from straight forward data/software sharing to investigating ways to improve cooperative working. Development of the EVEREST VRE will leverage on the results of several previous projects which have produced state-of-the-art technologies for scientific data management and curation as well those initiatives which have developed models, techniques and tools for the preservation of scientific methods and their implementation in computational forms such as scientific workflows.

ESIP Lab: Supporting Development of Earth Sciences Cyberinfrastructure through Innovation Commons

NASA Astrophysics Data System (ADS)

Burgess, A. B.; Robinson, E.

2017-12-01

The Earth Science Information Partners (ESIP) is an open, networked community that brings together science, data and information technology practitioners from across sectors. Participation in ESIP is beneficial because it provides an intellectual commons to expose, gather and enhance in-house capabilities in support of an organization's own mandate. Recently, ESIP has begun to explore piloting activities that have worked in the U.S. in other countries as a way to facilitate international collaboration and cross-pollination. The newly formed ESIP Lab realizes the commons concept by providing a virtual place to come up with with new solutions through facilitated ideation, take that idea to a low stakes development environment and potentially fail, but if successful, expose developing technology to domain experts through a technology evaluation process. The Lab does this by supporting and funding solution-oriented projects that have discrete development periods and associated budgets across organizations and agencies. In addition, the Lab provides access to AWS cloud computing resources, travel support, virtual and in-person collaborative platform for distributed groups and exposure to the ESIP community as an expert pool. This cycle of ideation to incubation to evaluation and ultimately adoption or infusion of Earth sciences cyberinfrastructure empowers the scientific community and has spawned a variety of developments like community-led ontology portals, ideas for W3C prov standard improvement and an evaluation framework that pushes technology forward and aides in infusion. The Lab is one of these concepts that could be implemented in other countries and the outputs of the Lab would be shared as a commons and available across traditional borders. This presentation will share the methods and the outcomes of the Lab and seed ideas for adoption internationally.

Geoinformatics in the public service: building a cyberinfrastructure across the geological surveys

USGS Publications Warehouse

Allison, M. Lee; Gundersen, Linda C.; Richard, Stephen M.; Keller, G. Randy; Baru, Chaitanya

2011-01-01

Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.

Will our Current Data Rescue, Curation and Preservation Practices bring us out of the Digital Dark Ages and into the Renaissance of Multi-Source Science? (Invited)

NASA Astrophysics Data System (ADS)

Wyborn, L. A.

2013-12-01

The emergence of the fourth paradigm of data intensive science in 2007 showed great promise: it offered a new fundamental methodology in scientific exploration in which researchers would be able to harness the huge increase in data volumes coming from new and more powerful instruments that were collecting data at unprecedented rates and at ever increasing resolutions. Given the potential this new methodology offered, decadal challenges were issued to the Earth and Space Science community to come together and work on problems such as impacts of climate change; sustainably exploiting scarce water, mineral and petroleum resources; and protecting our communities through better prediction of the behaviour of natural hazards. Such challenges require the capability to integrate heterogeneous data sets, from multiple sources, across multiple domains and at low transactional cost. To help realise these visions significant investments were made globally in cyberinfrastructures (computer centres, research clouds, data stores, high speed networks, etc.). Combined, these infrastructures are now capable of analysing petabyte size chunks of data, and the climate community is close to operating at exascale. But have we actually realised the vision of data intensive science? The simple reality is that data intensive science requires the capability to find and analyse large volumes of data in real time via machine to machine interactions. It is not necessarily just about ';Big Data' sets collected from remote instruments such as satellites or sensor networks. ';Long Tail' data sets, traditionally the output of small science campaigns, are vital to calibrating large data sets and need to be stored so that they can be reused and repurposed in ways beyond what the original collector of the data intended they be used for. Particularly for meaningful time series analysis in environmental sciences, there is the additional challenge to store and manage data through decades of multiple evolutions of both hardware and software. The move to data intensive science has driven the realisation that we need to put more effort and resources into rescuing, curating and preserving data and properly preserved data sets are now being use to resolve the real world issues of today. However, as the capacity of computational systems increases relentlessly we need to question if our current efforts in data curation and preservation will scale to these ever growing systems. For Earth and Space Sciences to come out of the digital dark ages and into the renaissance of multi-source science, it is time to take stock and question our current data rescue, curation and preservation initiatives. Will the data store I am using be around in 50 years' time? What measures is this data store taking to avoid bit-rot and/or deal with software and hardware obsolescence. Is my data self-describing? Have I paid enough attention to cross domain data standards so my data can be reused and repurposed for the current decadal challenges? More importantly, as the capacity of computational systems scale beyond exascale to zettascale and yottascale, will my data sets that I have rescued, curated and preserved in my lifetime, no matter whether they are small or large, be able to contribute to addressing the decadal challenges that are as yet undefined.

Overview of the SAMSI year-long program on Statistical, Mathematical and Computational Methods for Astronomy

NASA Astrophysics Data System (ADS)

Jogesh Babu, G.

2017-01-01

A year-long research (Aug 2016- May 2017) program on `Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ is well under way at Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation research institute in Research Triangle Park, NC. This program has brought together astronomers, computer scientists, applied mathematicians and statisticians. The main aims of this program are: to foster cross-disciplinary activities; to accelerate the adoption of modern statistical and mathematical tools into modern astronomy; and to develop new tools needed for important astronomical research problems. The program provides multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI. The main program is organized around five working groups:i) Uncertainty Quantification and Astrophysical Emulationii) Synoptic Time Domain Surveysiii) Multivariate and Irregularly Sampled Time Seriesiv) Astrophysical Populationsv) Statistics, computation, and modeling in cosmology.A brief description of each of the work under way by these groups will be given. Overlaps among various working groups will also be highlighted. How the wider astronomy community can both participate and benefit from the activities, will be briefly mentioned.

Accelerating scientific discovery : 2007 annual report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckman, P.; Dave, P.; Drugan, C.

2008-11-14

As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis ofmore » Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide guidance for applications that are transitioning to petascale as well as to produce software that facilitates their development, such as the MPICH library, which provides a portable and efficient implementation of the MPI standard--the prevalent programming model for large-scale scientific applications--and the PETSc toolkit that provides a programming paradigm that eases the development of many scientific applications on high-end computers.« less

RIACS

NASA Technical Reports Server (NTRS)

Moore, Robert C.

1998-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: (1) Automated Reasoning. (2) Human-Centered Computing. and (3) High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

NASA's Earth Observing System Data and Information System - Many Mechanisms for On-Going Evolution

NASA Astrophysics Data System (ADS)

Ramapriyan, H. K.

2012-12-01

NASA's Earth Observing System Data and Information System has been serving a broad user community since August 1994. As a long-lived multi-mission system serving multiple scientific disciplines and a diverse user community, EOSDIS has been evolving continuously. It has had and continues to have many forms of community input to help with this evolution. Early in its history, it had inputs from the EOSDIS Advisory Panel, benefited from the reviews by various external committees and evolved into the present distributed architecture with discipline-based Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems and a cross-DAAC search and data access capability. EOSDIS evolution has been helped by advances in computer technology, moving from an initially planned supercomputing environment to SGI workstations to Linux Clusters for computation and from near-line archives of robotic silos with tape cassettes to RAID-disk-based on-line archives for storage. The network capacities have increased steadily over the years making delivery of data on media almost obsolete. The advances in information systems technologies have been having an even greater impact on the evolution of EOSDIS. In the early days, the advent of the World Wide Web came as a game-changer in the operation of EOSDIS. The metadata model developed for the EOSDIS Core System for representing metadata from EOS standard data products has had an influence on the Federal Geographic Data Committee's metadata content standard and the ISO metadata standards. The influence works both ways. As ISO 19115 metadata standard has developed in recent years, EOSDIS is reviewing its metadata to ensure compliance with the standard. Improvements have been made in the cross-DAAC search and access of data using the centralized metadata clearing house (EOS Clearing House - ECHO) and the client Reverb. Given the diversity of the Earth science disciplines served by the DAACs, the DAACs have developed a number of software tools tailored to their respective user communities. Web services play an important part in improved access to data products including some basic analysis and visualization capabilities. A coherent view into all capabilities available from EOSDIS is evolving through the "Coherent Web" effort. Data are being made available in near real-time for scientific research as well as time-critical applications. On-going community inputs for infusion for maintaining vitality of EOSDIS come from technology developments by NASA-sponsored community data system programs - Advancing Collaborative Connections for Earth System Science (ACCESS), Making Earth System Data Records for Use in Research Environments (MEaSUREs) and Applied Information System Technology (AIST), as well as participation in Earth Science Data System Working Groups, the Earth Science Information Partners Federation and other interagency/international activities. An important source of community needs is the annual American Customer Satisfaction Index survey of EOSDIS users. Some of the key areas in which improvements are required and incremental progress is being made are: ease of discovery and access; cross-organizational interoperability; data inter-use; ease of collaboration; ease of citation of datasets; preservation of provenance and context and making them conveniently available to users.

Data-driven Science in Geochemistry & Petrology: Vision & Reality

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Ghiorso, M. S.; Spear, F. S.

2013-12-01

Science in many fields is increasingly ';data-driven'. Though referred to as a ';new' Fourth Paradigm (Hey, 2009), data-driven science is not new, and examples are cited in the Geochemical Society's data policy, including the compilation of Dziewonski & Anderson (1981) that led to PREM, and Zindler & Hart (1986), who compiled mantle isotope data to present for the first time a comprehensive view of the Earth's mantle. Today, rapidly growing data volumes, ubiquity of data access, and new computational and information management technologies enable data-driven science at a radically advanced scale of speed, extent, flexibility, and inclusiveness, with the ability to seamlessly synthesize observations, experiments, theory, and computation, and to statistically mine data across disciplines, leading to more comprehensive, well informed, and high impact scientific advances. Are geochemists, petrologists, and volcanologists ready to participate in this revolution of the scientific process? In the past year, researchers from the VGP community and related disciplines have come together at several cyberinfrastructure related workshops, in part prompted by the EarthCube initiative of the US NSF, to evaluate the status of cyberinfrastructure in their field, to put forth key scientific challenges, and identify primary data and software needs to address these. Science scenarios developed by workshop participants that range from non-equilibrium experiments focusing on mass transport, chemical reactions, and phase transformations (J. Hammer) to defining the abundance of elements and isotopes in every voxel in the Earth (W. McDonough), demonstrate the potential of cyberinfrastructure enabled science, and define the vision of how data access, visualization, analysis, computation, and cross-domain interoperability can and should support future research in VGP. The primary obstacle for data-driven science in VGP remains the dearth of accessible, integrated data from lab and sensor measurements, experiments, and models, both from past and from present studies, and their poor discoverability, interoperability, and standardization. Other deficiencies include the lack of widespread sample curation and online sample catalogs, and broad community support and enforcement of open data sharing policies and a strategy for sustained funding and operation of the cyberinfrastructure. In order to achieve true data-driven science in geochemistry and petrology, one of the primary requirements is to change the way data and models are managed and shared to dramatically improve their access and re-usability. Adoption of new data publication practices, new ways of citing data that ensure attribution and credit to authors, tools that help investigators to seamlessly manage their data throughout the data life cycle, from the point of acquisition to upload to repositories, and population of databases with historical data are among the most urgent needs. The community, especially early career scientists, must work together to produce the cultural shift within the discipline toward sharing of data and knowledge, virtual collaboration, and social networking. Dziewonski, A M, & Anderson, D L: Physics of the Earth and Planet Interiors 25 (4), 297 (1981) Hey, T, Tansley, S, Tolle, K (Eds.): Redmond, VA: Microsoft Research (2009) Zindler, A, & Hart, S R: Ann. Rev. Earth Plan. Sci. 14, 493 (1986)

GMRI.org | Science. Education. Community.

Science.gov Websites

Coastal Communities Science Education Fisheries Convening Events Calendar Event Series Sustainable Seafood Literacy Supporting Sustainable Seafood Strengthening Coastal Communities Our Work Science Education | Cultivating Science Literacy | Supporting Sustainable Seafood | Strengthening Coastal Communities GMRI's

MAXHELP: Needs Assessment in the Montgomery Community

DTIC Science & Technology

1984-04-01

become motivated for satisfactory accomplishments. 12 . Orientation flights. Simplified computer simulation games in math /science. Guest attendance of...NAME AND ADDRESS 12 . REPORT DATE APRIL 1984 ACSC/EDCC, MAXWELL AFB, AL 36112 13. NUMBER OF PAGES 14. MONITORING AGENCY NAME A AOORESS(’II dllerenl...and Finance specialist course where he was a distinguished graduate. In 1968 he was recalled to active duty and was assigned to Sewart Air Force Base

CSRI Summer Proceedings 2010

DTIC Science & Technology

2010-12-17

AND ADDRESSES U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Mathematics; Computer Science Eric C...Institute at Sandia National Laboratories Editors: Eric C. Cyr and S. Scott Collis Sandia National Laboratories December 17, 2010 SAND2010-8783P...CSRI and its activities which have benefited both Sandia and the greater research community. Eric C. Cyr S. Scott Collis December 17, 2010 iv CSRI

NASA Gulf of Mexico Initiative Hypoxia Research

NASA Technical Reports Server (NTRS)

Armstrong, Curtis D.

2012-01-01

The Applied Science & Technology Project Office at Stennis Space Center (SSC) manages NASA's Gulf of Mexico Initiative (GOMI). Addressing short-term crises and long-term issues, GOMI participants seek to understand the environment using remote sensing, in-situ observations, laboratory analyses, field observations and computational models. New capabilities are transferred to end-users to help them make informed decisions. Some GOMI activities of interest to the hypoxia research community are highlighted.

A Spatial Display for Ground-Penetrating Radar Change Detection

DTIC Science & Technology

2013-09-01

rights reserved. Author ............................ Department of Electrical Engineering and Computer Science September 1, 2013 Certified by...a new member of the Lincoln community. Thank you, Rebecca, for being you and being here with me at MIT. I would like to thank my parents for their...alteration in the height of dirt under it. This capability will raise the chance of detecting a place where someone buried an object by detecting the

Directory of Industry and University Collaborations with a Focus on Software Engineering Education and Training, Version 6

DTIC Science & Technology

1997-11-01

of Computer Science and Information Systems. Membership American University is an independent, coeducational university with more than 11,000...The entire community profits as AIM members achieve common objectives. Corporate contribution is evolving into a benefit -based membership, providing...direct value or service to CMU/SEI-97-SR-018 the member, while strengthening the Nebraska information technology environment. Specific benefits to

Combinatorial Algorithms to Enable Computational Science and Engineering: Work from the CSCAPES Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boman, Erik G.; Catalyurek, Umit V.; Chevalier, Cedric

2015-01-16

This final progress report summarizes the work accomplished at the Combinatorial Scientific Computing and Petascale Simulations Institute. We developed Zoltan, a parallel mesh partitioning library that made use of accurate hypergraph models to provide load balancing in mesh-based computations. We developed several graph coloring algorithms for computing Jacobian and Hessian matrices and organized them into a software package called ColPack. We developed parallel algorithms for graph coloring and graph matching problems, and also designed multi-scale graph algorithms. Three PhD students graduated, six more are continuing their PhD studies, and four postdoctoral scholars were advised. Six of these students and Fellowsmore » have joined DOE Labs (Sandia, Berkeley), as staff scientists or as postdoctoral scientists. We also organized the SIAM Workshop on Combinatorial Scientific Computing (CSC) in 2007, 2009, and 2011 to continue to foster the CSC community.« less

Biology Needs Evolutionary Software Tools: Let’s Build Them Right

PubMed Central

Team, Galaxy; Goecks, Jeremy; Taylor, James

2018-01-01

Abstract Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training. PMID:29688462

e-Science on Earthquake Disaster Mitigation by EUAsiaGrid

NASA Astrophysics Data System (ADS)

Yen, Eric; Lin, Simon; Chen, Hsin-Yen; Chao, Li; Huang, Bor-Shoh; Liang, Wen-Tzong

2010-05-01

Although earthquake is not predictable at this moment, with the aid of accurate seismic wave propagation analysis, we could simulate the potential hazards at all distances from possible fault sources by understanding the source rupture process during large earthquakes. With the integration of strong ground-motion sensor network, earthquake data center and seismic wave propagation analysis over gLite e-Science Infrastructure, we could explore much better knowledge on the impact and vulnerability of potential earthquake hazards. On the other hand, this application also demonstrated the e-Science way to investigate unknown earth structure. Regional integration of earthquake sensor networks could aid in fast event reporting and accurate event data collection. Federation of earthquake data center entails consolidation and sharing of seismology and geology knowledge. Capability building of seismic wave propagation analysis implies the predictability of potential hazard impacts. With gLite infrastructure and EUAsiaGrid collaboration framework, earth scientists from Taiwan, Vietnam, Philippine, Thailand are working together to alleviate potential seismic threats by making use of Grid technologies and also to support seismology researches by e-Science. A cross continental e-infrastructure, based on EGEE and EUAsiaGrid, is established for seismic wave forward simulation and risk estimation. Both the computing challenge on seismic wave analysis among 5 European and Asian partners, and the data challenge for data center federation had been exercised and verified. Seismogram-on-Demand service is also developed for the automatic generation of seismogram on any sensor point to a specific epicenter. To ease the access to all the services based on users workflow and retain the maximal flexibility, a Seismology Science Gateway integating data, computation, workflow, services and user communities would be implemented based on typical use cases. In the future, extension of the earthquake wave propagation to tsunami mitigation would be feasible once the user community support is in place.

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology

PubMed Central

Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics. PMID:28558050

The Internet of Samples in the Earth Sciences (iSamples)

NASA Astrophysics Data System (ADS)

Carter, M. R.; Lehnert, K. A.

2015-12-01

Across most Earth Science disciplines, research depends on the availability of samples collected above, at, and beneath Earth's surface, on the moon and in space, or generated in experiments. Many domains in the Earth Sciences have recently expressed the need for better discovery, access, and sharing of scientific samples and collections (EarthCube End-User Domain workshops, 2012 and 2013, http://earthcube.org/info/about/end-user-workshops), as has the US government (OSTP Memo, March 2014). The Internet of Samples in the Earth Sciences (iSamples) is an initiative funded as a Research Coordination Network (RCN) within the EarthCube program to address this need. iSamples aims to advance the use of innovative cyberinfrastructure to connect physical samples and sample collections across the Earth Sciences with digital data infrastructures to revolutionize their utility for science. iSamples strives to build, grow, and foster a new community of practice, in which domain scientists, curators of sample repositories and collections, computer and information scientists, software developers and technology innovators engage in and collaborate on defining, articulating, and addressing the needs and challenges of physical samples as a critical component of digital data infrastructure. A primary goal of iSamples is to deliver a community-endorsed set of best practices and standards for the registration, description, identification, and citation of physical specimens and define an actionable plan for implementation. iSamples conducted a broad community survey about sample sharing and has created 5 different working groups to address the different challenges of developing the internet of samples - from metadata schemas and unique identifiers to an architecture of a shared cyberinfrastructure for collections, to digitization of existing collections, to education, and ultimately to establishing the physical infrastructure that will ensure preservation and access of the physical samples. Creating awareness of the need to include physical samples in discussions of reproducible science is another priority of the iSamples RCN.

Space Weather in the Machine Learning Era: A Multidisciplinary Approach

NASA Astrophysics Data System (ADS)

Camporeale, E.; Wing, S.; Johnson, J.; Jackman, C. M.; McGranaghan, R.

2018-01-01

The workshop entitled Space Weather: A Multidisciplinary Approach took place at the Lorentz Center, University of Leiden, Netherlands, on 25-29 September 2017. The aim of this workshop was to bring together members of the Space Weather, Mathematics, Statistics, and Computer Science communities to address the use of advanced techniques such as Machine Learning, Information Theory, and Deep Learning, to better understand the Sun-Earth system and to improve space weather forecasting. Although individual efforts have been made toward this goal, the community consensus is that establishing interdisciplinary collaborations is the most promising strategy for fully utilizing the potential of these advanced techniques in solving Space Weather-related problems.

An infrastructure for the integration of geoscience instruments and sensors on the Grid

NASA Astrophysics Data System (ADS)

Pugliese, R.; Prica, M.; Kourousias, G.; Del Linz, A.; Curri, A.

2009-04-01

The Grid, as a computing paradigm, has long been in the attention of both academia and industry[1]. The distributed and expandable nature of its general architecture result to scalability and more efficient utilisation of the computing infrastructures. The scientific community, including that of geosciences, often handles problems with very high requirements in data processing, transferring, and storing[2,3]. This has raised the interest on Grid technologies but these are often viewed solely as an access gateway to HPC. Suitable Grid infrastructures could provide the geoscience community with additional benefits like those of sharing, remote access and control of scientific systems. These systems can be scientific instruments, sensors, robots, cameras and any other device used in geosciences. The solution for practical, general, and feasible Grid-enabling of such devices requires non-intrusive extensions on core parts of the current Grid architecture. We propose an extended version of an architecture[4] that can serve as the solution to the problem. The solution we propose is called Grid Instrument Element (IE) [5]. It is an addition to the existing core Grid parts; the Computing Element (CE) and the Storage Element (SE) that serve the purposes that their name suggests. The IE that we will be referring to, and the related technologies have been developed in the EU project on the Deployment of Remote Instrumentation Infrastructure (DORII1). In DORII, partners of various scientific communities including those of Earthquake, Environmental science, and Experimental science, have adopted the technology of the Instrument Element in order to integrate to the Grid their devices. The Oceanographic and coastal observation and modelling Mediterranean Ocean Observing Network (OGS2), a DORII partner, is in the process of deploying the above mentioned Grid technologies on two types of observational modules: Argo profiling floats and a novel Autonomous Underwater Vehicle (AUV). In this paper i) we define the need for integration of instrumentation in the Grid, ii) we introduce the solution of the Instrument Element, iii) we demonstrate a suitable end-user web portal for accessing Grid resources, iv) we describe from the Grid-technological point of view the process of the integration to the Grid of two advanced environmental monitoring devices. References [1] M. Surridge, S. Taylor, D. De Roure, and E. Zaluska, "Experiences with GRIA—Industrial Applications on a Web Services Grid," e-Science and Grid Computing, First International Conference on e-Science and Grid Computing, 2005, pp. 98-105. [2] A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke, "The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets," Journal of Network and Computer Applications, vol. 23, 2000, pp. 187-200. [3] B. Allcock, J. Bester, J. Bresnahan, A.L. Chervenak, I. Foster, C. Kesselman, S. Meder, V. Nefedova, D. Quesnel, and S. Tuecke, "Data management and transfer in high-performance computational grid environments," Parallel Computing, vol. 28, 2002, pp. 749-771. [4] E. Frizziero, M. Gulmini, F. Lelli, G. Maron, A. Oh, S. Orlando, A. Petrucci, S. Squizzato, and S. Traldi, "Instrument Element: A New Grid component that Enables the Control of Remote Instrumentation," Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)-Volume 00, IEEE Computer Society Washington, DC, USA, 2006. [5] R. Ranon, L. De Marco, A. Senerchia, S. Gabrielli, L. Chittaro, R. Pugliese, L. Del Cano, F. Asnicar, and M. Prica, "A Web-based Tool for Collaborative Access to Scientific Instruments in Cyberinfrastructures." 1 The DORII project is supported by the European Commission within the 7th Framework Programme (FP7/2007-2013) under grant agreement no. RI-213110. URL: http://www.dorii.eu 2 Istituto Nazionale di Oceanografia e di Geofisica Sperimentale. URL: http://www.ogs.trieste.it

Building Local Infrastructure for Community Adoption of Science-Based Prevention: The Role of Coalition Functioning.

PubMed

Shapiro, Valerie B; Hawkins, J David; Oesterle, Sabrina

2015-11-01

The widespread adoption of science-based prevention requires local infrastructures for prevention service delivery. Communities That Care (CTC) is a tested prevention service delivery system that enables a local coalition of community stakeholders to use a science-based approach to prevention and improve the behavioral health of young people. This paper uses data from the Community Youth Development Study (CYDS), a community-randomized trial of CTC, to examine the extent to which better internal team functioning of CTC coalitions increases the community-wide adoption of science-based prevention within 12 communities, relative to 12 matched comparison communities. Specifically, this paper examines the potential of both a direct relationship between coalition functioning and the community-wide adoption of science-based prevention and a direct relationship between functioning and the coalition capacities that ultimately enable the adoption of science-based prevention. Findings indicate no evidence of a direct relationship between four dimensions of coalition functioning and the community-wide adoption of a science-based approach to prevention, but suggest a relationship between coalition functioning and coalition capacities (building new member skills and establishing external linkages with existing community organizations) that enable science-based prevention.

University of Washington's eScience Institute Promotes New Training and Career Pathways in Data Science

NASA Astrophysics Data System (ADS)

Stone, S.; Parker, M. S.; Howe, B.; Lazowska, E.

2015-12-01

Rapid advances in technology are transforming nearly every field from "data-poor" to "data-rich." The ability to extract knowledge from this abundance of data is the cornerstone of 21st century discovery. At the University of Washington eScience Institute, our mission is to engage researchers across disciplines in developing and applying advanced computational methods and tools to real world problems in data-intensive discovery. Our research team consists of individuals with diverse backgrounds in domain sciences such as astronomy, oceanography and geology, with complementary expertise in advanced statistical and computational techniques such as data management, visualization, and machine learning. Two key elements are necessary to foster careers in data science: individuals with cross-disciplinary training in both method and domain sciences, and career paths emphasizing alternative metrics for advancement. We see persistent and deep-rooted challenges for the career paths of people whose skills, activities and work patterns don't fit neatly into the traditional roles and success metrics of academia. To address these challenges the eScience Institute has developed training programs and established new career opportunities for data-intensive research in academia. Our graduate students and post-docs have mentors in both a methodology and an application field. They also participate in coursework and tutorials to advance technical skill and foster community. Professional Data Scientist positions were created to support research independence while encouraging the development and adoption of domain-specific tools and techniques. The eScience Institute also supports the appointment of faculty who are innovators in developing and applying data science methodologies to advance their field of discovery. Our ultimate goal is to create a supportive environment for data science in academia and to establish global recognition for data-intensive discovery across all fields.

Factors influencing exemplary science teachers' levels of computer use

NASA Astrophysics Data System (ADS)

Hakverdi, Meral

This study examines exemplary science teachers' use of technology in science instruction, factors influencing their level of computer use, their level of knowledge/skills in using specific computer applications for science instruction, their use of computer-related applications/tools during their instruction, and their students' use of computer applications/tools in or for their science class. After a relevant review of the literature certain variables were selected for analysis. These variables included personal self-efficacy in teaching with computers, outcome expectancy, pupil-control ideology, level of computer use, age, gender, teaching experience, personal computer use, professional computer use and science teachers' level of knowledge/skills in using specific computer applications for science instruction. The sample for this study includes middle and high school science teachers who received the Presidential Award for Excellence in Science Teaching Award (sponsored by the White House and the National Science Foundation) between the years 1997 and 2003 from all 50 states and U.S. territories. Award-winning science teachers were contacted about the survey via e-mail or letter with an enclosed return envelope. Of the 334 award-winning science teachers, usable responses were received from 92 science teachers, which made a response rate of 27.5%. Analysis of the survey responses indicated that exemplary science teachers have a variety of knowledge/skills in using computer related applications/tools. The most commonly used computer applications/tools are information retrieval via the Internet, presentation tools, online communication, digital cameras, and data collection probes. Results of the study revealed that students' use of technology in their science classroom is highly correlated with the frequency of their science teachers' use of computer applications/tools. The results of the multiple regression analysis revealed that personal self-efficacy related to the exemplary science teachers' level of computer use suggesting that computer use is dependent on perceived abilities at using computers. The teachers' use of computer-related applications/tools during class, and their personal self-efficacy, age, and gender are highly related with their level of knowledge/skills in using specific computer applications for science instruction. The teachers' level of knowledge/skills in using specific computer applications for science instruction and gender related to their use of computer-related applications/tools during class and the students' use of computer-related applications/tools in or for their science class. In conclusion, exemplary science teachers need assistance in learning and using computer-related applications/tool in their science class.

Early Career Summer Interdisciplinary Team Experiences and Student Persistence in STEM Fields

NASA Astrophysics Data System (ADS)

Cadavid, A. C.; Pedone, V. A.; Horn, W.; Rich, H.

2015-12-01

STEPS (Students Targeting Engineering and Physical Science) is an NSF-funded program designed to increase the number of California State University Northridge students getting bachelor's degrees in the natural sciences, mathematics, engineering and computer science. The greatest loss of STEM majors occurs between sophomore and junior- years, so we designed Summer Interdisciplinary Team Experience (SITE) as an early career program for these students. Students work closely with a faculty mentor in teams of ten to investigate regionally relevant problems, many of which relate to sustainability efforts on campus or the community. The projects emphasize hands-on activities and team-based learning and decision making. We report data for five years of projects, qualitative assessment through entrance and exit surveys and student interviews, and in initial impact on retention of the participants.

Development of an Agile Knowledge Engineering Framework in Support of Multi-Disciplinary Translational Research

PubMed Central

Borlawsky, Tara B.; Dhaval, Rakesh; Hastings, Shannon L.; Payne, Philip R. O.

2009-01-01

In October 2006, the National Institutes of Health launched a new national consortium, funded through Clinical and Translational Science Awards (CTSA), with the primary objective of improving the conduct and efficiency of the inherently multi-disciplinary field of translational research. To help meet this goal, the Ohio State University Center for Clinical and Translational Science has launched a knowledge management initiative that is focused on facilitating widespread semantic interoperability among administrative, basic science, clinical and research computing systems, both internally and among the translational research community at-large, through the integration of domain-specific standard terminologies and ontologies with local annotations. This manuscript describes an agile framework that builds upon prevailing knowledge engineering and semantic interoperability methods, and will be implemented as part this initiative. PMID:21347164

Development of an agile knowledge engineering framework in support of multi-disciplinary translational research.

PubMed

Borlawsky, Tara B; Dhaval, Rakesh; Hastings, Shannon L; Payne, Philip R O

2009-03-01

In October 2006, the National Institutes of Health launched a new national consortium, funded through Clinical and Translational Science Awards (CTSA), with the primary objective of improving the conduct and efficiency of the inherently multi-disciplinary field of translational research. To help meet this goal, the Ohio State University Center for Clinical and Translational Science has launched a knowledge management initiative that is focused on facilitating widespread semantic interoperability among administrative, basic science, clinical and research computing systems, both internally and among the translational research community at-large, through the integration of domain-specific standard terminologies and ontologies with local annotations. This manuscript describes an agile framework that builds upon prevailing knowledge engineering and semantic interoperability methods, and will be implemented as part this initiative.

The community FabLab platform: applications and implications in biomedical engineering.

PubMed

Stephenson, Makeda K; Dow, Douglas E

2014-01-01

Skill development in science, technology, engineering and math (STEM) education present one of the most formidable challenges of modern society. The Community FabLab platform presents a viable solution. Each FabLab contains a suite of modern computer numerical control (CNC) equipment, electronics and computing hardware and design, programming, computer aided design (CAD) and computer aided machining (CAM) software. FabLabs are community and educational resources and open to the public. Development of STEM based workforce skills such as digital fabrication and advanced manufacturing can be enhanced using this platform. Particularly notable is the potential of the FabLab platform in STEM education. The active learning environment engages and supports a diversity of learners, while the iterative learning that is supported by the FabLab rapid prototyping platform facilitates depth of understanding, creativity, innovation and mastery. The product and project based learning that occurs in FabLabs develops in the student a personal sense of accomplishment, self-awareness, command of the material and technology. This helps build the interest and confidence necessary to excel in STEM and throughout life. Finally the introduction and use of relevant technologies at every stage of the education process ensures technical familiarity and a broad knowledge base needed for work in STEM based fields. Biomedical engineering education strives to cultivate broad technical adeptness, creativity, interdisciplinary thought, and an ability to form deep conceptual understanding of complex systems. The FabLab platform is well designed to enhance biomedical engineering education.

The VERCE Science Gateway: enabling user friendly seismic waves simulations across European HPC infrastructures

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Krause, Amy; Ramos Garcia, Clàudia; Casarotti, Emanuele; Magnoni, Federica; Klampanos, Iraklis A.; Frobert, Laurent; Krischer, Lion; Trani, Luca; David, Mario; Leong, Siew Hoon; Muraleedharan, Visakh

2014-05-01

The EU-funded project VERCE (Virtual Earthquake and seismology Research Community in Europe) aims to deploy technologies which satisfy the HPC and data-intensive requirements of modern seismology. As a result of VERCE's official collaboration with the EU project SCI-BUS, access to computational resources, like local clusters and international infrastructures (EGI and PRACE), is made homogeneous and integrated within a dedicated science gateway based on the gUSE framework. In this presentation we give a detailed overview on the progress achieved with the developments of the VERCE Science Gateway, according to a use-case driven implementation strategy. More specifically, we show how the computational technologies and data services have been integrated within a tool for Seismic Forward Modelling, whose objective is to offer the possibility to perform simulations of seismic waves as a service to the seismological community. We will introduce the interactive components of the OGC map based web interface and how it supports the user with setting up the simulation. We will go through the selection of input data, which are either fetched from federated seismological web services, adopting community standards, or provided by the users themselves by accessing their own document data store. The HPC scientific codes can be selected from a number of waveform simulators, currently available to the seismological community as batch tools or with limited configuration capabilities in their interactive online versions. The results will be staged out from the HPC via a secure GridFTP transfer to a VERCE data layer managed by iRODS. The provenance information of the simulation will be automatically cataloged by the data layer via NoSQL techonologies. We will try to demonstrate how data access, validation and visualisation can be supported by a general purpose provenance framework which, besides common provenance concepts imported from the OPM and the W3C-PROV initiatives, also offers an extensible metadata archive including community and user defined metadata and annotations. Finally, we will show how the VERCE Gateway platform will allow the customisation of pre and post processing phases of the simulation workflows, thanks to the availability of a registry of processing elements (PEs,) which are easily developed and maintained by the seismologists.

NASA's Participation in the National Computational Grid

NASA Technical Reports Server (NTRS)

Feiereisen, William J.; Zornetzer, Steve F. (Technical Monitor)

1998-01-01

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

GeoChronos: An On-line Collaborative Platform for Earth Observation Scientists

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Kiddle, C.; Curry, R.; Markatchev, N.; Zonta-Pastorello, G., Jr.; Rivard, B.; Sanchez-Azofeifa, G. A.; Simmonds, R.; Tan, T.

2009-12-01

Recent advances in cyberinfrastructure are offering new solutions to the growing challenges of managing and sharing large data volumes. Web 2.0 and social networking technologies, provide the means for scientists to collaborate and share information more effectively. Cloud computing technologies can provide scientists with transparent and on-demand access to applications served over the Internet in a dynamic and scalable manner. Semantic Web technologies allow for data to be linked together in a manner understandable by machines, enabling greater automation. Combining all of these technologies together can enable the creation of very powerful platforms. GeoChronos (http://geochronos.org/), part of a CANARIE Network Enabled Platforms project, is an online collaborative platform that incorporates these technologies to enable members of the earth observation science community to share data and scientific applications and to collaborate more effectively. The GeoChronos portal is built on an open source social networking platform called Elgg. Elgg provides a full set of social networking functionalities similar to Facebook including blogs, tags, media/document sharing, wikis, friends/contacts, groups, discussions, message boards, calendars, status, activity feeds and more. An underlying cloud computing infrastructure enables scientists to access dynamically provisioned applications via the portal for visualizing and analyzing data. Users are able to access and run the applications from any computer that has a Web browser and Internet connectivity and do not need to manage and maintain the applications themselves. Semantic Web Technologies, such as the Resource Description Framework (RDF) are being employed for relating and linking together spectral, satellite, meteorological and other data. Social networking functionality plays an integral part in facilitating the sharing of data and applications. Examples of recent GeoChronos users during the early testing phase have included the IAI International Wireless Sensor Networking Summer School at the University of Alberta, and the IAI Tropi-Dry community. Current GeoChronos activities include the development of a web-based spectral library and related analytical and visualization tools, in collaboration with members of the SpecNet community. The GeoChronos portal will be open to all members of the earth observation science community when the project nears completion at the end of 2010.

Knowing and Learning about Science in Primary School "Communities of Science Practice": The Views of Participating Scientists in the "MyScience" Initiative

ERIC Educational Resources Information Center

Forbes, Anne; Skamp, Keith

2013-01-01

"MyScience" is a primary science education initiative in which being in a community of practice is integral to the learning process. One component of this initiative involves professional scientists interacting with primary school communities which are navigating their way towards sustainable "communities of practice" around the "domain" of…

WebGL for Rosetta Science Planning

NASA Astrophysics Data System (ADS)

Schmidt, Albrecht; Völk, Stefan; Grieger, Björn

2013-04-01

Rosetta is a mission of the European Space Agency (ESA) to rendez-vous with comet Churyumov-Gerasimenko in 2014. The trajectory and operations of the mission are particularly complex, have many free parameters and are novel to the community. To support science planning, communicate operational ideas and disseminate operational scenarios to the scientific community, the science ground segment makes use of Web-based visualisation technologies. Using the recent standard WebGL, static pages of time-dependent three-dimensional views of the spacecraft and the field-of-views of the instruments are generated, directly from the operational files. These can then be viewed in modern Web browsers for understanding or verification, be analysed and correlated with other studies. Variable timesteps make it possible to provide both overviews and detailed animated scenes. The technical challenges that are particular to Web-based environments include: (1) In traditional OpenGL, is much easier to compute needed data on demand since the visualisation runs natively on a usually quite powerful computer. In WebGL application, since requests for additional data have to be passed through a Web server, they are more complex and also require a more complex infrastructure. (2) The volume of data that can be kept in a browser environment is limited and has to be transferred over often slow network links. Thus, careful design and reduction of data is required. (3) Although browser support for WebGL has improved since the authors started using it, it is often not well supported on mobile and small devices. (4) Web browsers often only support limited end user interactions with a mouse or keyboards. While some of the challenges can be expected to become less important as technological progress continues, others seem to be more inherent to the approach. On the positive side, the authors' experiences include: (1) low threshold in the community to using the visualisations, (2), thus, cooperative use of the products, and (3) good and still improving tool and library support.

The EGI-Engage EPOS Competence Center - Interoperating heterogeneous AAI mechanisms and Orchestrating distributed computational resources

NASA Astrophysics Data System (ADS)

Bailo, Daniele; Scardaci, Diego; Spinuso, Alessandro; Sterzel, Mariusz; Schwichtenberg, Horst; Gemuend, Andre

2016-04-01

The mission of EGI-Engage project [1] is to accelerate the implementation of the Open Science Commons vision, where researchers from all disciplines have easy and open access to the innovative digital services, data, knowledge and expertise they need for collaborative and excellent research. The Open Science Commons is grounded on three pillars: the e-Infrastructure Commons, an ecosystem of services that constitute the foundation layer of distributed infrastructures; the Open Data Commons, where observations, results and applications are increasingly available for scientific research and for anyone to use and reuse; and the Knowledge Commons, in which communities have shared ownership of knowledge, participate in the co-development of software and are technically supported to exploit state-of-the-art digital services. To develop the Knowledge Commons, EGI-Engage is supporting the work of a set of community-specific Competence Centres, with participants from user communities (scientific institutes), National Grid Initiatives (NGIs), technology and service providers. Competence Centres collect and analyse requirements, integrate community-specific applications into state-of-the-art services, foster interoperability across e-Infrastructures, and evolve services through a user-centric development model. One of these Competence Centres is focussed on the European Plate Observing System (EPOS) [2] as representative of the solid earth science communities. EPOS is a pan-European long-term plan to integrate data, software and services from the distributed (and already existing) Research Infrastructures all over Europe, in the domain of the solid earth science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. EPOS will improve our ability to better manage the use of the subsurface of the Earth. EPOS started its Implementation Phase in October 2015 and is now actively working in order to integrate multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) - European wide organizations and e-Infrastructure providing community specific data and data products - and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. TCS data, data products and services will be integrated into the Integrated Core Services (ICS) system, that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. The EPOS competence center (EPOS CC) goal is to tackle two of the main challenges that the ICS are going to face in the near future, by taking advantage of the technical solutions provided by EGI. In order to do this, we will present the two pilot use cases the EGI-EPOS CC is developing: 1) The AAI pilot, dealing with the provision of transparent and homogeneous access to the ICS infrastructure to users owning different kind of credentials (e.g. eduGain, OpenID Connect, X509 certificates etc.). Here the focus is on the mechanisms which allow the credential delegation. 2) The computational pilot, Improve the back-end services of an existing application in the field of Computational Seismology, developed in the context of the EC funded project VERCE. The application allows the processing and the comparison of data resulting from the simulation of seismic wave propagation following a real earthquake and real measurements recorded by seismographs. While the simulation data is produced directly by the users and stored in a Data Management System, the observations need to be pre-staged from institutional data-services, which are maintained by the community itself. This use case aims at exploiting the EGI FedCloud e-infrastructure for Data Intensive analysis and also explores possible interaction with other Common Data Infrastructure initiatives as EUDAT. In the presentation, the state of the art of the two use cases, together with the open challenges and the future application will be discussed. Also, possible integration of EGI solutions with EPOS and other e-infrastructure providers will be considered. [1] EGI-ENGAGE https://www.egi.eu/about/egi-engage/ [2] EPOS http://www.epos-eu.org/

Evaluating Cloud Computing in the Proposed NASA DESDynI Ground Data System

NASA Technical Reports Server (NTRS)

Tran, John J.; Cinquini, Luca; Mattmann, Chris A.; Zimdars, Paul A.; Cuddy, David T.; Leung, Kon S.; Kwoun, Oh-Ig; Crichton, Dan; Freeborn, Dana

2011-01-01

The proposed NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission would be a first-of-breed endeavor that would fundamentally change the paradigm by which Earth Science data systems at NASA are built. DESDynI is evaluating a distributed architecture where expert science nodes around the country all engage in some form of mission processing and data archiving. This is compared to the traditional NASA Earth Science missions where the science processing is typically centralized. What's more, DESDynI is poised to profoundly increase the amount of data collection and processing well into the 5 terabyte/day and tens of thousands of job range, both of which comprise a tremendous challenge to DESDynI's proposed distributed data system architecture. In this paper, we report on a set of architectural trade studies and benchmarks meant to inform the DESDynI mission and the broader community of the impacts of these unprecedented requirements. In particular, we evaluate the benefits of cloud computing and its integration with our existing NASA ground data system software called Apache Object Oriented Data Technology (OODT). The preliminary conclusions of our study suggest that the use of the cloud and OODT together synergistically form an effective, efficient and extensible combination that could meet the challenges of NASA science missions requiring DESDynI-like data collection and processing volumes at reduced costs.

Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

NASA Astrophysics Data System (ADS)

Molthan, A.; Limaye, A. S.

2011-12-01

Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula's "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA's National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA's SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT's experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by geostationary satellite observations processed on virtual machines powered by Nebula. This presentation will provide an overview of these activities from a scientific and cloud computing applications perspective, identifying the strengths and weaknesses for deploying each project within an IaaS environment, and ways to collaborate with the Nebula or other cloud-user communities to collaborate on projects as they go forward.

Increasing Student Retention Through Application of Attitude Change Packages (and) Increasing GPA and Student Retention of Low Income Minority Community College Students Through Application of Nightengale Conant Change Packages; A Pilot STUDY.

ERIC Educational Resources Information Center

Preising, Paul P.; Frost, Robert

The first of two studies reported was conducted to determine whether unemployed aerospace engineers who received computer science training as well as the Nightengale-Conant attitude change packages would have a significantly higher course completion rate than control classes who were given the same training without the attitude change packages.…

Next Generation Cloud-based Science Data Systems and Their Implications on Data and Software Stewardship, Preservation, and Provenance

NASA Astrophysics Data System (ADS)

Hua, H.; Manipon, G.; Starch, M.

2017-12-01

NASA's upcoming missions are expected to be generating data volumes at least an order of magnitude larger than current missions. A significant increase in data processing, data rates, data volumes, and long-term data archive capabilities are needed. Consequently, new challenges are emerging that impact traditional data and software management approaches. At large-scales, next generation science data systems are exploring the move onto cloud computing paradigms to support these increased needs. New implications such as costs, data movement, collocation of data systems & archives, and moving processing closer to the data, may result in changes to the stewardship, preservation, and provenance of science data and software. With more science data systems being on-boarding onto cloud computing facilities, we can expect more Earth science data records to be both generated and kept in the cloud. But at large scales, the cost of processing and storing global data may impact architectural and system designs. Data systems will trade the cost of keeping data in the cloud with the data life-cycle approaches of moving "colder" data back to traditional on-premise facilities. How will this impact data citation and processing software stewardship? What are the impacts of cloud-based on-demand processing and its affect on reproducibility and provenance. Similarly, with more science processing software being moved onto cloud, virtual machines, and container based approaches, more opportunities arise for improved stewardship and preservation. But will the science community trust data reprocessed years or decades later? We will also explore emerging questions of the stewardship of the science data system software that is generating the science data records both during and after the life of mission.

On the Future of Thermochemical Databases, the Development of Solution Models and the Practical Use of Computational Thermodynamics in Volcanology, Geochemistry and Petrology: Can Innovations of Modern Data Science Democratize an Oligarchy?

NASA Astrophysics Data System (ADS)

Ghiorso, M. S.

2014-12-01

Computational thermodynamics (CT) has now become an essential tool of petrologic and geochemical research. CT is the basis for the construction of phase diagrams, the application of geothermometers and geobarometers, the equilibrium speciation of solutions, the construction of pseudosections, calculations of mass transfer between minerals, melts and fluids, and, it provides a means of estimating materials properties for the evaluation of constitutive relations in fluid dynamical simulations. The practical application of CT to Earth science problems requires data. Data on the thermochemical properties and the equation of state of relevant materials, and data on the relative stability and partitioning of chemical elements between phases as a function of temperature and pressure. These data must be evaluated and synthesized into a self consistent collection of theoretical models and model parameters that is colloquially known as a thermodynamic database. Quantitative outcomes derived from CT reply on the existence, maintenance and integrity of thermodynamic databases. Unfortunately, the community is reliant on too few such databases, developed by a small number of research groups, and mostly under circumstances where refinement and updates to the database lag behind or are unresponsive to need. Given the increasing level of reliance on CT calculations, what is required is a paradigm shift in the way thermodynamic databases are developed, maintained and disseminated. They must become community resources, with flexible and assessable software interfaces that permit easy modification, while at the same time maintaining theoretical integrity and fidelity to the underlying experimental observations. Advances in computational and data science give us the tools and resources to address this problem, allowing CT results to be obtained at the speed of thought, and permitting geochemical and petrological intuition to play a key role in model development and calibration.

Opening Comments: SciDAC 2008

NASA Astrophysics Data System (ADS)

Strayer, Michael

2008-07-01

Welcome to Seattle and the 2008 SciDAC Conference. This conference, the fourth in the series, is a continuation of the PI meetings we first began under SciDAC-1. I would like to start by thanking the organizing committee, and Rick Stevens in particular, for organizing this year's meeting. This morning I would like to look briefly at SciDAC, to give you a brief history of SciDAC and also look ahead to see where we plan to go over the next few years. I think the best description of SciDAC, at least the simulation part, comes from a quote from Dr Ray Orbach, DOE's Under Secretary for Science and Director of the Office of Science. In an interview that appeared in the SciDAC Review magazine, Dr Orbach said, `SciDAC is unique in the world. There isn't any other program like it anywhere else, and it has the remarkable ability to do science by bringing together physical scientists, mathematicians, applied mathematicians, and computer scientists who recognize that computation is not something you do at the end, but rather it needs to be built into the solution of the very problem that one is addressing'. Of course, that is extended not just to physical scientists, but also to biological scientists. This is a theme of computational science, this partnership among disciplines, which goes all the way back to the early 1980s and Ken Wilson. It's a unique thread within the Department of Energy. SciDAC-1, launched around the turn of the millennium, created a new generation of scientific simulation codes. It advocated building out mathematical and computing system software in support of science and a new collaboratory software environment for data. The original concept for SciDAC-1 had topical centers for the execution of the various science codes, but several corrections and adjustments were needed. The ASCR scientific computing infrastructure was also upgraded, providing the hardware facilities for the program. The computing facility that we had at that time was the big 3 teraflop/s center at NERSC and that had to be shared with the programmatic side supporting research across DOE. At the time, ESnet was just slightly over half a gig per sec of bandwidth; and the science being addressed was accelerator science, climate, chemistry, fusion, astrophysics, materials science, and QCD. We built out the national collaboratories from the ASCR office, and in addition we built Integrated Software Infrastructure Centers (ISICs). Of these, three were in applied mathematics, four in computer science (including a performance evaluation research center), and four were collaboratories or Grid projects having to do with data management. For science, there were remarkable breakthroughs in simulation, such as full 3D laboratory scale flame simulation. There were also significant improvements in application codes - from factors of almost 3 to more than 100 - and code improvement as people began to realize they had to integrate mathematics tools and computer science tools into their codes to take advantage of the parallelism of the day. The SciDAC data-mining tool, Sapphire, received a 2006 R&D 100 award. And the community as a whole worked well together and began building a publication record that was substantial. In 2006, we recompeted the program with similar goals - SciDAC-1 was very successful, and we wanted to continue that success and extend what was happening under SciDAC to the broader science community. We opened up the partnership to all of the Offices of Science and the NSF and the NNSA. The goal was to create comprehensive scientific computing software and the infrastructure for the software to enable scientific discovery in the physical, biological, and environmental sciences and take the simulations to an extreme scale, in this case petascale. We would also build out a new generation of data management tools. What we observed during SciDAC-1 was that the data and the data communities - both experimental data from large experimental facilities and observational data, along with simulation data - were expanding at a rate significantly faster than Moore's law. In the past few weeks, the FastBit indexing technology software tool for data analyses and data mining developed under SciDAC's Scientific Data Management project was recognized with an R&D 100 Award, selected by an independent judging panel and editors of R&D Magazine as one of the 100 most technologically significant products introduced into the marketplace over the past year. For SciDAC-2 we had nearly 250 proposals requesting a total of slightly over 1 billion in funding. Of course, we had nowhere near 1 billion. The facilities and the science we ended up with were not significantly different from what we had in SciDAC-1. But we had put in place substantially increased facilities for science. When SciDAC-1 was originally executed with the facilities at NERSC, there was significant impact on the resources at NERSC, because not only did we have an expanding portfolio of programmatic science, but we had the SciDAC projects that also needed to run at NERSC. Suddenly, NERSC was incredibly oversubscribed. With SciDAC-2, we had in place leadership-class computing facilities at Argonne with slightly more than half a petaflop and at Oak Ridge with slightly more than a quarter petaflop with an upgrade planned at the end of this year for a petaflop. And we increased the production computing capacity at NERSC to 104 teraflop/s just so that we would not impact the programmatic research and so that we would have a startup facility for SciDAC. At the end of the summer, NERSC will be at 360 teraflop/s. Both the Oak Ridge system and the principal resource at NERSC are Cray systems; Argonne has a different architecture, an IBM Blue Gene/P. At the same time, ESnet has been built out, and we are on a path where we will have dual rings around the country, from 10 to 40 gigabits per second - a factor of 20 to 80 over what was available during SciDAC-1. The science areas include accelerator science and simulation, astrophysics, climate modeling and simulation, computational biology, fusion science, high-energy physics, petabyte high-energy/ nuclear physics, materials science and chemistry, nuclear physics, QCD, radiation transport, turbulence, and groundwater reactive transport modeling and simulation. They were supported by new enabling technology centers and university-based institutes to develop an educational thread for the SciDAC program. There were four mathematics projects and four computer science projects; and under data management, we see a significant difference in that we are bringing up new visualization projects to support and sustain data-intensive science. When we look at the budgets, we see growth in the budget from just under 60 million for SciDAC-1 to just over 80 for SciDAC-2. Part of the growth is due to bringing in NSF and NNSA as new partners, and some of the growth is due to some program offices increasing their investment in SciDAC, while other program offices are constant or have decreased their investment. This is not a reflection of their priorities per se but, rather, a reflection of the budget process and the difficult times in Washington during the past two years. New activities are under way in SciDAC - the annual PI meeting has turned into what I would describe as the premier interdisciplinary computational science meeting, one of the best in the world. Doing interdisciplinary meetings is difficult because people tend to develop a focus for their particular subject area. But this is the fourth in the series; and since the first meeting in San Francisco, these conferences have been remarkably successful. For SciDAC-2 we also created an outreach magazine, SciDAC Review, which highlights scientific discovery as well as high-performance computing. It's been very successful in telling the non-practitioners what SciDAC and computational science are all about. The other new instrument in SciDAC-2 is an outreach center. As we go from computing at the terascale to computing at the petascale, we face the problem of narrowing our research community. The number of people who are `literate' enough to compute at the terascale is more than the number of those who can compute at the petascale. To address this problem, we established the SciDAC Outreach Center to bring people into the fold and educate them as to how we do SciDAC, how the teams are composed, and what it really means to compute at scale. The resources I have mentioned don't come for free. As part of the HECRTF law of 2005, Congress mandated that the Secretary would ensure that leadership-class facilities would be open to everyone across all agencies. So we took Congress at its word, and INCITE is our instrument for making allocations at the leadership-class facilities at Argonne and Oak Ridge, as well as smaller allocations at NERSC. Therefore, the selected proposals are very large projects that are computationally intensive, that compute at scale, and that have a high science impact. An important feature is that INCITE is completely open to anyone - there is no requirement of DOE Office of Science funding, and proposals are rigorously reviewed for both the science and the computational readiness. In 2008, more than 100 proposals were received, requesting about 600 million processor-hours. We allocated just over a quarter of a billion processor-hours. Astrophysics, materials science, lattice gauge theory, and high energy and nuclear physics were the major areas. These were the teams that were computationally ready for the big machines and that had significant science they could identify. In 2009, there will be a significant increase amount of time to be allocated, over half a billion processor-hours. The deadline is August 11 for new proposals and September 12 for renewals. We anticipate a significant increase in the number of requests this year. We expect you - as successful SciDAC centers, institutes, or partnerships - to compete for and win INCITE program allocation awards. If you have a successful SciDAC proposal, we believe it will make you successful in the INCITE review. We have the expectation that you will among those most prepared and most ready to use the machines and to compute at scale. Over the past 18 months, we have assembled a team to look across our computational science portfolio and to judge what are the 10 most significant science accomplishments. The ASCR office, as it goes forward with OMB, the new administration, and Congress, will be judged by the science we have accomplished. All of our proposals - such as for increasing SciDAC, increasing applied mathematics, and so on - are tied to what have we accomplished in science. And so these 10 big accomplishments are key to establishing credibility for new budget requests. Tony Mezzacappa, who chaired the committee, will also give a presentation on the ranking of these top 10, how they got there, and what the science is all about. Here is the list - numbers 2, 5, 6, 7, 9, and 10 are all SciDAC projects. RankTitle 1Modeling the Molecular Basis of Parkinson's Disease (Tsigelny) 2Discovery of the Standing Accretion Shock Instability and Pulsar Birth Mechanism in a Core-Collapse Supernova Evolution and Explosion (Blondin) 3Prediction and Design of Macromolecular Structures and Functions (Baker) 4Understanding How Lifted Flame Stabilized in a Hot Coflow (Yoo) 5New Insights from LCF-enabled Advanced Kinetic Simulations of Global Turbulence in Fusion Systems (Tang) 6High Transition Temperature Superconductivity: A High-Temperature Superconductive State and a Pairing Mechanism in 2-D Hubbard Model (Scalapino) 7 PETsc: Providing the Solvers for DOE High-Performance Simulations (Smith) 8 Via Lactea II, A Billion Particle Simulation of the Dark Matter Halo of the Milky Way (Madau) 9Probing the Properties of Water through Advanced Computing (Galli) 10First Provably Scalable Maxwell Solver Enables Scalable Electromagnetic Simulations (Kovel) So, what's the future going to look like for us? The office is putting together an initiative with the community, which we call the E3 Initiative. We're looking for a 10-year horizon for what's going to happen. Through the series of town hall meetings, which many of you participated in, we have produced a document on `Transforming Energy, the Environment and Science through simulations at the eXtreme Scale'; it can be found at http://www.science.doe.gov/ascr/ProgramDocuments/TownHall.pdf . We sometimes call it the Exascale initiative. Exascale computing is the gold-ring level of computing that seems just out of reach; but if we work hard and stretch, we just might be able to reach it. We envision that there will be a SciDAC-X, working at the extreme scale, with SciDAC teams that will perform and carry out science in the areas that will have a great societal impact, such as alternative fuels and transportation, combustion, climate, fusion science, high-energy physics, advanced fuel cycles, carbon management, and groundwater. We envision institutes for applied mathematics and computer science that probably will segue into algorithms because, at the extreme scale, we see the distinction between the applied math and the algorithm per se and its implementation in computer science as being inseparable. We envision an INCITE-X with multi-petaflop platforms, perhaps even exaflop computing resources. ESnet will be best in class - our 10-year plan calls for having 400 terabits per second capacity available in dual rings around the country, an enormously fast data communications network for moving large amounts of data. In looking at where we've been and where we are going, we can see that the gigaflops and teraflops era was a regime where we were following Moore's law through advances in clock speed. In the current regime, we're introducing massive parallelism, which I think is exemplified by Intel's announcement of their teraflop chip, where they envision more than a thousand cores on a chip. But in order to reach exascale, extrapolations talk about machines that require 100 megawatts of power in terms of current architectures. It's clearly going to require novel architectures, things we have perhaps not yet envisioned. It is of course an era of challenge. There will be an unpredictable evolution of hardware if we are to reach the exascale; and there will clearly be multilevel heterogeneous parallelism, including multilevel memory hierarchies. We have no idea right now as to the programming models needed to execute at such an extreme scale. We have been incredibly successful at the petascale - we know that already. Managing data and just getting communications to scale is an enormous challenge. And it's not just the extreme scaling. It's the rapid increase in complexity that represents the challenge. Let me end with a metaphor. In previous meetings we have talked about the road to petascale. Indeed, we have seen in hindsight that it was a road well traveled. But perhaps the road to exascale is not a road at all. Perhaps the metaphor will be akin to scaling the south face of K2. That's clearly not something all of us will be able to do, and probably computing at the exascale is not something all of us will do. But if we achieve that goal, perhaps the words of Emily Dickinson will best summarize where we will be. Perhaps in her words, looking backward and down, you will say: I climb the `Hill of Science' I view the landscape o'er; Such transcendental prospect I ne'er beheld before!

Data management and its role in delivering science at DOE BES user facilities - Past, Present, and Future

NASA Astrophysics Data System (ADS)

Miller, Stephen D.; Herwig, Kenneth W.; Ren, Shelly; Vazhkudai, Sudharshan S.; Jemian, Pete R.; Luitz, Steffen; Salnikov, Andrei A.; Gaponenko, Igor; Proffen, Thomas; Lewis, Paul; Green, Mark L.

2009-07-01

The primary mission of user facilities operated by Basic Energy Sciences under the Department of Energy is to produce data for users in support of open science and basic research [1]. We trace back almost 30 years of history across selected user facilities illustrating the evolution of facility data management practices and how these practices have related to performing scientific research. The facilities cover multiple techniques such as X-ray and neutron scattering, imaging and tomography sciences. Over time, detector and data acquisition technologies have dramatically increased the ability to produce prolific volumes of data challenging the traditional paradigm of users taking data home upon completion of their experiments to process and publish their results. During this time, computing capacity has also increased dramatically, though the size of the data has grown significantly faster than the capacity of one's laptop to manage and process this new facility produced data. Trends indicate that this will continue to be the case for yet some time. Thus users face a quandary for how to manage today's data complexity and size as these may exceed the computing resources users have available to themselves. This same quandary can also stifle collaboration and sharing. Realizing this, some facilities are already providing web portal access to data and computing thereby providing users access to resources they need [2]. Portal based computing is now driving researchers to think about how to use the data collected at multiple facilities in an integrated way to perform their research, and also how to collaborate and share data. In the future, inter-facility data management systems will enable next tier cross-instrument-cross facility scientific research fuelled by smart applications residing upon user computer resources. We can learn from the medical imaging community that has been working since the early 1990's to integrate data from across multiple modalities to achieve better diagnoses [3] - similarly, data fusion across BES facilities will lead to new scientific discoveries.

Earth Science Informatics Community Requirements for Improving Sustainable Science Software Practices: User Perspectives and Implications for Organizational Action

NASA Astrophysics Data System (ADS)

Downs, R. R.; Lenhardt, W. C.; Robinson, E.

2014-12-01

Science software is integral to the scientific process and must be developed and managed in a sustainable manner to ensure future access to scientific data and related resources. Organizations that are part of the scientific enterprise, as well as members of the scientific community who work within these entities, can contribute to the sustainability of science software and to practices that improve scientific community capabilities for science software sustainability. As science becomes increasingly digital and therefore, dependent on software, improving community practices for sustainable science software will contribute to the sustainability of science. Members of the Earth science informatics community, including scientific data producers and distributers, end-user scientists, system and application developers, and data center managers, use science software regularly and face the challenges and the opportunities that science software presents for the sustainability of science. To gain insight on practices needed for the sustainability of science software from the science software experiences of the Earth science informatics community, an interdisciplinary group of 300 community members were asked to engage in simultaneous roundtable discussions and report on their answers to questions about the requirements for improving scientific software sustainability. This paper will present an analysis of the issues reported and the conclusions offered by the participants. These results provide perspectives for science software sustainability practices and have implications for actions that organizations and their leadership can initiate to improve the sustainability of science software.

CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

NASA Astrophysics Data System (ADS)

Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

2012-12-01

The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and their multiple threats and stressors, 5) a continental margin modeling initiative, to capture extreme oceanic and atmospheric events generating turbidity currents in the Gulf of Mexico, and 6) a CZO Focus Research Group, to develop compatibility between CSDMS architecture and protocols and Critical Zone Observatory-developed models and data.

Science education and worldview

NASA Astrophysics Data System (ADS)

Keane, Moyra

2008-09-01

Is there a place for Indigenous Knowledge in the science curriculum for a Zulu community in rural Kwa-Zulu Natal, South Africa? This article argues "yes," based on a participative research and development project that discovered relevant science learning in a Zulu community. Among community concerns for relevant factual and performative knowledge, we found that culture and worldview are critical to community identity, to visioning educational outcomes, and to learning in school science. Cultural practices may contribute to pedagogy and curriculum; curriculum, in turn, may affirm cultural practices. Further, worldview needs to be understood as an aspect of knowledge creation. By understanding key aspects of an African worldview, science educators can contribute to both meaningful science education and community well-being. By fostering culture and worldview, a rural community can make a unique contribution to science education.

The American Indian Summer Institute in Earth System Science (AISESS) at UC Irvine: A Two-Week Residential Summer Program for High School Students

NASA Astrophysics Data System (ADS)

Johnson, K. R.; Polequaptewa, N.; Leon, Y.

2012-12-01

Native Americans remain severely underrepresented in the geosciences, despite a clear need for qualified geoscience professionals within Tribal communities to address critical issues such as natural resource and land management, water and air pollution, and climate change. In addition to the need for geoscience professionals within Tribal communities, increased participation of Native Americans in the geosciences would enhance the overall diversity of perspectives represented within the Earth science community and lead to improved Earth science literacy within Native communities. To address this need, the Department of Earth System Science and the American Indian Resource Program at the University California have organized a two-week residential American Indian Summer Institute in Earth System Science (AISESS) for high-school students (grades 9-12) from throughout the nation. The format of the AISESS program is based on the highly-successful framework of a previous NSF Funded American Indian Summer Institute in Computer Science (AISICS) at UC Irvine and involves key senior personnel from the AISICS program. The AISESS program, however, incorporates a week of camping on the La Jolla Band of Luiseño Indians reservation in Northern San Diego County, California. Following the week of camping and field projects, the students spend a week on the campus of UC Irvine participating in Earth System Science lectures, laboratory activities, and tours. The science curriculum is closely woven together with cultural activities, native studies, and communication skills programs The program culminates with a closing ceremony during which students present poster projects on environmental issues relevant to their tribal communities. The inaugural AISESS program took place from July 15th-28th, 2012. We received over 100 applications from Native American high school students from across the nation. We accepted 40 students for the first year, of which 34 attended the program. The objective of the program is to introduce students to Earth System Science and, hopefully, inspire them to pursue Earth or Environmental Science degrees. Towards this end, we developed a fairly broad curriculum which will be presented here. Evaluation planning was conducted during the first quarter of 2012 during recruitment. A longitudinal database was established for the project to track college preparatory course-taking, GPA, school attendance, participation in earth science activities, and attitudes and interest in attending college and completing a degree after high school. Based on attendance during AISESS, schools and students will be selected as descriptive case studies. A pre-post design for evaluating the Summer Institute includes a survey about student background, attitudes, and knowledge about preparing to complete high school and attend college after graduation and focus groups of participants immediately after the Institute to capture qualitative data about their experiences in the field and at the University. Initial evaluation results will be presented here.

Building a Culture of Health Informatics Innovation and Entrepreneurship: A New Frontier.

PubMed

Househ, Mowafa; Alshammari, Riyad; Almutairi, Mariam; Jamal, Amr; Alshoaib, Saleh

2015-01-01

Entrepreneurship and innovation within the health informatics (HI) scientific community are relatively sluggish when compared to other disciplines such as computer science and engineering. Healthcare in general, and specifically, the health informatics scientific community needs to embrace more innovative and entrepreneurial practices. In this paper, we explore the concepts of innovation and entrepreneurship as they apply to the health informatics scientific community. We also outline several strategies to improve the culture of innovation and entrepreneurship within the health informatics scientific community such as: (I) incorporating innovation and entrepreneurship in health informatics education; (II) creating strong linkages with industry and healthcare organizations; (III) supporting national health innovation and entrepreneurship competitions; (IV) creating a culture of innovation and entrepreneurship within healthcare organizations; (V) developing health informatics policies that support innovation and entrepreneurship based on internationally recognized standards; and (VI) develop an health informatics entrepreneurship ecosystem. With these changes, we conclude that embracing health innovation and entrepreneurship may be more readily accepted over the long-term within the health informatics scientific community.

Scientific Discovery through Advanced Computing in Plasma Science

NASA Astrophysics Data System (ADS)

Tang, William

2005-03-01

Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of plasma turbulence in magnetically-confined high temperature plasmas. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to the computational science area.

Gender differences in the use of computers, programming, and peer interactions in computer science classrooms

NASA Astrophysics Data System (ADS)

Stoilescu, Dorian; Egodawatte, Gunawardena

2010-12-01

Research shows that female and male students in undergraduate computer science programs view computer culture differently. Female students are interested more in the use of computers than in doing programming, whereas male students see computer science mainly as a programming activity. The overall purpose of our research was not to find new definitions for computer science culture but to see how male and female students see themselves involved in computer science practices, how they see computer science as a successful career, and what they like and dislike about current computer science practices. The study took place in a mid-sized university in Ontario. Sixteen students and two instructors were interviewed to get their views. We found that male and female views are different on computer use, programming, and the pattern of student interactions. Female and male students did not have any major issues in using computers. In computing programming, female students were not so involved in computing activities whereas male students were heavily involved. As for the opinions about successful computer science professionals, both female and male students emphasized hard working, detailed oriented approaches, and enjoying playing with computers. The myth of the geek as a typical profile of successful computer science students was not found to be true.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

NASA Astrophysics Data System (ADS)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.

Geospatial Data as a Service: Towards planetary scale real-time analytics

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Larraondo, P. R.; Antony, J.; Richards, C. J.

2017-12-01

The rapid growth of earth systems, environmental and geophysical datasets poses a challenge to both end-users and infrastructure providers. For infrastructure and data providers, tasks like managing, indexing and storing large collections of geospatial data needs to take into consideration the various use cases by which consumers will want to access and use the data. Considerable investment has been made by the Earth Science community to produce suitable real-time analytics platforms for geospatial data. There are currently different interfaces that have been defined to provide data services. Unfortunately, there is considerable difference on the standards, protocols or data models which have been designed to target specific communities or working groups. The Australian National University's National Computational Infrastructure (NCI) is used for a wide range of activities in the geospatial community. Earth observations, climate and weather forecasting are examples of these communities which generate large amounts of geospatial data. The NCI has been carrying out significant effort to develop a data and services model that enables the cross-disciplinary use of data. Recent developments in cloud and distributed computing provide a publicly accessible platform where new infrastructures can be built. One of the key components these technologies offer is the possibility of having "limitless" compute power next to where the data is stored. This model is rapidly transforming data delivery from centralised monolithic services towards ubiquitous distributed services that scale up and down adapting to fluctuations in the demand. NCI has developed GSKY, a scalable, distributed server which presents a new approach for geospatial data discovery and delivery based on OGC standards. We will present the architecture and motivating use-cases that drove GSKY's collaborative design, development and production deployment. We show our approach offers the community valuable exploratory analysis capabilities, for dealing with petabyte-scale geospatial data collections.

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

NASA Astrophysics Data System (ADS)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Zooniverse - Real science online with more than a million people. (Invited)

NASA Astrophysics Data System (ADS)

Smith, A.; Lynn, S.; Lintott, C.; Whyte, L.; Borden, K. A.

2013-12-01

The Zooniverse (zooniverse.org) began in 2007 with the launch of Galaxy Zoo, a project in which more than 175,000 people provided shape analyses of more than 1 million galaxy images sourced from the Sloan Digital Sky Survey. These galaxy 'classifications', some 60 million in total, have since been used to produce more than 50 peer-reviewed publications based not only on the original research goals of the project but also because of serendipitous discoveries made by the volunteer community. Based upon the success of Galaxy Zoo the team have gone on to develop more than 25 web-based citizen science projects, all with a strong research focus in a range of subjects from astronomy to zoology where human-based analysis still exceeds that of machine intelligence. Over the past 6 years Zooniverse projects have collected more than 300 million data analyses from over 1 million volunteers providing fantastically rich datasets for not only the individuals working to produce research from their project but also the machine learning and computer vision research communities. This talk will focus on the core 'method' by which Zooniverse projects are developed and lessons learned by the Zooniverse team developing citizen science projects across a range of disciplines.

Fort Collins Science Center: Species and Habitats of Federal Interest

USGS Publications Warehouse

Stevens, Patty

2004-01-01

Ecosystem changes directly affect a wide variety of plant and animal species, floral and faunal communities, and groups of species such as amphibians and grassland birds. Appropriate management of public lands plays a crucial role in the conservation and recovery of endangered species and can be a key element in preventing a species from being listed under the Endangered Species Act. The Species and Habitats of Federal Interest Branch of the Fort Collins Science Center (FORT) conducts research on the ecology, habitat requirements, distribution and abundance, population dynamics, and genetics and systematics of many species facing threatened or endangered status or of special concern to resource management agencies. FORT scientists develop reintroduction and restoration techniques, technologies for monitoring populations, and novel methods to analyze data on population trends and habitat requirements. FORT expertise encompasses both traditional and specialized natural resource disciplines within wildlife biology, including population dynamics, animal behavior, plant and community ecology, inventory and monitoring, statistics and computer applications, conservation genetics, stable isotope analysis, and curatorial expertise.

Operating a production pilot factory serving several scientific domains

NASA Astrophysics Data System (ADS)

Sfiligoi, I.; Würthwein, F.; Andrews, W.; Dost, J. M.; MacNeill, I.; McCrea, A.; Sheripon, E.; Murphy, C. W.

2011-12-01

Pilot infrastructures are becoming prominent players in the Grid environment. One of the major advantages is represented by the reduced effort required by the user communities (also known as Virtual Organizations or VOs) due to the outsourcing of the Grid interfacing services, i.e. the pilot factory, to Grid experts. One such pilot factory, based on the glideinWMS pilot infrastructure, is being operated by the Open Science Grid at University of California San Diego (UCSD). This pilot factory is serving multiple VOs from several scientific domains. Currently the three major clients are the analysis operations of the HEP experiment CMS, the community VO HCC, which serves mostly math, biology and computer science users, and the structural biology VO NEBioGrid. The UCSD glidein factory allows the served VOs to use Grid resources distributed over 150 sites in North and South America, in Europe, and in Asia. This paper presents the steps taken to create a production quality pilot factory, together with the challenges encountered along the road.

Data Crosscutting Requirements Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleese van Dam, Kerstin; Shoshani, Arie; Plata, Charity

2013-04-01

In April 2013, a diverse group of researchers from the U.S. Department of Energy (DOE) scientific community assembled to assess data requirements associated with DOE-sponsored scientific facilities and large-scale experiments. Participants in the review included facilities staff, program managers, and scientific experts from the offices of Basic Energy Sciences, Biological and Environmental Research, High Energy Physics, and Advanced Scientific Computing Research. As part of the meeting, review participants discussed key issues associated with three distinct aspects of the data challenge: 1) processing, 2) management, and 3) analysis. These discussions identified commonalities and differences among the needs of varied scientific communities.more » They also helped to articulate gaps between current approaches and future needs, as well as the research advances that will be required to close these gaps. Moreover, the review provided a rare opportunity for experts from across the Office of Science to learn about their collective expertise, challenges, and opportunities. The "Data Crosscutting Requirements Review" generated specific findings and recommendations for addressing large-scale data crosscutting requirements.« less

RIACS

NASA Technical Reports Server (NTRS)

Moore, Robert C.

1998-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. Research is carried out by a staff of full-time scientist,augmented by visitors, students, post doctoral candidates and visiting university faculty. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: Automated Reasoning. Human-Centered Computing. and High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

The ACI-REF Program: Empowering Prospective Computational Researchers

NASA Astrophysics Data System (ADS)

Cuma, M.; Cardoen, W.; Collier, G.; Freeman, R. M., Jr.; Kitzmiller, A.; Michael, L.; Nomura, K. I.; Orendt, A.; Tanner, L.

2014-12-01

The ACI-REF program, Advanced Cyberinfrastructure - Research and Education Facilitation, represents a consortium of academic institutions seeking to further advance the capabilities of their respective campus research communities through an extension of the personal connections and educational activities that underlie the unique and often specialized cyberinfrastructure at each institution. This consortium currently includes Clemson University, Harvard University, University of Hawai'i, University of Southern California, University of Utah, and University of Wisconsin. Working together in a coordinated effort, the consortium is dedicated to the adoption of models and strategies which leverage the expertise and experience of its members with a goal of maximizing the impact of each institution's investment in research computing. The ACI-REFs (facilitators) are tasked with making connections and building bridges between the local campus researchers and the many different providers of campus, commercial, and national computing resources. Through these bridges, ACI-REFs assist researchers from all disciplines in understanding their computing and data needs and in mapping these needs to existing capabilities or providing assistance with development of these capabilities. From the Earth sciences perspective, we will give examples of how this assistance improved methods and workflows in geophysics, geography and atmospheric sciences. We anticipate that this effort will expand the number of researchers who become self-sufficient users of advanced computing resources, allowing them to focus on making research discoveries in a more timely and efficient manner.

Enabling the transition towards Earth Observation Science 2.0

NASA Astrophysics Data System (ADS)

Mathieu, Pierre-Philippe; Desnos, Yves-Louis

2015-04-01

Science 2.0 refers to the rapid and systematic changes in doing Research and organising Science driven by the rapid advances in ICT and digital technologies combined with a growing demand to do Science for Society (actionable research) and in Society (co-design of knowledge). Nowadays, teams of researchers around the world can easily access a wide range of open data across disciplines and remotely process them on the Cloud, combining them with their own data to generate knowledge, develop information products for societal applications, and tackle complex integrative complex problems that could not be addressed a few years ago. Such rapid exchange of digital data is fostering a new world of data-intensive research, characterized by openness, transparency, and scrutiny and traceability of results, access to large volume of complex data, availability of community open tools, unprecedented level of computing power, and new collaboration among researchers and new actors such as citizen scientists. The EO scientific community is now facing the challenge of responding to this new paradigm in science 2.0 in order to make the most of the large volume of complex and diverse data delivered by the new generation of EO missions, and in particular the Sentinels. In this context, ESA - in particular within the framework of the Scientific Exploitation of Operational Missions (SEOM) element - is supporting a variety of activities in partnership with research communities to ease the transition and make the most of the data. These include the generation of new open tools and exploitation platforms, exploring new ways to exploit data on cloud-based platforms, dissiminate data, building new partnership with citizen scientists, and training the new generation of data scientists. The paper will give a brief overview of some of ESA activities aiming to facilitate the exploitation of large amount of data from EO missions in a collaborative, cross-disciplinary, and open way, from science to applications and education.

The Quake-Catcher Network: Improving Earthquake Strong Motion Observations Through Community Engagement

NASA Astrophysics Data System (ADS)

Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Chung, A. I.; Neighbors, C.; Saltzman, J.

2010-12-01

The Quake-Catcher Network (QCN) involves the community in strong motion data collection by utilizing volunteer computing techniques and low-cost MEMS accelerometers. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers can be attached to a desktop computer via USB and are internal to many laptops. Preliminary shake table tests show the MEMS accelerometers can record high-quality seismic data with instrument response similar to research-grade strong-motion sensors. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1500 stations worldwide. We also recently tested whether sensors could be quickly deployed as part of a Rapid Aftershock Mobilization Program (RAMP) following the 2010 M8.8 Maule, Chile earthquake. Volunteers are recruited through media reports, web-based sensor request forms, as well as social networking sites. Using data collected to date, we examine whether a distributed sensing network can provide valuable seismic data for earthquake detection and characterization while promoting community participation in earthquake science. We utilize client-side triggering algorithms to determine when significant ground shaking occurs and this metadata is sent to the main QCN server. On average, trigger metadata are received within 1-10 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. When triggers are detected, we determine if the triggers correlate to others in the network using spatial and temporal clustering of incoming trigger information. If a minimum number of triggers are detected then a QCN-event is declared and an initial earthquake location and magnitude is estimated. Initial analysis suggests that the estimated locations and magnitudes are similar to those reported in regional and global catalogs. As the network expands, it will become increasingly important to provide volunteers access to the data they collect, both to encourage continued participation in the network and to improve community engagement in scientific discourse related to seismic hazard. In the future, we hope to provide access to both images and raw data from seismograms in formats accessible to the general public through existing seismic data archives (e.g. IRIS, SCSN) and/or through the QCN project website. While encouraging community participation in seismic data collection, we can extend the capabilities of existing seismic networks to rapidly detect and characterize strong motion events. In addition, the dense waveform observations may provide high-resolution ground shaking information to improve source imaging and seismic risk assessment.

Some Thoughts Regarding Practical Quantum Computing

NASA Astrophysics Data System (ADS)

Ghoshal, Debabrata; Gomez, Richard; Lanzagorta, Marco; Uhlmann, Jeffrey

2006-03-01

Quantum computing has become an important area of research in computer science because of its potential to provide more efficient algorithmic solutions to certain problems than are possible with classical computing. The ability of performing parallel operations over an exponentially large computational space has proved to be the main advantage of the quantum computing model. In this regard, we are particularly interested in the potential applications of quantum computers to enhance real software systems of interest to the defense, industrial, scientific and financial communities. However, while much has been written in popular and scientific literature about the benefits of the quantum computational model, several of the problems associated to the practical implementation of real-life complex software systems in quantum computers are often ignored. In this presentation we will argue that practical quantum computation is not as straightforward as commonly advertised, even if the technological problems associated to the manufacturing and engineering of large-scale quantum registers were solved overnight. We will discuss some of the frequently overlooked difficulties that plague quantum computing in the areas of memories, I/O, addressing schemes, compilers, oracles, approximate information copying, logical debugging, error correction and fault-tolerant computing protocols.

Is chess the drosophila of artificial intelligence? A social history of an algorithm.

PubMed

Ensmenger, Nathan

2012-02-01

Since the mid 1960s, researchers in computer science have famously referred to chess as the 'drosophila' of artificial intelligence (AI). What they seem to mean by this is that chess, like the common fruit fly, is an accessible, familiar, and relatively simple experimental technology that nonetheless can be used productively to produce valid knowledge about other, more complex systems. But for historians of science and technology, the analogy between chess and drosophila assumes a larger significance. As Robert Kohler has ably described, the decision to adopt drosophila as the organism of choice for genetics research had far-reaching implications for the development of 20th century biology. In a similar manner, the decision to focus on chess as the measure of both human and computer intelligence had important and unintended consequences for AL research. This paper explores the emergence of chess as an experimental technology, its significance in the developing research practices of the AI community, and the unique ways in which the decision to focus on chess shaped the program of AI research in the decade of the 1970s. More broadly, it attempts to open up the virtual black box of computer software--and of computer games in particular--to the scrutiny of historical and sociological analysis.

Evolution of the ATLAS PanDA workload management system for exascale computational science

NASA Astrophysics Data System (ADS)

Maeno, T.; De, K.; Klimentov, A.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Schovancova, J.; Vaniachine, A.; Wenaus, T.; Yu, D.; Atlas Collaboration

2014-06-01

An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of other data intensive scientific applications. Alpha-Magnetic Spectrometer [4], an astro-particle experiment on the International Space Station, and the Compact Muon Solenoid [5], an LHC experiment, have successfully evaluated PanDA and are pursuing its adoption. In this paper, a description of the new program of work to develop a generic version of PanDA will be given, as well as the progress in extending PanDA's capabilities to support supercomputers and clouds and to leverage intelligent networking. PanDA has demonstrated at a very large scale the value of automated dynamic brokering of diverse workloads across distributed computing resources. The next generation of PanDA will allow other data-intensive sciences and a wider exascale community employing a variety of computing platforms to benefit from ATLAS' experience and proven tools.

Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will involve the further integration and analysis of this data across the social sciences to facilitate the impacts across the societal domain, including timely analysis to more accurately predict and forecast future climate and environmental state.

Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansmann, Ulrich H.E.

2012-07-02

This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previousmore » years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.« less

Engineering brain-computer interfaces: past, present and future.

PubMed

Hughes, M A

2014-06-01

Electricity governs the function of both nervous systems and computers. Whilst ions move in polar fluids to depolarize neuronal membranes, electrons move in the solid-state lattices of microelectronic semiconductors. Joining these two systems together, to create an iono-electric brain-computer interface, is an immense challenge. However, such interfaces offer (and in select clinical contexts have already delivered) a method of overcoming disability caused by neurological or musculoskeletal pathology. To fulfill their theoretical promise, several specific challenges demand consideration. Rate-limiting steps cover a diverse range of disciplines including microelectronics, neuro-informatics, engineering, and materials science. As those who work at the tangible interface between brain and outside world, neurosurgeons are well placed to contribute to, and inform, this cutting edge area of translational research. This article explores the historical background, status quo, and future of brain-computer interfaces; and outlines the challenges to progress and opportunities available to the clinical neurosciences community.

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

DOE PAGES

Bethel, EW; Bauer, A; Abbasi, H; ...

2016-06-10

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitionersmore » using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.« less

Coordinating Communities and Building Governance in the Development of Schematic and Semantic Standards: the Key to Solving Global Earth and Space Science Challenges in the 21st Century.

NASA Astrophysics Data System (ADS)

Wyborn, L. A.

2007-12-01

The Information Age in Science is being driven partly by the data deluge as exponentially growing volumes of data are being generated by research. Such large volumes of data cannot be effectively processed by humans and efficient and timely processing by computers requires development of specific machine readable formats. Further, as key challenges in earth and space sciences, such as climate change, hazard prediction and sustainable development resources require a cross disciplinary approach, data from various domains will need to be integrated from globally distributed sources also via machine to machine formats. However, it is becoming increasingly apparent that the existing standards can be very domain specific and most existing data transfer formats require human intervention. Where groups from different communities do try combine data across the domain/discipline boundaries much time is spent reformatting and reorganizing the data and it is conservatively estimated that this can take 80% of a project's time and resources. Four different types of standards are required for machine to machine interaction: systems, syntactic, schematic and semantic. Standards at the systems (WMS, WFS, etc) and at the syntactic level (GML, Observation and Measurement, SensorML) are being developed through international standards bodies such as ISO, OGC, W3C, IEEE etc. In contrast standards at the schematic level (e.g., GeoSciML, LandslidesML, WaterML, QuakeML) and at the semantic level (ie ontologies and vocabularies) are currently developing rapidly, in a very uncoordinated way and with little governance. As the size of the community that can machine read each others data depends on the size of the community that has developed the schematic or semantic standards, it is essential that to achieve global integration of earth and space science data, the required standards need to be developed through international collaboration using accepted standard proceedures. Once developed the standards also require some form of governance to maintain and then extend the standard as the science evolves to meet new challenges. A standard that does have some governance is GeoSciML, a data transfer standard for geoscience map data. GeoSciML is currently being developed by a consortium of 7 countries under the auspices of the Commission for the Management of and Application of Geoscience Information (CGI), a commission of the International Union of Geological Sciences. Perhaps other `ML' or ontology and vocabulary development `teams' need to look to their international domain specific specialty societies for endorsement and governance. But the issue goes beyond Earth and Space Sciences, as increasingly cross and intra disciplinary science requires machine to machine interaction with other science disciplines such as physics, chemistry and astronomy. For example, for geochemistry do we develop GeochemistryML or do we extend the existing Chemical Markup Language? Again, the question is who will provide the coordination of the development of the required schematic and semantic standards that underpin machine to machine global integration of science data. Is this a role for ICSU or CODATA or who? In order to address this issue, Geoscience Australia and CSIRO established the Solid Earth and Environmental Grid Community website to enable communities to `advertise' standards development and to provide a community TWIKI where standards can be developed in a globally `open' environment.

Computational Aspects of Data Assimilation and the ESMF

NASA Technical Reports Server (NTRS)

daSilva, A.

2003-01-01

The scientific challenge of developing advanced data assimilation applications is a daunting task. Independently developed components may have incompatible interfaces or may be written in different computer languages. The high-performance computer (HPC) platforms required by numerically intensive Earth system applications are complex, varied, rapidly evolving and multi-part systems themselves. Since the market for high-end platforms is relatively small, there is little robust middleware available to buffer the modeler from the difficulties of HPC programming. To complicate matters further, the collaborations required to develop large Earth system applications often span initiatives, institutions and agencies, involve geoscience, software engineering, and computer science communities, and cross national borders.The Earth System Modeling Framework (ESMF) project is a concerted response to these challenges. Its goal is to increase software reuse, interoperability, ease of use and performance in Earth system models through the use of a common software framework, developed in an open manner by leaders in the modeling community. The ESMF addresses the technical and to some extent the cultural - aspects of Earth system modeling, laying the groundwork for addressing the more difficult scientific aspects, such as the physical compatibility of components, in the future. In this talk we will discuss the general philosophy and architecture of the ESMF, focussing on those capabilities useful for developing advanced data assimilation applications.

Review of the synergies between computational modeling and experimental characterization of materials across length scales

DOE PAGES

Dingreville, Rémi; Karnesky, Richard A.; Puel, Guillaume; ...

2015-11-16

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends in which predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure–property relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanicsmore » community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to “simply” support experimental work. This is illustrated by examples from several application areas on structural materials. In conclusion this manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.« less

Exploring the Relationships between Self-Efficacy and Preference for Teacher Authority among Computer Science Majors

ERIC Educational Resources Information Center

Lin, Che-Li; Liang, Jyh-Chong; Su, Yi-Ching; Tsai, Chin-Chung

2013-01-01

Teacher-centered instruction has been widely adopted in college computer science classrooms and has some benefits in training computer science undergraduates. Meanwhile, student-centered contexts have been advocated to promote computer science education. How computer science learners respond to or prefer the two types of teacher authority,…

Virtual school teacher's science efficacy beliefs: The effects of community of practice on science-teaching efficacy beliefs

NASA Astrophysics Data System (ADS)

Uzoff, Phuong Pham

The purpose of this study was to examine how much K-12 science teachers working in a virtual school experience a community of practice and how that experience affects personal science-teaching efficacy and science-teaching outcome expectancy. The study was rooted in theoretical frameworks from Lave and Wenger's (1991) community of practice and Bandura's (1977) self-efficacy beliefs. The researcher used three surveys to examine schoolteachers' experiences of a community of practice and science-teaching efficacy beliefs. The instrument combined Mangieri's (2008) virtual teacher demographic survey, Riggs and Enochs (1990) Science-teaching efficacy Beliefs Instrument-A (STEBI-A), and Cadiz, Sawyer, and Griffith's (2009) Experienced Community of Practice (eCoP) instrument. The results showed a significant linear statistical relationship between the science teachers' experiences of community of practice and personal science-teaching efficacy. In addition, the study found that there was also a significant linear statistical relationship between teachers' community of practice experiences and science-teaching outcome expectancy. The results from this study were in line with numerous studies that have found teachers who are involved in a community of practice report higher science-teaching efficacy beliefs (Akerson, Cullen, & Hanson, 2009; Fazio, 2009; Lakshmanan, Heath, Perlmutter, & Elder, 2011; Liu, Lee, & Lin, 2010; Sinclair, Naizer, & Ledbetter, 2010). The researcher concluded that school leaders, policymakers, and researchers should increase professional learning opportunities that are grounded in social constructivist theoretical frameworks in order to increase teachers' science efficacy.

Applying Game Thinking to Slips, Trips and Falls Prevention.

PubMed

Dewick, Paul; Stanmore, Emma

2017-01-01

Gamification is about the way in which 'game thinking' can engage participants and change behaviours in real, non-game contexts. This paper explores how game thinking can be applied to help prevent slips, trips and falls (STF), which are the largest cause of accidental death in older people across Europe. The paper contributes to the assistive technology, digital health and computer science/human behaviour communities by responding to a gap in the literature for papers detailing the innovation process of developing interventions to improve health and quality of life. The aim of the paper is of interest to the many stakeholders involved in enabling older people to live independent, confident, healthy and safe lives in the community.

Enabling Extreme Scale Earth Science Applications at the Oak Ridge Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Mozdzynski, G.; Hamrud, M.; Deconinck, W.; Smith, L.; Hack, J.

2014-12-01

The Oak Ridge Leadership Facility (OLCF), established at the Oak Ridge National Laboratory (ORNL) under the auspices of the U.S. Department of Energy (DOE), welcomes investigators from universities, government agencies, national laboratories and industry who are prepared to perform breakthrough research across a broad domain of scientific disciplines, including earth and space sciences. Titan, the OLCF flagship system, is currently listed as #2 in the Top500 list of supercomputers in the world, and the largest available for open science. The computational resources are allocated primarily via the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program, sponsored by the U.S. DOE Office of Science. In 2014, over 2.25 billion core hours on Titan were awarded via INCITE projects., including 14% of the allocation toward earth sciences. The INCITE competition is also open to research scientists based outside the USA. In fact, international research projects account for 12% of the INCITE awards in 2014. The INCITE scientific review panel also includes 20% participation from international experts. Recent accomplishments in earth sciences at OLCF include the world's first continuous simulation of 21,000 years of earth's climate history (2009); and an unprecedented simulation of a magnitude 8 earthquake over 125 sq. miles. One of the ongoing international projects involves scaling the ECMWF Integrated Forecasting System (IFS) model to over 200K cores of Titan. ECMWF is a partner in the EU funded Collaborative Research into Exascale Systemware, Tools and Applications (CRESTA) project. The significance of the research carried out within this project is the demonstration of techniques required to scale current generation Petascale capable simulation codes towards the performance levels required for running on future Exascale systems. One of the techniques pursued by ECMWF is to use Fortran2008 coarrays to overlap computations and communications and to reduce the total volume of data communicated. Use of Titan has enabled ECMWF to plan future scalability developments and resource requirements. We will also discuss the best practices developed over the years in navigating logistical, legal and regulatory hurdles involved in supporting the facility's diverse user community.

Van Allen Probes Science Gateway: Single-Point Access to Long-Term Radiation Belt Measurements and Space Weather Nowcasting

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Ukhorskiy, A. Y.; Sotirelis, T.; Stephens, G.

2017-12-01

The Science Gateway gives single-point access to over 4.5 years of comprehensive wave and particle measurements from the Van Allen Probes NASA twin-spacecraft mission. The Gateway provides a set of visualization and data analysis tools including: HTML5-based interactive visualization of high-level data products from all instrument teams in the form of: line plots, orbital content plots, dynamical energy spectra, L-shell context plots (including two-spacecraft plotting), FFT spectra of wave data, solar wind and geomagnetic indices data, etc.; download custom multi-instrument CDF data files of selected data products; publication quality plots of digital data; combined orbit predicts for mission planning and coordination including: Van Allen Probes, MMS, THEMIS, Arase (ERG), Cluster, GOES, Geotail, FIREBIRD; magnetic footpoint calculator for coordination with LEO and ground-based assets; real-time computation and processing of empirical magnetic field models - computation of magnetic ephemeris, computation of adiabatic invariants. Van Allen Probes is the first spacecraft mission to provide a nowcast of the radiation environment in the heart of the radiation belts, where the radiation levels are the highest and most dangerous for spacecraft operations. For this purpose, all instruments continuously broadcast a subset of their science data in real time. Van Allen Probes partners with four foreign institutions who operate ground stations that receive the broadcast: Korea (KASI), the Czech republic (CAS), Argentina (CONAE), and Brazil (INPE). The SpWx broadcast is then collected at APL and delivered to the community via the Science Gateway.

Measuring mumbo jumbo: A preliminary quantification of the use of jargon in science communication.

PubMed

Sharon, Aviv J; Baram-Tsabari, Ayelet

2014-07-01

Leaders of the scientific community encourage scientists to learn effective science communication, including honing the skill to discuss science with little professional jargon. However, avoiding jargon is not trivial for scientists for several reasons, and this demands special attention in teaching and evaluation. Despite this, no standard measurement for the use of scientific jargon in speech has been developed to date. Here a standard yardstick for the use of scientific jargon in spoken texts, using a computational linguistics approach, is proposed. Analyzed transcripts included academic speech, scientific TEDTalks, and communication about the discovery of a Higgs-like boson at CERN. Findings suggest that scientists use less jargon in communication with a general audience than in communication with peers, but not always less obscure jargon. These findings may lay the groundwork for evaluating the use of jargon.

Youth Science Ambassadors: Connecting Indigenous communities with Ocean Networks Canada tools to inspire future ocean scientists and marine resource managers

NASA Astrophysics Data System (ADS)

Pelz, M.; Hoeberechts, M.; Hale, C.; McLean, M. A.

2017-12-01

This presentation describes Ocean Networks Canada's (ONC) Youth Science Ambassador Program. The Youth Science Ambassadors are a growing network of youth in Canadian coastal communities whose role is to connect ocean science, ONC data, and Indigenous knowledge. By directly employing Indigenous youth in communities in which ONC operates monitoring equipment, ONC aims to encourage wider participation and interest in ocean science and exploration. Further, the Youth Science Ambassadors act as role models and mentors to other local youth by highlighting connections between Indigenous and local knowledge and current marine science efforts. Ocean Networks Canada, an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. These include technologies developed on the world-leading NEPTUNE and VENUS observatories as well as community observatories in the Arctic and coastal British Columbia. These observatories, large and small, enable communities, users, scientists, teachers, and students to monitor real-time and historical data from the local marine environment from anywhere on the globe. Youth Science Ambassadors are part of the Learning and Engagement team whose role includes engaging Indigenous communities and schools in ocean science through ONC's K-12 Ocean Sense education program. All of the data collected by ONC are freely available over the Internet for non-profit use, including disaster planning, community-based decision making, and education. The Youth Science Ambassadors support collaboration with Indigenous communities and schools by facilitating educational programming, encouraging participation in ocean data collection and analysis, and fostering interest in ocean science. In addition, the Youth Science Ambassadors support community collaboration in decision-making for instrument deployment locations and identify ways in which ONC can help to address any areas of concern raised by the community. This presentation will share the successes and challenges of the Youth Science Ambassador program in engaging both rural and urban Indigenous communities. We will share activities and experiences, discuss how we have adapted to meet the needs of each community, and outline ideas we have for the future development of the program.

Two-Year Community: Construction with Scaffolds: Helping Community College Students Build Explanations

ERIC Educational Resources Information Center

Bennett, Steve; Gotwals, Amelia Wenk

2017-01-01

Science education reform documents call for students to learn science by engaging in inquiry and using science practices. One such science practice is constructing evidence-based explanations. Few students enter community college science classrooms having experience with, or being proficient in, using evidence to explain scientific phenomena.…

Academic computer science and gender: A naturalistic study investigating the causes of attrition

NASA Astrophysics Data System (ADS)

Declue, Timothy Hall

Far fewer women than men take computer science classes in high school, enroll in computer science programs in college, or complete advanced degrees in computer science. The computer science pipeline begins to shrink for women even before entering college, but it is at the college level that the "brain drain" is the most evident numerically, especially in the first class taken by most computer science majors called "Computer Science 1" or CS-I. The result, for both academia and industry, is a pronounced technological gender disparity in academic and industrial computer science. The study revealed the existence of several factors influencing success in CS-I. First, and most clearly, the effect of attribution processes seemed to be quite strong. These processes tend to work against success for females and in favor of success for males. Likewise, evidence was discovered which strengthens theories related to prior experience and the perception that computer science has a culture which is hostile to females. Two unanticipated themes related to the motivation and persistence of successful computer science majors. The findings did not support the belief that females have greater logistical problems in computer science than males, or that females tend to have a different programming style than males which adversely affects the females' ability to succeed in CS-I.

EUROPLANET-RI modelling service for the planetary science community: European Modelling and Data Analysis Facility (EMDAF)

NASA Astrophysics Data System (ADS)

Khodachenko, Maxim; Miller, Steven; Stoeckler, Robert; Topf, Florian

2010-05-01

Computational modeling and observational data analysis are two major aspects of the modern scientific research. Both appear nowadays under extensive development and application. Many of the scientific goals of planetary space missions require robust models of planetary objects and environments as well as efficient data analysis algorithms, to predict conditions for mission planning and to interpret the experimental data. Europe has great strength in these areas, but it is insufficiently coordinated; individual groups, models, techniques and algorithms need to be coupled and integrated. Existing level of scientific cooperation and the technical capabilities for operative communication, allow considerable progress in the development of a distributed international Research Infrastructure (RI) which is based on the existing in Europe computational modelling and data analysis centers, providing the scientific community with dedicated services in the fields of their computational and data analysis expertise. These services will appear as a product of the collaborative communication and joint research efforts of the numerical and data analysis experts together with planetary scientists. The major goal of the EUROPLANET-RI / EMDAF is to make computational models and data analysis algorithms associated with particular national RIs and teams, as well as their outputs, more readily available to their potential user community and more tailored to scientific user requirements, without compromising front-line specialized research on model and data analysis algorithms development and software implementation. This objective will be met through four keys subdivisions/tasks of EMAF: 1) an Interactive Catalogue of Planetary Models; 2) a Distributed Planetary Modelling Laboratory; 3) a Distributed Data Analysis Laboratory, and 4) enabling Models and Routines for High Performance Computing Grids. Using the advantages of the coordinated operation and efficient communication between the involved computational modelling, research and data analysis expert teams and their related research infrastructures, EMDAF will provide a 1) flexible, 2) scientific user oriented, 3) continuously developing and fast upgrading computational and data analysis service to support and intensify the European planetary scientific research. At the beginning EMDAF will create a set of demonstrators and operational tests of this service in key areas of European planetary science. This work will aim at the following objectives: (a) Development and implementation of tools for distant interactive communication between the planetary scientists and computing experts (including related RIs); (b) Development of standard routine packages, and user-friendly interfaces for operation of the existing numerical codes and data analysis algorithms by the specialized planetary scientists; (c) Development of a prototype of numerical modelling services "on demand" for space missions and planetary researchers; (d) Development of a prototype of data analysis services "on demand" for space missions and planetary researchers; (e) Development of a prototype of coordinated interconnected simulations of planetary phenomena and objects (global multi-model simulators); (f) Providing the demonstrators of a coordinated use of high performance computing facilities (super-computer networks), done in cooperation with European HPC Grid DEISA.

Alaska's Secondary Science Teachers and Students Receive Earth Systems Science Knowledge, GIS Know How and University Technical Support for Pre- College Research Experiences: The EDGE Project

NASA Astrophysics Data System (ADS)

Connor, C. L.; Prakash, A.

2007-12-01

Alaska's secondary school teachers are increasingly required to provide Earth systems science (ESS) education that integrates student observations of local natural processes related to rapid climate change with geospatial datasets and satellite imagery using Geographic Information Systems (GIS) technology. Such skills are also valued in various employment sectors of the state where job opportunities requiring Earth science and GIS training are increasing. University of Alaska's EDGE (Experiential Discoveries in Geoscience Education) program has provided training and classroom resources for 3 cohorts of inservice Alaska science and math teachers in GIS and Earth Systems Science (2005-2007). Summer workshops include geologic field experiences, GIS instruction, computer equipment and technical support for groups of Alaska high school (HS) and middle school (MS) science teachers each June and their students in August. Since 2005, EDGE has increased Alaska science and math teachers' Earth science content knowledge and developed their GIS and computer skills. In addition, EDGE has guided teachers using a follow-up, fall online course that provided more extensive ESS knowledge linked with classroom standards and provided course content that was directly transferable into their MS and HS science classrooms. EDGE teachers were mentored by University faculty and technical staff as they guided their own students through semester-scale, science fair style projects using geospatial data that was student- collected. EDGE program assessment indicates that all teachers have improved their ESS knowledge, GIS knowledge, and the use of technology in their classrooms. More than 230 middle school students have learned GIS, from EDGE teachers and 50 EDGE secondary students have conducted original research related to landscape change and its impacts on their own communities. Longer-term EDGE goals include improving student performance on the newly implemented (spring 2008) 10th grade, standards-based, High School Qualifying Exam, on recruiting first-generation college students, and on increasing the number of Earth science majors in the University of Alaska system.

Automated metadata--final project report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schissel, David

This report summarizes the work of the Automated Metadata, Provenance Cataloging, and Navigable Interfaces: Ensuring the Usefulness of Extreme-Scale Data Project (MPO Project) funded by the United States Department of Energy (DOE), Offices of Advanced Scientific Computing Research and Fusion Energy Sciences. Initially funded for three years starting in 2012, it was extended for 6 months with additional funding. The project was a collaboration between scientists at General Atomics, Lawrence Berkley National Laboratory (LBNL), and Massachusetts Institute of Technology (MIT). The group leveraged existing computer science technology where possible, and extended or created new capabilities where required. The MPO projectmore » was able to successfully create a suite of software tools that can be used by a scientific community to automatically document their scientific workflows. These tools were integrated into workflows for fusion energy and climate research illustrating the general applicability of the project’s toolkit. Feedback was very positive on the project’s toolkit and the value of such automatic workflow documentation to the scientific endeavor.« less

Information system evolution at the French National Network of Seismic Survey (BCSF-RENASS)

NASA Astrophysics Data System (ADS)

Engels, F.; Grunberg, M.

2013-12-01

The aging information system of the French National Network of Seismic Survey (BCSF-RENASS), located in Strasbourg (EOST), needed to be updated to satisfy new practices from Computer science world. The latter means to evolve our system at different levels : development method, datamining solutions, system administration. The new system had to provide more agility for incoming projects. The main difficulty was to maintain old system and the new one in parallel the time to validate new solutions with a restricted team. Solutions adopted here are coming from standards used by the seismological community and inspired by the state of the art of devops community. The new system is easier to maintain and take advantage of large community to find support. This poster introduces the new system and choosen solutions like Puppet, Fabric, MongoDB and FDSN Webservices.

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression Toward Type1 Diabetes

DTIC Science & Technology

2016-09-09

5Research Program Unit, Diabetes and Obesity , University of Helsinki, 00290 Helsinki, Finland 6Department of Information and Computer Science, Aalto...Figure 6C). Altered levels of serum triglycerides are a common feature of obesity and type 2 diabetes, and hypertriglyceridemia is (B) Shown is the...composition that may contribute to childhood disease, we must first investigate the normal dynamics of the community in the developing infant. Here

CASL Dakota Capabilities Summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Brian M.; Simmons, Chris; Williams, Brian J.

2017-10-10

The Dakota software project serves the mission of Sandia National Laboratories and supports a worldwide user community by delivering state-of-the-art research and robust, usable software for optimization and uncertainty quantification. These capabilities enable advanced exploration and riskinformed prediction with a wide range of computational science and engineering models. Dakota is the verification and validation (V&V) / uncertainty quantification (UQ) software delivery vehicle for CASL, allowing analysts across focus areas to apply these capabilities to myriad nuclear engineering analyses.

Internet-Based Software Tools for Analysis and Processing of LIDAR Point Cloud Data via the OpenTopography Portal

NASA Astrophysics Data System (ADS)

Nandigam, V.; Crosby, C. J.; Baru, C.; Arrowsmith, R.

2009-12-01

LIDAR is an excellent example of the new generation of powerful remote sensing data now available to Earth science researchers. Capable of producing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LIDAR data allows earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible, yet essential for their appropriate representation. Along with these high-resolution datasets comes an increase in the volume and complexity of data that the user must efficiently manage and process in order for it to be scientifically useful. Although there are expensive commercial LIDAR software applications available, processing and analysis of these datasets are typically computationally inefficient on the conventional hardware and software that is currently available to most of the Earth science community. We have designed and implemented an Internet-based system, the OpenTopography Portal, that provides integrated access to high-resolution LIDAR data as well as web-based tools for processing of these datasets. By using remote data storage and high performance compute resources, the OpenTopography Portal attempts to simplify data access and standard LIDAR processing tasks for the Earth Science community. The OpenTopography Portal allows users to access massive amounts of raw point cloud LIDAR data as well as a suite of DEM generation tools to enable users to generate custom digital elevation models to best fit their science applications. The Cyberinfrastructure software tools for processing the data are freely available via the portal and conveniently integrated with the data selection in a single user-friendly interface. The ability to run these tools on powerful Cyberinfrastructure resources instead of their own labs provides a huge advantage in terms of performance and compute power. The system also encourages users to explore data processing methods and the variations in algorithm parameters since all of the processing is done remotely and numerous jobs can be submitted in sequence. The web-based software also eliminates the need for users to deal with the hassles and costs associated with software installation and licensing while providing adequate disk space for storage and personal job archival capability. Although currently limited to data access and DEM generation tasks, the OpenTopography system is modular in design and can be modified to accommodate new processing tools as they become available. We are currently exploring implementation of higher-level DEM analysis tasks in OpenTopography, since such processing is often computationally intensive and thus lends itself to utilization of cyberinfrastructure. Products derived from OpenTopography processing are available in a variety of formats ranging from simple Google Earth visualizations of LIDAR-derived hillshades to various GIS-compatible grid formats. To serve community users less interested in data processing, OpenTopography also hosts 1 km^2 digital elevation model tiles as well as Google Earth image overlays for a synoptic view of the data.

Computer-Game Construction: A Gender-Neutral Attractor to Computing Science

ERIC Educational Resources Information Center

Carbonaro, Mike; Szafron, Duane; Cutumisu, Maria; Schaeffer, Jonathan

2010-01-01

Enrollment in Computing Science university programs is at a dangerously low level. A major reason for this is the general lack of interest in Computing Science by females. In this paper, we discuss our experience with using a computer game construction environment as a vehicle to encourage female participation in Computing Science. Experiments…

Search for Signatures of Life in the Solar System

NASA Astrophysics Data System (ADS)

Race, M.; Schwehm, G.; Arnould, J.; Dawson, S.; Devore, E.; Evans, D.; Ferrazzani, M.; Shostak, S.

The search for evidence of extraterrestrial life is an important scientific theme that fascinates the public and encourages interest in space exploration, both within the solar system and beyond. The rapid pace of mass media communication allows the public to share mission results and new discoveries almost simultaneously with the scientific community. The public can read about proposed sample return missions to Mars, listen as scientists debate about in situ exploration of the oceans on Europa, learn about the growing number of extrasolar planets, or use their personal computers to participate in searches for extraterrestrial intelligence (SETI). As the science community continues its multi-pronged efforts to detect evidence of extraterrestrial life, it must be mindful of more than just science and technology. It is important to understand public perceptions, misperceptions, beliefs, concerns and potential complications associated with the search for life beyond our home planet. This panel is designed to provide brief overviews of some important non-scientific areas with the potential to impact future astrobiological exploration. The presentations will be followed by open discussion and audience participation. Invited panelists and their topical areas include: SCIENCE FICTION AND MISPERCEPTIONS: Seth Shostak, Dylan EvansBattling Pseudo-Science, Hollywood and Alien Abductions LEGAL ISSUES: Marcus FerrazzaniLooming Complications for Future Missions and Exploration RISK COMMUNICATION: Sandra DawsonEngaging the Public, Explaining the Risks, and Encouraging Long-Term Interestin Mission Science EDUCATION: Edna DeVoreUsing the Search for Life as a Motivating Theme in Teaching Basic Science andCritical Thinking. ETHICAL ISSUES AND CONCERNS: Jacques ArnouldWhat Will it Mean if We Find "ET"? PANEL MODERATORS: Margaret Race, Gerhard Schwehm

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets

PubMed Central

McKinney, Bill; Meyer, Peter A.; Crosas, Mercè; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension—functionality supporting preservation of filesystem structure within Dataverse—which is essential for both in-place computation and supporting non-http data transfers. PMID:27862010

Virtual Labs (Science Gateways) as platforms for Free and Open Source Science

NASA Astrophysics Data System (ADS)

Lescinsky, David; Car, Nicholas; Fraser, Ryan; Friedrich, Carsten; Kemp, Carina; Squire, Geoffrey

2016-04-01

The Free and Open Source Software (FOSS) movement promotes community engagement in software development, as well as provides access to a range of sophisticated technologies that would be prohibitively expensive if obtained commercially. However, as geoinformatics and eResearch tools and services become more dispersed, it becomes more complicated to identify and interface between the many required components. Virtual Laboratories (VLs, also known as Science Gateways) simplify the management and coordination of these components by providing a platform linking many, if not all, of the steps in particular scientific processes. These enable scientists to focus on their science, rather than the underlying supporting technologies. We describe a modular, open source, VL infrastructure that can be reconfigured to create VLs for a wide range of disciplines. Development of this infrastructure has been led by CSIRO in collaboration with Geoscience Australia and the National Computational Infrastructure (NCI) with support from the National eResearch Collaboration Tools and Resources (NeCTAR) and the Australian National Data Service (ANDS). Initially, the infrastructure was developed to support the Virtual Geophysical Laboratory (VGL), and has subsequently been repurposed to create the Virtual Hazards Impact and Risk Laboratory (VHIRL) and the reconfigured Australian National Virtual Geophysics Laboratory (ANVGL). During each step of development, new capabilities and services have been added and/or enhanced. We plan on continuing to follow this model using a shared, community code base. The VL platform facilitates transparent and reproducible science by providing access to both the data and methodologies used during scientific investigations. This is further enhanced by the ability to set up and run investigations using computational resources accessed through the VL. Data is accessed using registries pointing to catalogues within public data repositories (notably including the NCI National Environmental Research Data Interoperability Platform), or by uploading data directly from user supplied addresses or files. Similarly, scientific software is accessed through registries pointing to software repositories (e.g., GitHub). Runs are configured by using or modifying default templates designed by subject matter experts. After the appropriate computational resources are identified by the user, Virtual Machines (VMs) are spun up and jobs are submitted to service providers (currently the NeCTAR public cloud or Amazon Web Services). Following completion of the jobs the results can be reviewed and downloaded if desired. By providing a unified platform for science, the VL infrastructure enables sophisticated provenance capture and management. The source of input data (including both collection and queries), user information, software information (version and configuration details) and output information are all captured and managed as a VL resource which can be linked to output data sets. This provenance resource provides a mechanism for publication and citation for Free and Open Source Science.

PREFACE: New trends in Computer Simulations in Physics and not only in physics

NASA Astrophysics Data System (ADS)

Shchur, Lev N.; Krashakov, Serge A.

2016-02-01

In this volume we have collected papers based on the presentations given at the International Conference on Computer Simulations in Physics and beyond (CSP2015), held in Moscow, September 6-10, 2015. We hope that this volume will be helpful and scientifically interesting for readers. The Conference was organized for the first time with the common efforts of the Moscow Institute for Electronics and Mathematics (MIEM) of the National Research University Higher School of Economics, the Landau Institute for Theoretical Physics, and the Science Center in Chernogolovka. The name of the Conference emphasizes the multidisciplinary nature of computational physics. Its methods are applied to the broad range of current research in science and society. The choice of venue was motivated by the multidisciplinary character of the MIEM. It is a former independent university, which has recently become the part of the National Research University Higher School of Economics. The Conference Computer Simulations in Physics and beyond (CSP) is planned to be organized biannually. This year's Conference featured 99 presentations, including 21 plenary and invited talks ranging from the analysis of Irish myths with recent methods of statistical physics, to computing with novel quantum computers D-Wave and D-Wave2. This volume covers various areas of computational physics and emerging subjects within the computational physics community. Each section was preceded by invited talks presenting the latest algorithms and methods in computational physics, as well as new scientific results. Both parallel and poster sessions paid special attention to numerical methods, applications and results. For all the abstracts presented at the conference please follow the link http://csp2015.ac.ru/files/book5x.pdf

Low Latency Workflow Scheduling and an Application of Hyperspectral Brightness Temperatures

NASA Astrophysics Data System (ADS)

Nguyen, P. T.; Chapman, D. R.; Halem, M.

2012-12-01

New system analytics for Big Data computing holds the promise of major scientific breakthroughs and discoveries from the exploration and mining of the massive data sets becoming available to the science community. However, such data intensive scientific applications face severe challenges in accessing, managing and analyzing petabytes of data. While the Hadoop MapReduce environment has been successfully applied to data intensive problems arising in business, there are still many scientific problem domains where limitations in the functionality of MapReduce systems prevent its wide adoption by those communities. This is mainly because MapReduce does not readily support the unique science discipline needs such as special science data formats, graphic and computational data analysis tools, maintaining high degrees of computational accuracies, and interfacing with application's existing components across heterogeneous computing processors. We address some of these limitations by exploiting the MapReduce programming model for satellite data intensive scientific problems and address scalability, reliability, scheduling, and data management issues when dealing with climate data records and their complex observational challenges. In addition, we will present techniques to support the unique Earth science discipline needs such as dealing with special science data formats (HDF and NetCDF). We have developed a Hadoop task scheduling algorithm that improves latency by 2x for a scientific workflow including the gridding of the EOS AIRS hyperspectral Brightness Temperatures (BT). This workflow processing algorithm has been tested at the Multicore Computing Center private Hadoop based Intel Nehalem cluster, as well as in a virtual mode under the Open Source Eucalyptus cloud. The 55TB AIRS hyperspectral L1b Brightness Temperature record has been gridded at the resolution of 0.5x1.0 degrees, and we have computed a 0.9 annual anti-correlation to the El Nino Southern oscillation in the Nino 4 region, as well as a 1.9 Kelvin decadal Arctic warming in the 4u and 12u spectral regions. Additionally, we will present the frequency of extreme global warming events by the use of a normalized maximum BT in a grid cell relative to its local standard deviation. A low-latency Hadoop scheduling environment maintains data integrity and fault tolerance in a MapReduce data intensive Cloud environment while improving the "time to solution" metric by 35% when compared to a more traditional parallel processing system for the same dataset. Our next step will be to improve the usability of our Hadoop task scheduling system, to enable rapid prototyping of data intensive experiments by means of processing "kernels". We will report on the performance and experience of implementing these experiments on the NEX testbed, and propose the use of a graphical directed acyclic graph (DAG) interface to help us develop on-demand scientific experiments. Our workflow system works within Hadoop infrastructure as a replacement for the FIFO or FairScheduler, thus the use of Apache "Pig" latin or other Apache tools may also be worth investigating on the NEX system to improve the usability of our workflow scheduling infrastructure for rapid experimentation.

Opening Remarks: SciDAC 2007

NASA Astrophysics Data System (ADS)

Strayer, Michael

2007-09-01

Good morning. Welcome to Boston, the home of the Red Sox, Celtics and Bruins, baked beans, tea parties, Robert Parker, and SciDAC 2007. A year ago I stood before you to share the legacy of the first SciDAC program and identify the challenges that we must address on the road to petascale computing—a road E E Cummins described as `. . . never traveled, gladly beyond any experience.' Today, I want to explore the preparations for the rapidly approaching extreme scale (X-scale) generation. These preparations are the first step propelling us along the road of burgeoning scientific discovery enabled by the application of X- scale computing. We look to petascale computing and beyond to open up a world of discovery that cuts across scientific fields and leads us to a greater understanding of not only our world, but our universe. As part of the President's America Competitiveness Initiative, the ASCR Office has been preparing a ten year vision for computing. As part of this planning the LBNL together with ORNL and ANL hosted three town hall meetings on Simulation and Modeling at the Exascale for Energy, Ecological Sustainability and Global Security (E3). The proposed E3 initiative is organized around four programmatic themes: Engaging our top scientists, engineers, computer scientists and applied mathematicians; investing in pioneering large-scale science; developing scalable analysis algorithms, and storage architectures to accelerate discovery; and accelerating the build-out and future development of the DOE open computing facilities. It is clear that we have only just started down the path to extreme scale computing. Plan to attend Thursday's session on the out-briefing and discussion of these meetings. The road to the petascale has been at best rocky. In FY07, the continuing resolution provided 12% less money for Advanced Scientific Computing than either the President, the Senate, or the House. As a consequence, many of you had to absorb a no cost extension for your SciDAC work. I am pleased that the President's FY08 budget restores the funding for SciDAC. Quoting from Advanced Scientific Computing Research description in the House Energy and Water Development Appropriations Bill for FY08, "Perhaps no other area of research at the Department is so critical to sustaining U.S. leadership in science and technology, revolutionizing the way science is done and improving research productivity." As a society we need to revolutionize our approaches to energy, environmental and global security challenges. As we go forward along the road to the X-scale generation, the use of computation will continue to be a critical tool along with theory and experiment in understanding the behavior of the fundamental components of nature as well as for fundamental discovery and exploration of the behavior of complex systems. The foundation to overcome these societal challenges will build from the experiences and knowledge gained as you, members of our SciDAC research teams, work together to attack problems at the tera- and peta- scale. If SciDAC is viewed as an experiment for revolutionizing scientific methodology, then a strategic goal of ASCR program must be to broaden the intellectual base prepared to address the challenges of the new X-scale generation of computing. We must focus our computational science experiences gained over the past five years on the opportunities introduced with extreme scale computing. Our facilities are on a path to provide the resources needed to undertake the first part of our journey. Using the newly upgraded 119 teraflop Cray XT system at the Leadership Computing Facility, SciDAC research teams have in three days performed a 100-year study of the time evolution of the atmospheric CO2 concentration originating from the land surface. The simulation of the El Nino/Southern Oscillation which was part of this study has been characterized as `the most impressive new result in ten years' gained new insight into the behavior of superheated ionic gas in the ITER reactor as a result of an AORSA run on 22,500 processors that achieved over 87 trillion calculations per second (87 teraflops) which is 74% of the system's theoretical peak. Tomorrow, Argonne and IBM will announce that the first IBM Blue Gene/P, a 100 teraflop system, will be shipped to the Argonne Leadership Computing Facility later this fiscal year. By the end of FY2007 ASCR high performance and leadership computing resources will include the 114 teraflop IBM Blue Gene/P; a 102 teraflop Cray XT4 at NERSC and a 119 teraflop Cray XT system at Oak Ridge. Before ringing in the New Year, Oak Ridge will upgrade to 250 teraflops with the replacement of the dual core processors with quad core processors and Argonne will upgrade to between 250-500 teraflops, and next year, a petascale Cray Baker system is scheduled for delivery at Oak Ridge. The multidisciplinary teams in our SciDAC Centers for Enabling Technologies and our SciDAC Institutes must continue to work with our Scientific Application teams to overcome the barriers that prevent effective use of these new systems. These challenges include: the need for new algorithms as well as operating system and runtime software and tools which scale to parallel systems composed of hundreds of thousands processors; program development environments and tools which scale effectively and provide ease of use for developers and scientific end users; and visualization and data management systems that support moving, storing, analyzing, manipulating and visualizing multi-petabytes of scientific data and objects. The SciDAC Centers, located primarily at our DOE national laboratories will take the lead in ensuring that critical computer science and applied mathematics issues are addressed in a timely and comprehensive fashion and to address issues associated with research software lifecycle. In contrast, the SciDAC Institutes, which are university-led centers of excellence, will have more flexibility to pursue new research topics through a range of research collaborations. The Institutes will also work to broaden the intellectual and researcher base—conducting short courses and summer schools to take advantage of new high performance computing capabilities. The SciDAC Outreach Center at Lawrence Berkeley National Laboratory complements the outreach efforts of the SciDAC Institutes. The Outreach Center is our clearinghouse for SciDAC activities and resources and will communicate with the high performance computing community in part to understand their needs for workshops, summer schools and institutes. SciDAC is not ASCR's only effort to broaden the computational science community needed to meet the challenges of the new X-scale generation. I hope that you were able to attend the Computational Science Graduate Fellowship poster session last night. ASCR developed the fellowship in 1991 to meet the nation's growing need for scientists and technology professionals with advanced computer skills. CSGF, now jointly funded between ASCR and NNSA, is more than a traditional academic fellowship. It has provided more than 200 of the best and brightest graduate students with guidance, support and community in preparing them as computational scientists. Today CSGF alumni are bringing their diverse top-level skills and knowledge to research teams at DOE laboratories and in industries such as Proctor and Gamble, Lockheed Martin and Intel. At universities they are working to train the next generation of computational scientists. To build on this success, we intend to develop a wholly new Early Career Principal Investigator's (ECPI) program. Our objective is to stimulate academic research in scientific areas within ASCR's purview especially among faculty in early stages of their academic careers. Last February, we lost Ken Kennedy, one of the leading lights of our community. As we move forward into the extreme computing generation, his vision and insight will be greatly missed. In memorial to Ken Kennedy, we shall designate the ECPI grants to beginning faculty in Computer Science as the Ken Kennedy Fellowship. Watch the ASCR website for more information about ECPI and other early career programs in the computational sciences. We look to you, our scientists, researchers, and visionaries to take X-scale computing and use it to explode scientific discovery in your fields. We at SciDAC will work to ensure that this tool is the sharpest and most precise and efficient instrument to carve away the unknown and reveal the most exciting secrets and stimulating scientific discoveries of our time. The partnership between research and computing is the marriage that will spur greater discovery, and as Spencer said to Susan in Robert Parker's novel, `Sudden Mischief', `We stick together long enough, and we may get as smart as hell'. Michael Strayer

The Rise of China in the International Trade Network: A Community Core Detection Approach

PubMed Central

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995–2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism. PMID:25136895

The rise of China in the International Trade Network: a community core detection approach.

PubMed

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.

Engaging Scientists in NASA Education and Public Outreach: Informal Science Education and Outreach

NASA Astrophysics Data System (ADS)

Lawton, Brandon L.; Smith, D. A.; Bartolone, L.; Meinke, B. K.; Discovery Guides Collaborative, Universe; Collaborative, NASAScience4Girls; SEPOF Informal Education Working Group; E/PO Community, SMD

2014-01-01

The NASA Science Education and Public Outreach Forums support the NASA Science Mission Directorate (SMD) and its education and public outreach (E/PO) community through a coordinated effort to enhance the coherence and efficiency of SMD-funded E/PO programs. The Forums foster collaboration between scientists with content expertise and educators with pedagogy expertise. We present opportunities for the astronomy community to participate in collaborations supporting the NASA SMD efforts in the Informal Science Education and Outreach communities. Members of the Informal Science Education and Outreach communities include museum/science center/planetarium professionals, librarians, park rangers, amateur astronomers, and other out-of-school-time educators. The Forums’ efforts for the Informal Science Education and Outreach communities include a literature review, appraisal of informal educators’ needs, coordination of audience-based NASA resources and opportunities, and professional development. Learn how to join in our collaborative efforts to reach the informal science education and outreach communities based upon mutual needs and interests.

Central Computer Science Concepts to Research-Based Teacher Training in Computer Science: An Experimental Study

ERIC Educational Resources Information Center

Zendler, Andreas; Klaudt, Dieter

2012-01-01

The significance of computer science for economics and society is undisputed. In particular, computer science is acknowledged to play a key role in schools (e.g., by opening multiple career paths). The provision of effective computer science education in schools is dependent on teachers who are able to properly represent the discipline and whose…

Comparison of attitudes of non-science major students toward science and technology

NASA Astrophysics Data System (ADS)

Wick, Donald Gary

This study examines the attitudes of non-science major students who were enrolled in General Education Required (GER) science courses at three diverse Iowa post-secondary educational institutions: The University of Iowa, Cornell College, and Kirkwood Community College. The information was gathered using a survey instrument with the test subjects responding with a five-part Likert-scale to a series of statements regarding: (1) reasons for taking the science course, (2) views and attitudes toward science, and (3) the nature and implications of science and technology. The initial data gathered was analyzed using either chi-squared, analysis of variance (ANOVA), and/or Bonferroni tests. Responses to grouped statements were used to generate population indices related to: (1) experience, (2) attitude, (3) experimentation, and (4) technology. These indices were analyzed for statistically significant differences using Tukey's Studentized (HSD) and Tukey-Krammer tests. Statistically significant differences were found in the response means for some individual statements. When a population index was calculated for each school using the grouped responses related to attitude, experience, science/technology, multiple comparison testing determined significant differences with regards to attitude, experiences, and science/technology. No significant differences were found between the schools for the population index regarding experimentation. Demographic information gathered concerning the nature of the student populations included: (1) declared major, (2) classification, (3) previous number of science courses, (4) gender, and (5) use of computers for the science course. Analysis of demographic data also revealed statistically significant differences. The differences found in this study provide additional quantitative data to characterize the non-science major student. Recommendations based on this data are: (1) The University of Iowa strive for smaller GER class sizes and reevaluate current pedagogy, (2) Kirkwood Community College make class material more relevant and place more emphasis on research, (3) Cornell College utilize full professors in the non-major course and incorporate more technology, and (4) all reevaluate the science GERs course pedagogy, retain the science GERs, maintain the current number of GER science course choices, and, finally, reevaluate any GER science course credit reciprocity.

Final Report National Laboratory Professional Development Workshop for Underrepresented Participants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, Valerie

The 2013 CMD-IT National Laboratories Professional Development Workshop for Underrepresented Participants (CMD-IT NLPDev 2013) was held at the Oak Ridge National Laboratory campus in Oak Ridge, TN. from June 13 - 14, 2013. Sponsored by the Department of Energy (DOE) Advanced Scientific Computing Research Program, the primary goal of these workshops is to provide information about career opportunities in computational science at the various national laboratories and to mentor the underrepresented participants through community building and expert presentations focused on career success. This second annual workshop offered sessions to facilitate career advancement and, in particular, the strategies and resources neededmore » to be successful at the national laboratories.« less

QMC Goes BOINC: Using Public Resource Computing to Perform Quantum Monte Carlo Calculations

NASA Astrophysics Data System (ADS)

Rainey, Cameron; Engelhardt, Larry; Schröder, Christian; Hilbig, Thomas

2008-10-01

Theoretical modeling of magnetic molecules traditionally involves the diagonalization of quantum Hamiltonian matrices. However, as the complexity of these molecules increases, the matrices become so large that this process becomes unusable. An additional challenge to this modeling is that many repetitive calculations must be performed, further increasing the need for computing power. Both of these obstacles can be overcome by using a quantum Monte Carlo (QMC) method and a distributed computing project. We have recently implemented a QMC method within the Spinhenge@home project, which is a Public Resource Computing (PRC) project where private citizens allow part-time usage of their PCs for scientific computing. The use of PRC for scientific computing will be described in detail, as well as how you can contribute to the project. See, e.g., L. Engelhardt, et. al., Angew. Chem. Int. Ed. 47, 924 (2008). C. Schröoder, in Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities. (Weber, M.H.W., ed., 2008). Project URL: http://spin.fh-bielefeld.de

Perspectives on chemical oceanography in the 21st century: Participants of the COME ABOARD Meeting examine aspects of the field in the context of 40 years of DISCO

USGS Publications Warehouse

Fassbender, Andrea J.; Palevsky, Hilary I.; Martz, Todd R.; Ingalls, Anitra E.; Gledhill, Martha; Fawcett, Sarah E.; Brandes, Jay; Aluwihare, Lihini; Anderson, Robert M.; Bender, Sara; Boyle, Ed; Bronk, Debbie; Buesseler, Ken; Burdige, David J.; Casciotti, Karen; Close, Hilary; Conte, Maureen; Cutter, Greg; Estapa, Meg; Fennel, Katja; Ferron, Sara; Glazer, Brian; Goni, Miguel; Grand, Max; Guay, Chris; Hatta, Mariko; Hayes, Chris; Horner, Tristan; Ingall, Ellery; Johnson, Kenneth G.; Juranek, Laurie; Knapp, Angela; Lam, Phoebe; Luther, George; Matrai, Paty; Nicholson, David; Paytan, Adina; Pellenbarg, Robert; Popendorf, Kim; Reddy, Christopher M.; Ruttenberg, Kathleen; Sabine, Chris; Sansone, Frank; Shaltout, Nayrah; Sikes, Liz; Sundquist, Eric T.; Valentine, David; Wang, Zhao (Aleck); Wilson, Sam; Barrett, Pamela; Behrens, Melanie; Belcher, Anna; Biermann, Lauren; Boiteau, Rene; Clarke, Jennifer; Collins, Jamie; Coppola, Alysha; Ebling, Alina M.; Garcia-Tigreros, Fenix; Goldman, Johanna; Guallart, Elisa F.; Haskell, William; Hurley, Sarah; Janssen, David; Johnson, Winn; Lennhartz, Sinikka; Liu, Shuting; Rahman, Shaily; Ray, Daisy; Sarkar, Amit; Steiner, Zvika; Widner, Brittany; Yang, Bo

2017-01-01

The questions that chemical oceanographers prioritize over the coming decades, and the methods we use to address these questions, will define our field's contribution to 21st century science. In recognition of this, the U.S. National Science Foundation and National Oceanic and Atmospheric Administration galvanized a community effort (the Chemical Oceanography MEeting: A BOttom-up Approach to Research Directions, or COME ABOARD) to synthesize bottom-up perspectives on selected areas of research in Chemical Oceanography. Representing only a small subset of the community, COME ABOARD participants did not attempt to identify targeted research directions for the field. Instead, we focused on how best to foster diverse research in Chemical Oceanography, placing emphasis on the following themes: strengthening our core chemical skillset; expanding our tools through collaboration with chemists, engineers, and computer scientists; considering new roles for large programs; enhancing interface research through interdisciplinary collaboration; and expanding ocean literacy by engaging with the public. For each theme, COME ABOARD participants reflected on the present state of Chemical Oceanography, where the community hopes to go and why, and actionable pathways to get there. A unifying concept among the discussions was that dissimilar funding structures and metrics of success may be required to accommodate the various levels of readiness and stages of knowledge development found throughout our community. In addition to the science, participants of the concurrent Dissertations Symposium in Chemical Oceanography (DISCO) XXV, a meeting of recent and forthcoming Ph.D. graduates in Chemical Oceanography, provided perspectives on how our field could show leadership in addressing long-standing diversity and early-career challenges that are pervasive throughout science. Here we summarize the COME ABOARD Meeting discussions, providing a synthesis of reflections and perspectives on the field.

War of Ontology Worlds: Mathematics, Computer Code, or Esperanto?

PubMed Central

Rzhetsky, Andrey; Evans, James A.

2011-01-01

The use of structured knowledge representations—ontologies and terminologies—has become standard in biomedicine. Definitions of ontologies vary widely, as do the values and philosophies that underlie them. In seeking to make these views explicit, we conducted and summarized interviews with a dozen leading ontologists. Their views clustered into three broad perspectives that we summarize as mathematics, computer code, and Esperanto. Ontology as mathematics puts the ultimate premium on rigor and logic, symmetry and consistency of representation across scientific subfields, and the inclusion of only established, non-contradictory knowledge. Ontology as computer code focuses on utility and cultivates diversity, fitting ontologies to their purpose. Like computer languages C++, Prolog, and HTML, the code perspective holds that diverse applications warrant custom designed ontologies. Ontology as Esperanto focuses on facilitating cross-disciplinary communication, knowledge cross-referencing, and computation across datasets from diverse communities. We show how these views align with classical divides in science and suggest how a synthesis of their concerns could strengthen the next generation of biomedical ontologies. PMID:21980276

War of ontology worlds: mathematics, computer code, or Esperanto?

PubMed

Rzhetsky, Andrey; Evans, James A

2011-09-01

The use of structured knowledge representations-ontologies and terminologies-has become standard in biomedicine. Definitions of ontologies vary widely, as do the values and philosophies that underlie them. In seeking to make these views explicit, we conducted and summarized interviews with a dozen leading ontologists. Their views clustered into three broad perspectives that we summarize as mathematics, computer code, and Esperanto. Ontology as mathematics puts the ultimate premium on rigor and logic, symmetry and consistency of representation across scientific subfields, and the inclusion of only established, non-contradictory knowledge. Ontology as computer code focuses on utility and cultivates diversity, fitting ontologies to their purpose. Like computer languages C++, Prolog, and HTML, the code perspective holds that diverse applications warrant custom designed ontologies. Ontology as Esperanto focuses on facilitating cross-disciplinary communication, knowledge cross-referencing, and computation across datasets from diverse communities. We show how these views align with classical divides in science and suggest how a synthesis of their concerns could strengthen the next generation of biomedical ontologies.

Using spatial principles to optimize distributed computing for enabling the physical science discoveries

PubMed Central

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-01-01

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century. PMID:21444779

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

PubMed

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-04-05

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

High Performance Computing Facility Operational Assessment 2015: Oak Ridge Leadership Computing Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barker, Ashley D.; Bernholdt, David E.; Bland, Arthur S.

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security aspects associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2015 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction that ties the highest-ever mark set in CY 2014; the greatestmore » number of core-hours delivered to research projects; the largest percentage of capability usage since the OLCF began tracking the metric in 2009; and success in delivering on the allocation of 60, 30, and 10% of core hours offered for the INCITE (Innovative and Novel Computational Impact on Theory and Experiment), ALCC (Advanced Scientific Computing Research Leadership Computing Challenge), and Director’s Discretionary programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations. The impact of all of these successes and more is reflected in the accomplishments of OLCF users, with publications this year in notable journals Nature, Nature Materials, Nature Chemistry, Nature Physics, Nature Climate Change, ACS Nano, Journal of the American Chemical Society, and Physical Review Letters, as well as many others. The achievements included in the 2015 OLCF Operational Assessment Report reflect first-ever or largest simulations in their communities; for example Titan enabled engineers in Los Angeles and the surrounding region to design and begin building improved critical infrastructure by enabling the highest-resolution Cybershake map for Southern California to date. The Titan system provides the largest extant heterogeneous architecture for computing and computational science. Usage is high, delivering on the promise of a system well-suited for capability simulations for science. This success is due in part to innovations in tracking and reporting the activity on the compute nodes, and using this information to further enable and optimize applications, extending and balancing workload across the entire node. The OLCF continues to invest in innovative processes, tools, and resources necessary to meet continuing user demand. The facility’s leadership in data analysis and workflows was featured at the Department of Energy (DOE) booth at SC15, for the second year in a row, highlighting work with researchers from the National Library of Medicine coupled with unique computational and data resources serving experimental and observational data across facilities. Effective operations of the OLCF play a key role in the scientific missions and accomplishments of its users. Building on the exemplary year of 2014, as shown by the 2014 Operational Assessment Report (OAR) review committee response in Appendix A, this OAR delineates the policies, procedures, and innovations implemented by the OLCF to continue delivering a multi-petaflop resource for cutting-edge research. This report covers CY 2015, which, unless otherwise specified, denotes January 1, 2015, through December 31, 2015.« less

The National Cancer Institute's Physical Sciences - Oncology Network

NASA Astrophysics Data System (ADS)

Espey, Michael Graham

In 2009, the NCI launched the Physical Sciences - Oncology Centers (PS-OC) initiative with 12 Centers (U54) funded through 2014. The current phase of the Program includes U54 funded Centers with the added feature of soliciting new Physical Science - Oncology Projects (PS-OP) U01 grant applications through 2017; see NCI PAR-15-021. The PS-OPs, individually and along with other PS-OPs and the Physical Sciences-Oncology Centers (PS-OCs), comprise the Physical Sciences-Oncology Network (PS-ON). The foundation of the Physical Sciences-Oncology initiative is a high-risk, high-reward program that promotes a `physical sciences perspective' of cancer and fosters the convergence of physical science and cancer research by forming transdisciplinary teams of physical scientists (e.g., physicists, mathematicians, chemists, engineers, computer scientists) and cancer researchers (e.g., cancer biologists, oncologists, pathologists) who work closely together to advance our understanding of cancer. The collaborative PS-ON structure catalyzes transformative science through increased exchange of people, ideas, and approaches. PS-ON resources are leveraged to fund Trans-Network pilot projects to enable synergy and cross-testing of experimental and/or theoretical concepts. This session will include a brief PS-ON overview followed by a strategic discussion with the APS community to exchange perspectives on the progression of trans-disciplinary physical sciences in cancer research.

Observatories, think tanks, and community models in the hydrologic and environmental sciences: How does it affect me?

NASA Astrophysics Data System (ADS)

Torgersen, Thomas

2006-06-01

Multiple issues in hydrologic and environmental sciences are now squarely in the public focus and require both government and scientific study. Two facts also emerge: (1) The new approach being touted publicly for advancing the hydrologic and environmental sciences is the establishment of community-operated "big science" (observatories, think tanks, community models, and data repositories). (2) There have been important changes in the business of science over the last 20 years that make it important for the hydrologic and environmental sciences to demonstrate the "value" of public investment in hydrological and environmental science. Given that community-operated big science (observatories, think tanks, community models, and data repositories) could become operational, I argue that such big science should not mean a reduction in the importance of single-investigator science. Rather, specific linkages between the large-scale, team-built, community-operated big science and the single investigator should provide context data, observatory data, and systems models for a continuing stream of hypotheses by discipline-based, specialized research and a strong rationale for continued, single-PI ("discovery-based") research. I also argue that big science can be managed to provide a better means of demonstrating the value of public investment in the hydrologic and environmental sciences. Decisions regarding policy will still be political, but big science could provide an integration of the best scientific understanding as a guide for the best policy.

A Financial Technology Entrepreneurship Program for Computer Science Students

ERIC Educational Resources Information Center

Lawler, James P.; Joseph, Anthony

2011-01-01

Education in entrepreneurship is becoming a critical area of curricula for computer science students. Few schools of computer science have a concentration in entrepreneurship in the computing curricula. The paper presents Technology Entrepreneurship in the curricula at a leading school of computer science and information systems, in which students…

A synergistic effort among geoscience, physics, computer science and mathematics at Hunter College of CUNY as a Catalyst for educating Earth scientists.

NASA Astrophysics Data System (ADS)

Salmun, H.; Buonaiuto, F. S.

2016-12-01

The Catalyst Scholarship Program at Hunter College of The City University of New York (CUNY) was established with a four-year award from the National Science Foundation (NSF) to fund scholarships for academically talented but financially disadvantaged students majoring in four disciplines of science, technology, engineering and mathematics (STEM). Led by Earth scientists the Program awarded scholarships to students in their junior or senior years majoring in computer science, geosciences, mathematics and physics to create two cohorts of students that spent a total of four semesters in an interdisciplinary community. The program included mentoring of undergraduate students by faculty and graduate students (peer-mentoring), a sequence of three semesters of a one-credit seminar course and opportunities to engage in research activities, research seminars and other enriching academic experiences. Faculty and peer-mentoring were integrated into all parts of the scholarship activities. The one-credit seminar course, although designed to expose scholars to the diversity STEM disciplines and to highlight research options and careers in these disciplines, was thematically focused on geoscience, specifically on ocean and atmospheric science. The program resulted in increased retention rates relative to institutional averages. In this presentation we will discuss the process of establishing the program, from the original plans to its implementation, as well as the impact of this multidisciplinary approach to geoscience education at our institution and beyond. An overview of accomplishments, lessons learned and potential for best practices will be presented.

Computer Science Teacher Professional Development in the United States: A Review of Studies Published between 2004 and 2014

ERIC Educational Resources Information Center

Menekse, Muhsin

2015-01-01

While there has been a remarkable interest to make computer science a core K-12 academic subject in the United States, there is a shortage of K-12 computer science teachers to successfully implement computer sciences courses in schools. In order to enhance computer science teacher capacity, training programs have been offered through teacher…

Argonne Leadership Computing Facility 2011 annual report : Shaping future supercomputing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papka, M.; Messina, P.; Coffey, R.

The ALCF's Early Science Program aims to prepare key applications for the architecture and scale of Mira and to solidify libraries and infrastructure that will pave the way for other future production applications. Two billion core-hours have been allocated to 16 Early Science projects on Mira. The projects, in addition to promising delivery of exciting new science, are all based on state-of-the-art, petascale, parallel applications. The project teams, in collaboration with ALCF staff and IBM, have undertaken intensive efforts to adapt their software to take advantage of Mira's Blue Gene/Q architecture, which, in a number of ways, is a precursormore » to future high-performance-computing architecture. The Argonne Leadership Computing Facility (ALCF) enables transformative science that solves some of the most difficult challenges in biology, chemistry, energy, climate, materials, physics, and other scientific realms. Users partnering with ALCF staff have reached research milestones previously unattainable, due to the ALCF's world-class supercomputing resources and expertise in computation science. In 2011, the ALCF's commitment to providing outstanding science and leadership-class resources was honored with several prestigious awards. Research on multiscale brain blood flow simulations was named a Gordon Bell Prize finalist. Intrepid, the ALCF's BG/P system, ranked No. 1 on the Graph 500 list for the second consecutive year. The next-generation BG/Q prototype again topped the Green500 list. Skilled experts at the ALCF enable researchers to conduct breakthrough science on the Blue Gene system in key ways. The Catalyst Team matches project PIs with experienced computational scientists to maximize and accelerate research in their specific scientific domains. The Performance Engineering Team facilitates the effective use of applications on the Blue Gene system by assessing and improving the algorithms used by applications and the techniques used to implement those algorithms. The Data Analytics and Visualization Team lends expertise in tools and methods for high-performance, post-processing of large datasets, interactive data exploration, batch visualization, and production visualization. The Operations Team ensures that system hardware and software work reliably and optimally; system tools are matched to the unique system architectures and scale of ALCF resources; the entire system software stack works smoothly together; and I/O performance issues, bug fixes, and requests for system software are addressed. The User Services and Outreach Team offers frontline services and support to existing and potential ALCF users. The team also provides marketing and outreach to users, DOE, and the broader community.« less