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.

Computational provenance in hydrologic science: a snow mapping example.

PubMed

Dozier, Jeff; Frew, James

2009-03-13

Computational provenance--a record of the antecedents and processing history of digital information--is key to properly documenting computer-based scientific research. To support investigations in hydrologic science, we produce the daily fractional snow-covered area from NASA's moderate-resolution imaging spectroradiometer (MODIS). From the MODIS reflectance data in seven wavelengths, we estimate the fraction of each 500 m pixel that snow covers. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry, so we interpolate and smooth to produce our best estimate of the daily snow cover. To manage the data, we have developed the Earth System Science Server (ES3), a software environment for data-intensive Earth science, with unique capabilities for automatically and transparently capturing and managing the provenance of arbitrary computations. Transparent acquisition avoids the scientists having to express their computations in specific languages or schemas in order for provenance to be acquired and maintained. ES3 models provenance as relationships between processes and their input and output files. It is particularly suited to capturing the provenance of an evolving algorithm whose components span multiple languages and execution environments.

Striving for Balance: The Co-Existence of Multi-, Inter- and Transdisciplinary Curricula in Information Management Education To Address Information Imbalances on Tertiary Level.

ERIC Educational Resources Information Center

Fairer-Wessels, Felicite A.

Within the South African tertiary education context, information management is taught from a variety of perspectives, including computer science, business management, informatics, and library and information science. Each discipline has a particular multidisciplinary focus dealing with its fundamentals. To investigate information management…

SANs and Large Scale Data Migration at the NASA Center for Computational Sciences

NASA Technical Reports Server (NTRS)

Salmon, Ellen M.

2004-01-01

Evolution and migration are a way of life for provisioners of high-performance mass storage systems that serve high-end computers used by climate and Earth and space science researchers: the compute engines come and go, but the data remains. At the NASA Center for Computational Sciences (NCCS), disk and tape SANs are deployed to provide high-speed I/O for the compute engines and the hierarchical storage management systems. Along with gigabit Ethernet, they also enable the NCCS's latest significant migration: the transparent transfer of 300 Til3 of legacy HSM data into the new Sun SAM-QFS cluster.

Energy and technology review

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

Quirk, W.J.; Canada, J.; de Vore, L.

1994-04-01

This issue highlights the Lawrence Livermore National Laboratory`s 1993 accomplishments in our mission areas and core programs: economic competitiveness, national security, energy, the environment, lasers, biology and biotechnology, engineering, physics, chemistry, materials science, computers and computing, and science and math education. Secondary topics include: nonproliferation, arms control, international security, environmental remediation, and waste management.

Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

NASA Technical Reports Server (NTRS)

Estes, Ronald H. (Editor)

1993-01-01

This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center.

Computer Science Research at Langley

NASA Technical Reports Server (NTRS)

Voigt, S. J. (Editor)

1982-01-01

A workshop was held at Langley Research Center, November 2-5, 1981, to highlight ongoing computer science research at Langley and to identify additional areas of research based upon the computer user requirements. A panel discussion was held in each of nine application areas, and these are summarized in the proceedings. Slides presented by the invited speakers are also included. A survey of scientific, business, data reduction, and microprocessor computer users helped identify areas of focus for the workshop. Several areas of computer science which are of most concern to the Langley computer users were identified during the workshop discussions. These include graphics, distributed processing, programmer support systems and tools, database management, and numerical methods.

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.

New and revised fire effects tools for fire management

Treesearch

Robert E. Keane; Greg Dillon; Stacy Drury; Robin Innes; Penny Morgan; Duncan Lutes; Susan J. Prichard; Jane Smith; Eva Strand

2014-01-01

Announcing the release of new software packages for application in wildland fire science and management, two fields that are already fully saturated with computer technology, may seem a bit too much to many managers. However, there have been some recent releases of new computer programs and revisions of existing software and information tools that deserve mention...

Computers in Undergraduate Science Education. Conference Proceedings.

ERIC Educational Resources Information Center

Blum, Ronald, Ed.

Six areas of computer use in undergraduate education, particularly in the fields of mathematics and physics, are discussed in these proceedings. The areas included are: the computational mode; computer graphics; the simulation mode; analog computing; computer-assisted instruction; and the current politics and management of college level computer…

Workflow Management Systems for Molecular Dynamics on Leadership Computers

NASA Astrophysics Data System (ADS)

Wells, Jack; Panitkin, Sergey; Oleynik, Danila; Jha, Shantenu

Molecular Dynamics (MD) simulations play an important role in a range of disciplines from Material Science to Biophysical systems and account for a large fraction of cycles consumed on computing resources. Increasingly science problems require the successful execution of ''many'' MD simulations as opposed to a single MD simulation. There is a need to provide scalable and flexible approaches to the execution of the workload. We present preliminary results on the Titan computer at the Oak Ridge Leadership Computing Facility that demonstrate a general capability to manage workload execution agnostic of a specific MD simulation kernel or execution pattern, and in a manner that integrates disparate grid-based and supercomputing resources. Our results build upon our extensive experience of distributed workload management in the high-energy physics ATLAS project using PanDA (Production and Distributed Analysis System), coupled with recent conceptual advances in our understanding of workload management on heterogeneous resources. We will discuss how we will generalize these initial capabilities towards a more production level service on DOE leadership resources. This research is sponsored by US DOE/ASCR and used resources of the OLCF computing facility.

Bioinformatics for Exploration

NASA Technical Reports Server (NTRS)

Johnson, Kathy A.

2006-01-01

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Summary of Research 1997, Department of Computer Science.

DTIC Science & Technology

1999-01-01

Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704...contains summaries of research projects in the Department of Computer Science . A list of recent publications is also included which consists of conference...parallel programming. Recently, in a joint research project between NPS and the Russian Academy of Sciences Systems Programming Insti- tute in Moscow

Development of Online Cognitive and Algorithm Tests as Assessment Tools in Introductory Computer Science Courses

ERIC Educational Resources Information Center

Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul

2012-01-01

This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…

Using Frameworks in a Government Contracting Environment: Case Study at the NASA Center for Computational Sciences

NASA Technical Reports Server (NTRS)

McGalliard, James

2008-01-01

A viewgraph describing the use of multiple frameworks by NASA, GSA, and U.S. Government agencies is presented. The contents include: 1) Federal Systems Integration and Management Center (FEDSIM) and NASA Center for Computational Sciences (NCCS) Environment; 2) Ruling Frameworks; 3) Implications; and 4) Reconciling Multiple Frameworks.

Effective Teacher Qualities from International Mathematics, Science, and Computer Teachers' Perspectives

ERIC Educational Resources Information Center

Sahin, Alpaslan; Adiguzel, Tufan

2014-01-01

The purpose of this study is to investigate how international teachers, who were from overseas but taught in the United States, rate effective teacher qualities in three domains; personal, professional, and classroom management skills. The study includes 130 international mathematics, science, and computer teachers who taught in a multi-school…

Welcome to health information science and systems.

PubMed

Zhang, Yanchun

2013-01-01

Health Information Science and Systems is an exciting, new, multidisciplinary journal that aims to use technologies in computer science to assist in disease diagnoses, treatment, prediction and monitoring through the modeling, design, development, visualization, integration and management of health related information. These computer-science technologies include such as information systems, web technologies, data mining, image processing, user interaction and interface, sensors and wireless networking and are applicable to a wide range of health related information including medical data, biomedical data, bioinformatics data, public health data.

Software for pest-management science: computer models and databases from the United States Department of Agriculture-Agricultural Research Service.

PubMed

Wauchope, R Don; Ahuja, Lajpat R; Arnold, Jeffrey G; Bingner, Ron; Lowrance, Richard; van Genuchten, Martinus T; Adams, Larry D

2003-01-01

We present an overview of USDA Agricultural Research Service (ARS) computer models and databases related to pest-management science, emphasizing current developments in environmental risk assessment and management simulation models. The ARS has a unique national interdisciplinary team of researchers in surface and sub-surface hydrology, soil and plant science, systems analysis and pesticide science, who have networked to develop empirical and mechanistic computer models describing the behavior of pests, pest responses to controls and the environmental impact of pest-control methods. Historically, much of this work has been in support of production agriculture and in support of the conservation programs of our 'action agency' sister, the Natural Resources Conservation Service (formerly the Soil Conservation Service). Because we are a public agency, our software/database products are generally offered without cost, unless they are developed in cooperation with a private-sector cooperator. Because ARS is a basic and applied research organization, with development of new science as our highest priority, these products tend to be offered on an 'as-is' basis with limited user support except for cooperating R&D relationship with other scientists. However, rapid changes in the technology for information analysis and communication continually challenge our way of doing business.

Enabling campus grids with open science grid technology

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

Weitzel, Derek; Bockelman, Brian; Swanson, David

2011-01-01

The Open Science Grid is a recognized key component of the US national cyber-infrastructure enabling scientific discovery through advanced high throughput computing. The principles and techniques that underlie the Open Science Grid can also be applied to Campus Grids since many of the requirements are the same, even if the implementation technologies differ. We find five requirements for a campus grid: trust relationships, job submission, resource independence, accounting, and data management. The Holland Computing Center's campus grid at the University of Nebraska-Lincoln was designed to fulfill the requirements of a campus grid. A bridging daemon was designed to bring non-Condormore » clusters into a grid managed by Condor. Condor features which make it possible to bridge Condor sites into a multi-campus grid have been exploited at the Holland Computing Center as well.« less

Computational Ecology and Open Science: Tools to Help Manage Lakes for Cyanobacteria in Lakes

EPA Science Inventory

Computational ecology is an interdisciplinary field that takes advantage of modern computation abilities to expand our ecological understanding. As computational ecologists, we use large data sets, which often cover large spatial extents, and advanced statistical/mathematical co...

Multiscale Computation. Needs and Opportunities for BER Science

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

Scheibe, Timothy D.; Smith, Jeremy C.

2015-01-01

The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSLmore » decisions regarding future computational (hardware and software) architectures.« less

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

Journal of Undergraduate Research, Volume VIII, 2008

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

Stiner, K. S.; Graham, S.; Khan, M.

Th e Journal of Undergraduate Research (JUR) provides undergraduate interns the opportunity to publish their scientific innovation and to share their passion for education and research with fellow students and scientists. Fields in which these students worked include: Biology; Chemistry; Computer Science; Engineering; Environmental Science; General Sciences; Materials Sciences; Medical and Health Sciences; Nuclear Sciences; Physics; Science Policy; and Waste Management.

Advanced Technologies and Data Management Practices in Environmental Science: Lessons from Academia

ERIC Educational Resources Information Center

Hernandez, Rebecca R.; Mayernik, Matthew S.; Murphy-Mariscal, Michelle L.; Allen, Michael F.

2012-01-01

Environmental scientists are increasing their capitalization on advancements in technology, computation, and data management. However, the extent of that capitalization is unknown. We analyzed the survey responses of 434 graduate students to evaluate the understanding and use of such advances in the environmental sciences. Two-thirds of the…

Enhancements to the Redmine Database Metrics Plug in

DTIC Science & Technology

2017-08-01

management web application has been adopted within the US Army Research Laboratory’s Computational and Information Sciences Directorate as a database...Metrics Plug-in by Terry C Jameson Computational and Information Sciences Directorate, ARL Approved for public... information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and

A Report on the Design and Construction of the University of Massachusetts Computer Science Center.

ERIC Educational Resources Information Center

Massachusetts State Office of the Inspector General, Boston.

This report describes a review conducted by the Massachusetts Office of the Inspector General on the construction of the Computer Science and Development Center at the University of Massachusetts, Amherst. The office initiated the review after hearing concerns about the management of the project, including its delayed completion and substantial…

The MORPG-Based Learning System for Multiple Courses: A Case Study on Computer Science Curriculum

ERIC Educational Resources Information Center

Liu, Kuo-Yu

2015-01-01

This study aimed at developing a Multiplayer Online Role Playing Game-based (MORPG) Learning system which enabled instructors to construct a game scenario and manage sharable and reusable learning content for multiple courses. It used the curriculum of "Introduction to Computer Science" as a study case to assess students' learning…

Simplified Key Management for Digital Access Control of Information Objects

DTIC Science & Technology

2016-07-02

0001, Task BC-5-2283, “Architecture, Design of Services for Air Force Wide Distributed Systems,” for USAF HQ USAF SAF/CIO A6. The views, opinions...Challenges for Cloud Computing,” Lecture Notes in Engineering and Computer Science: Proceedings World Congress on Engineering and Computer Science 2011...P. Konieczny USAF HQ USAF SAF/CIO A6 11. SPONSOR’S / MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT Approved for public

Synthetic Biology: Knowledge Accessed by Everyone (Open Sources)

ERIC Educational Resources Information Center

Sánchez Reyes, Patricia Margarita

2016-01-01

Using the principles of biology, along with engineering and with the help of computer, scientists manage to copy. DNA sequences from nature and use them to create new organisms. DNA is created through engineering and computer science managing to create life inside a laboratory. We cannot dismiss the role that synthetic biology could lead in…

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.

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.

Selected papers in the applied computer sciences 1992

USGS Publications Warehouse

Wiltshire, Denise A.

1992-01-01

This compilation of short papers reports on technical advances in the applied computer sciences. The papers describe computer applications in support of earth science investigations and research. This is the third volume in the series "Selected Papers in the Applied Computer Sciences." Listed below are the topics addressed in the compilation:Integration of geographic information systems and expert systems for resource management,Visualization of topography using digital image processing,Development of a ground-water data base for the southeastern Uited States using a geographic information system,Integration and aggregation of stream-drainage data using a geographic information system,Procedures used in production of digital geologic coverage using compact disc read-only memory (CD-ROM) technology, andAutomated methods for producing a technical publication on estimated water use in the United States.

Snowmass Computing Frontier: Computing for the Cosmic Frontier, Astrophysics, and Cosmology

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

Connolly, A.; Habib, S.; Szalay, A.

2013-11-12

This document presents (off-line) computing requrements and challenges for Cosmic Frontier science, covering the areas of data management, analysis, and simulations. We invite contributions to extend the range of covered topics and to enhance the current descriptions.

The Management of Information & Knowledge; Meeting of the Panel on Science and Technology with the Committee on Science and Astronautics, U.S. House of Representatives.

ERIC Educational Resources Information Center

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

The emphasis of the eleventh meeting of the Panel on Science and Technology was on the management of information and knowledge. It was organized essentially as a seminar with two papers given at each session. The topic of the first two papers presented was: "Computers, Communications, and the Economy." The papers given at the second session were…

Management Sciences Division Annual Report (10th)

DTIC Science & Technology

1993-01-01

of the Weapon System Management Information System (WSMIS). TheI Aircraft Sustainability Model ( ASM ) is the computational technique employed by...provisioning. We enhanced the capabilities of RBIRD by using the Aircraft Sustainability Model ( ASM ) for the spares calculation. ASM offers many... ASM for several years to 3 compute spares for war. It is also fully compatible with the Air Force’s peacetime spares computation system (D041). This

The Process of Updating Engineering Management Science in an Australian Regional University Excellence in Developing E-Learning

ERIC Educational Resources Information Center

Ku, H.; Fulcher, R.

2007-01-01

The aim of the current paper is to share the processes in revising the courseware of the course of "Engineering Management Science" coded as ENG4004, in the Bachelor of Engineering (Mechanical, Mechatronics, Electrical and Electronic, Computer Systems, Instrumentation and Control), Bachelor of Engineering Technology (Mechanical, Building…

Management and Analysis of Biological and Clinical Data: How Computer Science May Support Biomedical and Clinical Research

NASA Astrophysics Data System (ADS)

Veltri, Pierangelo

The use of computer based solutions for data management in biology and clinical science has contributed to improve life-quality and also to gather research results in shorter time. Indeed, new algorithms and high performance computation have been using in proteomics and genomics studies for curing chronic diseases (e.g., drug designing) as well as supporting clinicians both in diagnosis (e.g., images-based diagnosis) and patient curing (e.g., computer based information analysis on information gathered from patient). In this paper we survey on examples of computer based techniques applied in both biology and clinical contexts. The reported applications are also results of experiences in real case applications at University Medical School of Catanzaro and also part of experiences of the National project Staywell SH 2.0 involving many research centers and companies aiming to study and improve citizen wellness.

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

The Development of a Learning Dashboard for Lecturers: A Case Study on a Student-Centered E-Learning Environment

ERIC Educational Resources Information Center

Santoso, Harry B.; Batuparan, Alivia Khaira; Isal, R. Yugo K.; Goodridge, Wade H.

2018-01-01

Student Centered e-Learning Environment (SCELE) is a Moodle-based learning management system (LMS) that has been modified to enhance learning within a computer science department curriculum offered by the Faculty of Computer Science of large public university in Indonesia. This Moodle provided a mechanism to record students' activities when…

High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations

NASA Technical Reports Server (NTRS)

Parks, John (Technical Monitor); Biswas, Rupak; Yan, Jerry C.; Brooks, Walter F.; Sterling, Thomas L.

2003-01-01

Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.

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.

Analysis of a Proposed Material Handling System Using a Computer Simulation Model.

DTIC Science & Technology

1981-06-01

the proposed MMHS were identified to assist the managers of the system in implementation and future planning. * 4 UNCLASSIFIED SRCUllTY CLASSIPICATION...the Degree of Master of Science in Logistics Management By Darwin D. Harp, BSIE GS-11. June 1981 Approved for public release; distribution unlimited...partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN LOGISTICS MANAGEMENT DATE: 17 June 1981 (( COMMITECARN ii 67- B I

A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure.

PubMed

Warner, Guy C; Blum, Jesse M; Jones, Simon B; Lambert, Paul S; Turner, Kenneth J; Tan, Larry; Dawson, Alison S F; Bell, David N F

2010-08-28

The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analytical methodologies, such as microsimulation, and increases in computing power. These rich resources do, however, bring with them substantial challenges associated with organizing and using data. These processes are often referred to as 'data management'. The Data Management through e-Social Science (DAMES) project is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data-fusion process that is central to the project approach. It covers: the background and requirements for provision of resources by DAMES; the use of grid technologies to provide easy-to-use tools and user front-ends for several common social science data-management tasks such as data fusion; the approach taken to solve problems related to data resources and metadata relevant to social science applications; and the implementation of the architecture that has been designed to achieve this infrastructure.

Designing a Versatile Dedicated Computing Lab to Support Computer Network Courses: Insights from a Case Study

ERIC Educational Resources Information Center

Gercek, Gokhan; Saleem, Naveed

2006-01-01

Providing adequate computing lab support for Management Information Systems (MIS) and Computer Science (CS) programs is a perennial challenge for most academic institutions in the US and abroad. Factors, such as lack of physical space, budgetary constraints, conflicting needs of different courses, and rapid obsolescence of computing technology,…

Developing a Mobile Learning Management System for Outdoors Nature Science Activities Based on 5E Learning Cycle

ERIC Educational Resources Information Center

Lai, Ah-Fur; Lai, Horng-Yih; Chuang, Wei-Hsiang; Wu, Zih-Heng

2015-01-01

Traditional outdoor learning activities such as inquiry-based learning in nature science encounter many dilemmas. Due to prompt development of mobile computing and widespread of mobile devices, mobile learning becomes a big trend on education. The main purpose of this study is to develop a mobile-learning management system for overcoming the…

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.

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…

Teaching Efficacy of Universiti Putra Malaysia Science Student Teachers

ERIC Educational Resources Information Center

Bakar, Abd. Rahim; Konting, Mohd. Majid; Jamian, Rashid; Lyndon, Novel

2008-01-01

The objective of the study was to access teaching efficacy of Universiti Putra Malaysia Science student teachers. The specific objectives were to determine teaching efficacy of Science student teachers in terms of student engagement; instructional strategies; classroom management and teaching with computers in classroom; their satisfaction with…

1994 Science Information Management and Data Compression Workshop

NASA Technical Reports Server (NTRS)

Tilton, James C. (Editor)

1994-01-01

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on September 26-27, 1994, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival and retrieval of large quantities of data in future Earth and space science missions. It consisted of eleven presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center.

The 1995 Science Information Management and Data Compression Workshop

NASA Technical Reports Server (NTRS)

Tilton, James C. (Editor)

1995-01-01

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on October 26-27, 1995, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival, and retrieval of large quantities of data in future Earth and space science missions. It consisted of fourteen presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The Workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center.

78 FR 41046 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-09

... Services Administration, notice is hereby given that the Advanced Scientific Computing Advisory Committee will be renewed for a two-year period beginning on July 1, 2013. The Committee will provide advice to the Director, Office of Science (DOE), on the Advanced Scientific Computing Research Program managed...

NASA's Information Power Grid: Large Scale Distributed Computing and Data Management

NASA Technical Reports Server (NTRS)

Johnston, William E.; Vaziri, Arsi; Hinke, Tom; Tanner, Leigh Ann; Feiereisen, William J.; Thigpen, William; Tang, Harry (Technical Monitor)

2001-01-01

Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.

A characterization of workflow management systems for extreme-scale applications

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

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

A characterization of workflow management systems for extreme-scale applications

DOE PAGES

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...

2017-02-16

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

Unclassified Computing Capability: User Responses to a Multiprogrammatic and Institutional Computing Questionnaire

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

McCoy, M; Kissel, L

2002-01-29

We are experimenting with a new computing model to be applied to a new computer dedicated to that model. Several LLNL science teams now have computational requirements, evidenced by the mature scientific applications that have been developed over the past five plus years, that far exceed the capability of the institution's computing resources. Thus, there is increased demand for dedicated, powerful parallel computational systems. Computation can, in the coming year, potentially field a capability system that is low cost because it will be based on a model that employs open source software and because it will use PC (IA32-P4) hardware.more » This incurs significant computer science risk regarding stability and system features but also presents great opportunity. We believe the risks can be managed, but the existence of risk cannot be ignored. In order to justify the budget for this system, we need to make the case that it serves science and, through serving science, serves the institution. That is the point of the meeting and the White Paper that we are proposing to prepare. The questions are listed and the responses received are in this report.« less

Computers in the Forest: A Summer Alternative. A Description and Evaluation of the Nature Computer Camp.

ERIC Educational Resources Information Center

Prom, Sukai; And Others

The District of Columbia's Nature Computer Camp program, described and evaluated in this paper, was designed to reduce the geographical isolation of economically disadvantaged urban sixth graders, and to provide them with increased knowledge of the environmental and computer sciences. The paper begins by giving details of the program's management,…

Association of Small Computer Users in Education (ASCUE) Summer Conference. Proceedings (25th, North Myrtle Beach, South Carolina, June 21-25, 1992).

ERIC Educational Resources Information Center

Association of Small Computer Users in Education, Greencastle, IN.

Forty-three papers from a conference on microcomputers are presented under the following headings: Computing in the Curriculum, Information and Computer Science Information; Institutional and Administrative Computing, and Management, Services, and Training. Topics of the papers include the following: telecommunications projects that work in…

Job Skills of the Financial Aid Professional.

ERIC Educational Resources Information Center

Heist, Vali

2002-01-01

Describes the skills practiced by student financial aid professionals which are valued by all employers, including problem solving, human relations, computer programming, teaching/training, information management, money management, business management, and science and math. Also describes how to develop skills outside of the office. (EV)

Perceptions and Experiences of Baccalaureate Nursing Program Leaders Related to Nursing Informatics

ERIC Educational Resources Information Center

Larson, Lisa R.

2017-01-01

Nursing program leadership for integrating nursing informatics (NI) into curricula is essential. NI is a specialty that combines nursing science, computer science, and information science to manage health information and improve patient health outcomes (American Nurses Association, 2008). Approximately 98,000 patient deaths per year occur due to…

Future Challenges in Library Science.

ERIC Educational Resources Information Center

Murgai, Sarla R.

This paper considers a number of potential developments for the future of library science and the roles of information professionals. Among the projections are: (1) the use of computers and management science operations research methodologies will form the basis of decision making in libraries in the future; (2) a concerted effort will be made to…

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia.

PubMed

Safdari, Reza; Shahmoradi, Leila; Hosseini-Beheshti, Molouk-Sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-10-01

Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics' sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics.

A data management system to enable urgent natural disaster computing

NASA Astrophysics Data System (ADS)

Leong, Siew Hoon; Kranzlmüller, Dieter; Frank, Anton

2014-05-01

Civil protection, in particular natural disaster management, is very important to most nations and civilians in the world. When disasters like flash floods, earthquakes and tsunamis are expected or have taken place, it is of utmost importance to make timely decisions for managing the affected areas and reduce casualties. Computer simulations can generate information and provide predictions to facilitate this decision making process. Getting the data to the required resources is a critical requirement to enable the timely computation of the predictions. An urgent data management system to support natural disaster computing is thus necessary to effectively carry out data activities within a stipulated deadline. Since the trigger of a natural disaster is usually unpredictable, it is not always possible to prepare required resources well in advance. As such, an urgent data management system for natural disaster computing has to be able to work with any type of resources. Additional requirements include the need to manage deadlines and huge volume of data, fault tolerance, reliable, flexibility to changes, ease of usage, etc. The proposed data management platform includes a service manager to provide a uniform and extensible interface for the supported data protocols, a configuration manager to check and retrieve configurations of available resources, a scheduler manager to ensure that the deadlines can be met, a fault tolerance manager to increase the reliability of the platform and a data manager to initiate and perform the data activities. These managers will enable the selection of the most appropriate resource, transfer protocol, etc. such that the hard deadline of an urgent computation can be met for a particular urgent activity, e.g. data staging or computation. We associated 2 types of deadlines [2] with an urgent computing system. Soft-hard deadline: Missing a soft-firm deadline will render the computation less useful resulting in a cost that can have severe consequences Hard deadline: Missing a hard deadline renders the computation useless and results in full catastrophic consequences. A prototype of this system has a REST-based service manager. The REST-based implementation provides a uniform interface that is easy to use. New and upcoming file transfer protocols can easily be extended and accessed via the service manager. The service manager interacts with the other four managers to coordinate the data activities so that the fundamental natural disaster urgent computing requirement, i.e. deadline, can be fulfilled in a reliable manner. A data activity can include data storing, data archiving and data storing. Reliability is ensured by the choice of a network of managers organisation model[1] the configuration manager and the fault tolerance manager. With this proposed design, an easy to use, resource-independent data management system that can support and fulfill the computation of a natural disaster prediction within stipulated deadlines can thus be realised. References [1] H. G. Hegering, S. Abeck, and B. Neumair, Integrated management of networked systems - concepts, architectures, and their operational application, Morgan Kaufmann Publishers, 340 Pine Stret, Sixth Floor, San Francisco, CA 94104-3205, USA, 1999. [2] H. Kopetz, Real-time systems design principles for distributed embedded applications, second edition, Springer, LLC, 233 Spring Street, New York, NY 10013, USA, 2011. [3] S. H. Leong, A. Frank, and D. Kranzlmu¨ ller, Leveraging e-infrastructures for urgent computing, Procedia Computer Science 18 (2013), no. 0, 2177 - 2186, 2013 International Conference on Computational Science. [4] N. Trebon, Enabling urgent computing within the existing distributed computing infrastructure, Ph.D. thesis, University of Chicago, August 2011, http://people.cs.uchicago.edu/~ntrebon/docs/dissertation.pdf.

The science in social science

PubMed Central

Bernard, H. Russell

2012-01-01

A recent poll showed that most people think of science as technology and engineering—life-saving drugs, computers, space exploration, and so on. This was, in fact, the promise of the founders of modern science in the 17th century. It is less commonly understood that social and behavioral sciences have also produced technologies and engineering that dominate our everyday lives. These include polling, marketing, management, insurance, and public health programs. PMID:23213222

Software for the Humanities and Social Sciences.

ERIC Educational Resources Information Center

National Collegiate Software Clearinghouse, Raleigh, NC.

This computer software program bibliography available from the National Collegiate Software Clearinghouse (NCSC) includes programs for college students and researchers in anthropology, economics and business, education, English and text analysis, foreign language, general interest, history, management, philosophy and religion, political science,…

EPA SCIENCE FORUM - EPA'S TOXICOGENOMICS PARTNERSHIPS ACROSS GOVERNMENT, ACADEMIA AND INDUSTRY

EPA Science Inventory

Over the past decade genomics, proteomics and metabonomics technologies have transformed the science of toxicology, and concurrent advances in computing and informatics have provided management and analysis solutions for this onslaught of toxicogenomic data. EPA has been actively...

Encouraging more women into computer science: Initiating a single-sex intervention program in Sweden

NASA Astrophysics Data System (ADS)

Brandell, Gerd; Carlsson, Svante; Ekblom, Håkan; Nord, Ann-Charlotte

1997-11-01

The process of starting a new program in computer science and engineering, heavily based on applied mathematics and only open to women, is described in this paper. The program was introduced into an educational system without any tradition in single-sex education. Important observations made during the process included the considerable interest in mathematics and curiosity about computer science found among female students at the secondary school level, and the acceptance of the single-sex program by the staff, administration, and management of the university as well as among male and female students. The process described highlights the importance of preparing the environment for a totally new type of educational program.

Liz Torres | NREL

Science.gov Websites

of Expertise Customer service Technically savvy Event planning Word processing/desktop publishing Database management Research Interests Website design Database design Computational science Technology Consulting, Westminster, CO (2007-2012) Administrative Assistant, Source One Management, Denver, CO (2005

Sandia National Laboratories: About Sandia: Environmental Responsibility:

Science.gov Websites

Environmental Management: Sandia Sandia National Laboratories Exceptional service in the Environmental Responsibility Environmental Management System Pollution Prevention History 60 impacts Diversity ; Verification Research Research Foundations Bioscience Computing & Information Science Electromagnetics

Communications among data and science centers

NASA Technical Reports Server (NTRS)

Green, James L.

1990-01-01

The ability to electronically access and query the contents of remote computer archives is of singular importance in space and earth sciences; the present evaluation of such on-line information networks' development status foresees swift expansion of their data capabilities and complexity, in view of the volumes of data that will continue to be generated by NASA missions. The U.S.'s National Space Science Data Center (NSSDC) manages NASA's largest science computer network, the Space Physics Analysis Network; a comprehensive account is given of the structure of NSSDC international access through BITNET, and of connections to the NSSDC available in the Americas via the International X.25 network.

Computer Sciences Applied to Management at Open University of Catalonia: Development of Competences of Teamworks

NASA Astrophysics Data System (ADS)

Pisa, Carlos Cabañero; López, Enric Serradell

Teamwork is considered one of the most important professional skills in today's business environment. More specifically, the collaborative work between professionals and information technology managers from various functional areas is a strategic key in competitive business. Several university-level programs are focusing on developing these skills. This article presents the case of the course Computer Science Applied to Management (hereafter CSAM) that has been designed with the objective to develop the ability to work cooperatively in interdisciplinary teams. For their design and development have been addressed to the key elements of efficiency that appear in the literature, most notably the establishment of shared objectives and a feedback system, the management of the harmony of the team, their level of autonomy, independence, diversity and level of supervision. The final result is a subject in which, through a working virtual platform, interdisciplinary teams solve a problem raised by a case study.

First principles calculations of thermal conductivity with out of equilibrium molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Puligheddu, Marcello; Gygi, Francois; Galli, Giulia

The prediction of the thermal properties of solids and liquids is central to numerous problems in condensed matter physics and materials science, including the study of thermal management of opto-electronic and energy conversion devices. We present a method to compute the thermal conductivity of solids by performing ab initio molecular dynamics at non equilibrium conditions. Our formulation is based on a generalization of the approach to equilibrium technique, using sinusoidal temperature gradients, and it only requires calculations of first principles trajectories and atomic forces. We discuss results and computational requirements for a representative, simple oxide, MgO, and compare with experiments and data obtained with classical potentials. This work was supported by MICCoM as part of the Computational Materials Science Program funded by the U.S. Department of Energy (DOE), Office of Science , Basic Energy Sciences (BES), Materials Sciences and Engineering Division under Grant DOE/BES 5J-30.

Conceptual Modeling in the Time of the Revolution: Part II

NASA Astrophysics Data System (ADS)

Mylopoulos, John

Conceptual Modeling was a marginal research topic at the very fringes of Computer Science in the 60s and 70s, when the discipline was dominated by topics focusing on programs, systems and hardware architectures. Over the years, however, the field has moved to centre stage and has come to claim a central role both in Computer Science research and practice in diverse areas, such as Software Engineering, Databases, Information Systems, the Semantic Web, Business Process Management, Service-Oriented Computing, Multi-Agent Systems, Knowledge Management, and more. The transformation was greatly aided by the adoption of standards in modeling languages (e.g., UML), and model-based methodologies (e.g., Model-Driven Architectures) by the Object Management Group (OMG) and other standards organizations. We briefly review the history of the field over the past 40 years, focusing on the evolution of key ideas. We then note some open challenges and report on-going research, covering topics such as the representation of variability in conceptual models, capturing model intentions, and models of laws.

AIR FORCE CYBER MISSION ASSURANCE SOURCES OF MISSION UNCERTAINTY

DTIC Science & Technology

2017-04-06

Army’s Command and General Staff College at Fort Leavenworth, Kansas. Lt Col Herwick holds a bachelor of science degree in Computer Science from the...United States Air Force Academy and a master’s degree in Computer Resources and Information Management from Webster University. iii Abstract...vocabulary and while it is common to use conversationally, that usage is not always based on specific definitions. As a result, it finds common usage in

Are Academic Programs Adequate for the Software Profession?

ERIC Educational Resources Information Center

Koster, Alexis

2010-01-01

According to the Bureau of Labor Statistics, close to 1.8 million people, or 77% of all computer professionals, were working in the design, development, deployment, maintenance, and management of software in 2006. The ACM [Association for Computing Machinery] model curriculum for the BS in computer science proposes that about 42% of the core body…

The State of the Art in Information Handling. Operation PEP/Executive Information Systems.

ERIC Educational Resources Information Center

Summers, J. K.; Sullivan, J. E.

This document explains recent developments in computer science and information systems of interest to the educational manager. A brief history of computers is included, together with an examination of modern computers' capabilities. Various features of card, tape, and disk information storage systems are presented. The importance of time-sharing…

Teaching Real Science with a Microcomputer.

ERIC Educational Resources Information Center

Naiman, Adeline

1983-01-01

Discusses various ways science can be taught using microcomputers, including simulations/games which allow large-scale or historic experiments to be replicated on a manageable scale in a brief time. Examples of several computer programs are also presented, including "Experiments in Human Physiology,""Health Awareness…

Cumulative reports and publications through December 31, 1989

NASA Technical Reports Server (NTRS)

1990-01-01

A complete list of reports from the Institute for Computer Applications in Science and Engineering (ICASE) is presented. The major categories of the current ICASE research program are: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effectual numerical methods; computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; computer systems and software, especially vector and parallel computers, microcomputers, and data management. Since ICASE reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available.

Teaching Public Policy: Theory, Research, and Practice. Contributions in Political Science, Number 268.

ERIC Educational Resources Information Center

Bergerson, Peter J., Ed.

The 16 chapters of this book offer innovative instructional techniques used to train public managers. It presents public management concepts along with such subtopics as organizational theory and ethics, research skills, program evaluation, financial management, computers and communication skills in public administration, comparative public…

Videos | Argonne National Laboratory

Science.gov Websites

science --Agent-based modeling --Applied mathematics --Artificial intelligence --Cloud computing management -Intelligence & counterterrorrism -Vulnerability assessment -Sensors & detectors Programs

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...

Integrating emerging earth science technologies into disaster risk management: an enterprise architecture approach

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster risk management has grown to rely on earth observations, multi-source data analysis, numerical modeling, and interagency information sharing. The practice and outcomes of disaster risk management will likely undergo further change as several emerging earth science technologies come of age: mobile devices; location-based services; ubiquitous sensors; drones; small satellites; satellite direct readout; Big Data analytics; cloud computing; Web services for predictive modeling, semantic reconciliation, and collaboration; and many others. Integrating these new technologies well requires developing and adapting them to meet current needs; but also rethinking current practice to draw on new capabilities to reach additional objectives. This requires a holistic view of the disaster risk management enterprise and of the analytical or operational capabilities afforded by these technologies. One helpful tool for this assessment, the GEOSS Architecture for the Use of Remote Sensing Products in Disaster Management and Risk Assessment (Evans & Moe, 2013), considers all phases of the disaster risk management lifecycle for a comprehensive set of natural hazard types, and outlines common clusters of activities and their use of information and computation resources. We are using these architectural views, together with insights from current practice, to highlight effective, interrelated roles for emerging earth science technologies in disaster risk management. These roles may be helpful in creating roadmaps for research and development investment at national and international levels.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

Information technology challenges of biodiversity and ecosystems informatics

USGS Publications Warehouse

Schnase, J.L.; Cushing, J.; Frame, M.; Frondorf, A.; Landis, E.; Maier, D.; Silberschatz, A.

2003-01-01

Computer scientists, biologists, and natural resource managers recently met to examine the prospects for advancing computer science and information technology research by focusing on the complex and often-unique challenges found in the biodiversity and ecosystem domain. The workshop and its final report reveal that the biodiversity and ecosystem sciences are fundamentally information sciences and often address problems having distinctive attributes of scale and socio-technical complexity. The paper provides an overview of the emerging field of biodiversity and ecosystem informatics and demonstrates how the demands of biodiversity and ecosystem research can advance our understanding and use of information technologies.

Systematic Control and Management of Data Integrity, Quality and Provenance for Command and Control Applications

DTIC Science & Technology

2010-01-24

assess the trustworthiness of sensor data. Mohamed Nabeel (PhD student), Department of Computer Science. M. Nabeel has been involved in the research...April 7-12, 2008, Cancun, Mexico. 10. M. Nabeel , E. Bertino, "Secure Delta-Publishing of XML Content", Poster Paper, Proceedings of 24th...30, 2007, Vilamoura, Portugal, Lecture Notes in Computer Science 4804, Springer 2007. 12. M. Nabeel , E. Bertino, "A Structure Preserving Approach for

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia

PubMed Central

Safdari, Reza; Shahmoradi, Leila; Hosseini-beheshti, Molouk-sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-01-01

Introduction: Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. Materials and Methods: This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. Findings: In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics’ sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Results and Discussion: Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics. PMID:26635440

Analogical Processes in Learning

DTIC Science & Technology

1980-09-15

Stilluater, MN 55082 1200 19th Street NW 1 r. Genevieve Haddad Washington, DC 20208 1 Mr Avron Barr Program Manager Department of Computer Science Life ...Jack A. Thorp. Maj., USAF I Dr. Kenneth Bowles Life Sciences Directorate I Dr. Andrew R. Molnar Institute for Information Sciences AFOSR Science... Uiversity OGTI 31 1 Dr. Frank Withrow Stanford Univrsit Arlington Annex U. S. Office of Education Stanford. CA 91305 Columbia Pike at Arlington Ridge Rd

1999 NCCS Highlights

NASA Technical Reports Server (NTRS)

Bennett, Jerome (Technical Monitor)

2002-01-01

The NASA Center for Computational Sciences (NCCS) is a high-performance scientific computing facility operated, maintained and managed by the Earth and Space Data Computing Division (ESDCD) of NASA Goddard Space Flight Center's (GSFC) Earth Sciences Directorate. The mission of the NCCS is to advance leading-edge science by providing the best people, computers, and data storage systems to NASA's Earth and space sciences programs and those of other U.S. Government agencies, universities, and private institutions. Among the many computationally demanding Earth science research efforts supported by the NCCS in Fiscal Year 1999 (FY99) are the NASA Seasonal-to-Interannual Prediction Project, the NASA Search and Rescue Mission, Earth gravitational model development efforts, the National Weather Service's North American Observing System program, Data Assimilation Office studies, a NASA-sponsored project at the Center for Ocean-Land-Atmosphere Studies, a NASA-sponsored microgravity project conducted by researchers at the City University of New York and the University of Pennsylvania, the completion of a satellite-derived global climate data set, simulations of a new geodynamo model, and studies of Earth's torque. This document presents highlights of these research efforts and an overview of the NCCS, its facilities, and its people.

SPAN: Ocean science

NASA Technical Reports Server (NTRS)

Thomas, Valerie L.; Koblinsky, Chester J.; Webster, Ferris; Zlotnicki, Victor; Green, James L.

1987-01-01

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.

36 CFR 200.1 - Central organization.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., engineering, lands, aviation, and computer systems. The National Forest System includes: 155 Proclaimed or... other environmental concerns, forest insects and disease, forest fire and atmospheric science. Plans and...-wide management of systems and computer applications. [41 FR 24350, June 16, 1976, as amended at 42 FR...

36 CFR 200.1 - Central organization.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., engineering, lands, aviation, and computer systems. The National Forest System includes: 155 Proclaimed or... other environmental concerns, forest insects and disease, forest fire and atmospheric science. Plans and...-wide management of systems and computer applications. [41 FR 24350, June 16, 1976, as amended at 42 FR...

36 CFR 200.1 - Central organization.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., engineering, lands, aviation, and computer systems. The National Forest System includes: 155 Proclaimed or... other environmental concerns, forest insects and disease, forest fire and atmospheric science. Plans and...-wide management of systems and computer applications. [41 FR 24350, June 16, 1976, as amended at 42 FR...

36 CFR 200.1 - Central organization.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., engineering, lands, aviation, and computer systems. The National Forest System includes: 155 Proclaimed or... other environmental concerns, forest insects and disease, forest fire and atmospheric science. Plans and...-wide management of systems and computer applications. [41 FR 24350, June 16, 1976, as amended at 42 FR...

The FIFE Project at Fermilab

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

Box, D.; Boyd, J.; Di Benedetto, V.

2016-01-01

The FabrIc for Frontier Experiments (FIFE) project is an initiative within the Fermilab Scientific Computing Division designed to steer the computing model for non-LHC Fermilab experiments across multiple physics areas. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying size, needs, and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of solutions for high throughput computing, data management, database access and collaboration management within an experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid compute sites alongmore » with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including a common job submission service, software and reference data distribution through CVMFS repositories, flexible and robust data transfer clients, and access to opportunistic resources on the Open Science Grid. The progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken the leading role in defining the computing model for Fermilab experiments, aided in the design of experiments beyond those hosted at Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide.« less

Power monitoring and control for large scale projects: SKA, a case study

NASA Astrophysics Data System (ADS)

Barbosa, Domingos; Barraca, João. Paulo; Maia, Dalmiro; Carvalho, Bruno; Vieira, Jorge; Swart, Paul; Le Roux, Gerhard; Natarajan, Swaminathan; van Ardenne, Arnold; Seca, Luis

2016-07-01

Large sensor-based science infrastructures for radio astronomy like the SKA will be among the most intensive datadriven projects in the world, facing very high demanding computation, storage, management, and above all power demands. The geographically wide distribution of the SKA and its associated processing requirements in the form of tailored High Performance Computing (HPC) facilities, require a Greener approach towards the Information and Communications Technologies (ICT) adopted for the data processing to enable operational compliance to potentially strict power budgets. Addressing the reduction of electricity costs, improve system power monitoring and the generation and management of electricity at system level is paramount to avoid future inefficiencies and higher costs and enable fulfillments of Key Science Cases. Here we outline major characteristics and innovation approaches to address power efficiency and long-term power sustainability for radio astronomy projects, focusing on Green ICT for science and Smart power monitoring and control.

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

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.

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.

A Data-Based Financial Management Information System (FMIS) for Administrative Sciences Department

DTIC Science & Technology

1990-12-01

Financial Management Information System that would result in improved management of financial assets, better use of clerical skills, and more detailed...develops and implements a personal computer-based Management Information System for the Management of the many funding accounts controlled by the...different software programs, into a single all-encompassing Management Information System . The system was written using dBASE IV and is currently operational.

List of Publications of the U.S. Army Engineer Waterways Experiment Station. Volume 2

DTIC Science & Technology

1993-09-01

Station List of Publications of the U.S. Army Engineer Waterways Experiment Station Volume II compiled by Research Library Information Management Division...Waterways Experiment Station for Other Agencies Air Base Survivability Systems Management Office Headquarters .............................. Z-1 Airport... manages , conducts, and coordinates research and development in the Information Management (IM) technology areas that include computer science

Why the Petascale era will drive improvements in the management of the full lifecycle of earth science data.

NASA Astrophysics Data System (ADS)

Wyborn, L.

2012-04-01

The advent of the petascale era, in both storage and compute facilities, will offer new opportunities for earth scientists to transform the way they do their science and to undertake cross-disciplinary science at a global scale. No longer will data have to be averaged and subsampled: it can be analysed to its fullest resolution at national or even global scales. Much larger data volumes can be analysed in single passes and at higher resolution: large scale cross domain science is now feasible. However, in general, earth sciences have been slow to capitalise on the potential of these new petascale compute facilities: many struggle to even use terascale facilities. Our chances of using these new facilities will require a vast improvement in the management of the full life cycle of data: in reality it will need to be transformed. Many of our current issues with earth science data are historic and stem from the limitations of early data storage systems. As storage was so expensive, metadata was usually stored separate from the data and attached as a readme file. Likewise, attributes that defined uncertainty, reliability and traceability were recoded in lab note books and rarely stored with the data. Data were routinely transferred as files. The new opportunities require that the traditional discover, display and locally download and process paradigm is too limited. For data access and assimilation to be improved, data will need to be self describing. For heterogeneous data to be rapidly integrated attributes such as reliability, uncertainty and traceability will need to be systematically recorded with each observation. The petascale era also requires that individual data files be transformed and aggregated into calibrated data arrays or data cubes. Standards become critical and are the enablers of integration. These changes are common to almost every science discipline. What makes earth sciences unique is that many domains record time series data, particularly in the environmental geosciences areas (weathering, soil changes, climate change). The data life cycle will be measured in decades and centuries, not years. Preservation over such time spans is quite a challenge to the earth sciences as data will have to be managed over many evolutions of software and hardware. The focus has to be on managing the data and not the media. Currently storage is not an issue, but it is predicted that data volumes will soon exceed the effective storage media than can be physically manufactured. This means that organisations will have to think about disposal and destruction of data. For earth sciences, this will be a particularly sensitive issue. Petascale computing offers many new opportunities to the earth sciences and by 2020 exascale computers will be a reality. To fully realise these opportunities the earth sciences needs to actively and systematically rethink what the ramifications of these new systems will have on current practices for data storage, discovery, access and assimilation.

Conflict Management in Collaborative Engineering Design: Basic Research in Fundamental Theory, Modeling Framework, and Computer Support for Collaborative Engineering Activities

DTIC Science & Technology

2002-01-01

behaviors are influenced by social interactions, and to how modern IT sys- tems should be designed to support these group technical activities. The...engineering disciplines to behavior, decision, psychology, organization, and the social sciences. “Conflict manage- ment activity in collaborative...Researchers instead began to search for an entirely new paradigm, starting from a theory in social science, to construct a conceptual framework to describe

Mobile Devices in Health Education: Current Use and Practice

ERIC Educational Resources Information Center

Ducut, Erick; Fontelo, Paul

2008-01-01

The increasing amount of new scientific information made available by computers and the Internet is demonstrated by the growing number of available health sciences journals. Medical students, nursing students, those in other health science disciplines, and clinicians need to make information more manageable and accessible, especially at the point…

Using Ontologies for Knowledge Management: An Information Systems Perspective.

ERIC Educational Resources Information Center

Jurisica, Igor; Mylopoulos, John; Yu, Eric

1999-01-01

Surveys some of the basic concepts that have been used in computer science for the representation of knowledge and summarizes some of their advantages and drawbacks. Relates these techniques to information sciences theory and practice. Concepts are classified in four broad ontological categories: static ontology, dynamic ontology, intentional…

Soft Skills in Practice and in Education: An Evaluation

ERIC Educational Resources Information Center

Wahl, Harald; Kaufmann, Christian; Eckkrammer, Florian; Mense, Alexander; Gollner, Helmut; Himmler, Christian; Rogner, Wolf; Baierl, Thomas; Slobodian, Roman

2012-01-01

The paper measures the soft skills needs of companies and industry to technical oriented academic graduates, especially coming from IT course programs like business informatics, computer science, or information management. Therefore, between March and September 2010, two groups of researchers at the University of Applied Sciences (UAS) Technikum…

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

NASA Astrophysics Data System (ADS)

Klimentov, A.; Buncic, P.; De, K.; Jha, S.; Maeno, T.; Mount, R.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Porter, R. J.; Read, K. F.; Vaniachine, A.; Wells, J. C.; Wenaus, T.

2015-05-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(102) sites, O(105) cores, O(108) jobs per year, O(103) users, and ATLAS data volume is O(1017) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled ‘Next Generation Workload Management and Analysis System for Big Data’ (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. We will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.

The international emergency management and engineering conference 1995: Proceedings. Globalization of emergency management and engineering: National and international issues concerning research and applications

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

Sullivan, J.D.; Wybo, J.L.; Buisson, L.

1995-12-31

This conference was held May 9--12, 1995 in Nice, France. The purpose of this conference was to provide a forum for exchange of state-of-the-art information to cope more effectively with emergencies. Attention is focused on advance technology from both a managerial and a scientific viewpoint. Interests include computers and communication systems as well as the social science and management aspects involved in emergency management and engineering. The major sections are: Management and Social Sciences; Training; Natural Disasters; Nuclear Hazards; Chemical Hazards; Research; and Applications. Individual papers have been processed separately for inclusion in the appropriate data bases.

dV/dt - Accelerating the Rate of Progress towards Extreme Scale Collaborative Science

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

Livny, Miron

This report introduces publications that report the results of a project that aimed to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources,deploying the applications and data on the resources, managing applications and resources during run.

Template Interfaces for Agile Parallel Data-Intensive Science

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

Ramakrishnan, Lavanya; Gunter, Daniel; Pastorello, Gilerto Z.

Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres ismore » addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable "templates" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.« less

Cloudbus Toolkit for Market-Oriented Cloud Computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Pandey, Suraj; Vecchiola, Christian

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.

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.

The 1984 NASA/ASEE summer faculty fellowship program

NASA Technical Reports Server (NTRS)

Mcinnis, B. C.; Duke, M. B.; Crow, B.

1984-01-01

An overview is given of the program management and activities. Participants and research advisors are listed. Abstracts give describe and present results of research assignments performed by 31 fellows either at the Johnson Space Center, at the White Sands test Facility, or at the California Space Institute in La Jolla. Disciplines studied include engineering; biology/life sciences; Earth sciences; chemistry; mathematics/statistics/computer sciences; and physics/astronomy.

Towards a Multi-Mission, Airborne Science Data System Environment

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Hardman, S.; Law, E.; Freeborn, D.; Kay-Im, E.; Lau, G.; Oswald, J.

2011-12-01

NASA earth science instruments are increasingly relying on airborne missions. However, traditionally, there has been limited common infrastructure support available to principal investigators in the area of science data systems. As a result, each investigator has been required to develop their own computing infrastructures for the science data system. Typically there is little software reuse and many projects lack sufficient resources to provide a robust infrastructure to capture, process, distribute and archive the observations acquired from airborne flights. At NASA's Jet Propulsion Laboratory (JPL), we have been developing a multi-mission data system infrastructure for airborne instruments called the Airborne Cloud Computing Environment (ACCE). ACCE encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation. This includes improving data system interoperability across each instrument. A principal characteristic is being able to provide an agile infrastructure that is architected to allow for a variety of configurations of the infrastructure from locally installed compute and storage services to provisioning those services via the "cloud" from cloud computer vendors such as Amazon.com. Investigators often have different needs that require a flexible configuration. The data system infrastructure is built on the Apache's Object Oriented Data Technology (OODT) suite of components which has been used for a number of spaceborne missions and provides a rich set of open source software components and services for constructing science processing and data management systems. In 2010, a partnership was formed between the ACCE team and the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to support the data processing and data management needs. A principal goal is to provide support for the Fourier Transform Spectrometer (FTS) instrument which will produce over 700,000 soundings over the life of their three-year mission. The cost to purchase and operate a cluster-based system in order to generate Level 2 Full Physics products from this data was prohibitive. Through an evaluation of cloud computing solutions, Amazon's Elastic Compute Cloud (EC2) was selected for the CARVE deployment. As the ACCE infrastructure is developed and extended to form an infrastructure for airborne missions, the experience of working with CARVE has provided a number of lessons learned and has proven to be important in reinforcing the unique aspects of airborne missions and the importance of the ACCE infrastructure in developing a cost effective, flexible multi-mission capability that leverages emerging capabilities in cloud computing, workflow management, and distributed computing.

Producing a Data Dictionary from an Extensible Markup Language (XML) Schemain the Global Force Management Data Initiative

DTIC Science & Technology

2017-02-01

entity relationship (diagram) EwID Enterprise-wide Identifier FMID Force Management Identifier GFM Global Force Management HTML Hypertext Markup Language... Management Data Initiative by Frederick S Brundick Approved for public release; distribution is unlimited. NOTICES Disclaimers The findings in this report...Schema in the Global Force Management Data Initiative by Frederick S Brundick Computing and Information Sciences Directorate, ARL Approved for public

Progress on the Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Box, Dennis; Boyd, Joseph; Dykstra, Dave; Garzoglio, Gabriele; Herner, Kenneth; Kirby, Michael; Kreymer, Arthur; Levshina, Tanya; Mhashilkar, Parag; Sharma, Neha

2015-12-01

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. The progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide.

32 CFR 242b.7 - Officers of the University.

Code of Federal Regulations, 2012 CFR

2012-07-01

... THE HEALTH SCIENCES § 242b.7 Officers of the University. (a) Dean of the University. (1) The Regents... Services and Materiel Acquisition; (C) Military Personnel; (D) Civilian Personnel; (E) Computer Operations... Management and Computer Operations will report directly to the Vice President for Operations; the Civilian...

32 CFR 242b.7 - Officers of the University.

Code of Federal Regulations, 2011 CFR

2011-07-01

... THE HEALTH SCIENCES § 242b.7 Officers of the University. (a) Dean of the University. (1) The Regents... Services and Materiel Acquisition; (C) Military Personnel; (D) Civilian Personnel; (E) Computer Operations... Management and Computer Operations will report directly to the Vice President for Operations; the Civilian...

32 CFR 242b.7 - Officers of the University.

Code of Federal Regulations, 2010 CFR

2010-07-01

... THE HEALTH SCIENCES § 242b.7 Officers of the University. (a) Dean of the University. (1) The Regents... Services and Materiel Acquisition; (C) Military Personnel; (D) Civilian Personnel; (E) Computer Operations... Management and Computer Operations will report directly to the Vice President for Operations; the Civilian...

32 CFR 242b.7 - Officers of the University.

Code of Federal Regulations, 2013 CFR

2013-07-01

... THE HEALTH SCIENCES § 242b.7 Officers of the University. (a) Dean of the University. (1) The Regents... Services and Materiel Acquisition; (C) Military Personnel; (D) Civilian Personnel; (E) Computer Operations... Management and Computer Operations will report directly to the Vice President for Operations; the Civilian...

32 CFR 242b.7 - Officers of the University.

Code of Federal Regulations, 2014 CFR

2014-07-01

... THE HEALTH SCIENCES § 242b.7 Officers of the University. (a) Dean of the University. (1) The Regents... Services and Materiel Acquisition; (C) Military Personnel; (D) Civilian Personnel; (E) Computer Operations... Management and Computer Operations will report directly to the Vice President for Operations; the Civilian...

Women in Technology: College Experiences That Are Correlated with Long-Term Career Success

ERIC Educational Resources Information Center

Moreno, Melissa Gearhart

2017-01-01

Women are underrepresented in technology careers because they pursue technology degrees less frequently and leave technology careers at greater numbers than do men. By analyzing a representative dataset of college graduates with degrees in computer science, computer engineering, and management information systems, this study identified…

Flatbrain Spreadsheets: Mindtool outside the Box?

ERIC Educational Resources Information Center

Lamontagne, Claude; Desjardins, Francois; Benard, Michele

2007-01-01

Managing the pedagogical aspects of the "computational turn" that is occurring within the Humanities in general and the disciplines associated with cognitive science and neuroscience in particular, first implies facing the challenge of introducing students to computation. This paper presents what has proven to be an efficient approach to bringing…

Computational sciences in the upstream oil and gas industry

PubMed Central

Halsey, Thomas C.

2016-01-01

The predominant technical challenge of the upstream oil and gas industry has always been the fundamental uncertainty of the subsurface from which it produces hydrocarbon fluids. The subsurface can be detected remotely by, for example, seismic waves, or it can be penetrated and studied in the extremely limited vicinity of wells. Inevitably, a great deal of uncertainty remains. Computational sciences have been a key avenue to reduce and manage this uncertainty. In this review, we discuss at a relatively non-technical level the current state of three applications of computational sciences in the industry. The first of these is seismic imaging, which is currently being revolutionized by the emergence of full wavefield inversion, enabled by algorithmic advances and petascale computing. The second is reservoir simulation, also being advanced through the use of modern highly parallel computing architectures. Finally, we comment on the role of data analytics in the upstream industry. This article is part of the themed issue ‘Energy and the subsurface’. PMID:27597785

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.

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment.

PubMed

Harrigan, Robert L; Yvernault, Benjamin C; Boyd, Brian D; Damon, Stephen M; Gibney, Kyla David; Conrad, Benjamin N; Phillips, Nicholas S; Rogers, Baxter P; Gao, Yurui; Landman, Bennett A

2016-01-01

The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and REDCap to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers. Copyright © 2015 Elsevier Inc. All rights reserved.

Service-Oriented Architectures and Project Optimization for a Special Cost Management Problem Creating Synergies for Informed Change between Qualitative and Quantitative Strategic Management Processes

DTIC Science & Technology

2010-05-01

Science, Werner Heisenberg -Weg 39,85577 Neubiberg, Germany,CA,93943 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S...University of the Federal Armed Forces of Germany Institute for Theoretic Computer Science Mathematics and Operations Research Werner Heisenberg -Weg...Research Werner Heisenberg -Weg 39 85577 Neubiberg, Germany Phone +49 89 6004 2400 Marco Schuler—Marco Schuler is an active Officer of the Federal

Analysis of the United States Computer Emergency Readiness Team’s (U.S. CERT) EINSTEIN III Intrusion Detection System, and Its Impact on Privacy

DTIC Science & Technology

2013-03-01

Arlington, VA 22202–4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704–0188) Washington DC 20503. 1. AGENCY USE ONLY...University, 2004 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN INFORMATION TECHNOLOGY MANAGEMENT...Fulp Second Reader Dr. Dan Boger Chair, Department of Information Sciences iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT To secure

Estimation of Time Requirements during Planning: Interactions between Motivation and Cognition.

DTIC Science & Technology

1980-11-01

Haddad Program Manager Life Sciences Directorate AFOSR bollinq APB, DC 20332 44 Er. Party Rockway (AFHRL/IT) Lowry AFd Colorado 90230 45 3700 TCHTW/T!GH...10016 125 Dr. Robert Smith oepartment of Computer Science [utqers Uiversity New Brunswick. NJ 09903 126 Dr. Richard Snow School of Education Stanford

The Kepler Science Data Processing Pipeline Source Code Road Map

NASA Technical Reports Server (NTRS)

Wohler, Bill; Jenkins, Jon M.; Twicken, Joseph D.; Bryson, Stephen T.; Clarke, Bruce Donald; Middour, Christopher K.; Quintana, Elisa Victoria; Sanderfer, Jesse Thomas; Uddin, Akm Kamal; Sabale, Anima;

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

The Implementation of Web Conferencing Technologies in Online Graduate Classes

ERIC Educational Resources Information Center

Zotti, Robert

2017-01-01

This dissertation examines the implementation of web conferencing technology in online graduate courses within management, engineering, and computer science programs. Though the spread of learning management systems over the past two decades has been dramatic, the use of web conferencing technologies has curiously lagged. The real-time…

Frameworks Coordinate Scientific Data Management

NASA Technical Reports Server (NTRS)

2012-01-01

Jet Propulsion Laboratory computer scientists developed a unique software framework to help NASA manage its massive amounts of science data. Through a partnership with the Apache Software Foundation of Forest Hill, Maryland, the technology is now available as an open-source solution and is in use by cancer researchers and pediatric hospitals.

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'.

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. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

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.

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

PubMed

Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

2012-01-01

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

Fuels planning: science synthesis and integration; forest structure and fire hazard fact sheet 03: visualizing forest structure and fuels

Treesearch

Rocky Mountain Research Station USDA Forest Service

2004-01-01

The software described in this fact sheet provides managers with tools for visualizing forest and fuels information. Computer-based landscape simulations can help visualize stand and landscape conditions and the effects of different management treatments and fuel changes over time. These visualizations can assist forest planning by considering a range of management...

Complex Systems Simulation and Optimization | Computational Science | NREL

Science.gov Websites

account. Stochastic Optimization and Control: Formulation and implementation of advanced optimization and account uncertainty. Contact Wesley Jones Group Manager, Complex Systems Simulation and Optimiziation

Optimization of knowledge-based systems and expert system building tools

NASA Technical Reports Server (NTRS)

Yasuda, Phyllis; Mckellar, Donald

1993-01-01

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

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).

Desktop Social Science: Coming of Age.

ERIC Educational Resources Information Center

Dwyer, David C.; And Others

Beginning in 1985, Apple Computer, Inc. and several school districts began a collaboration to examine the impact of intensive computer use on instruction and learning in K-12 classrooms. This paper follows the development of a Macintosh II-based management and retrieval system for text data undertaken to store and retrieve oral reflections of…

ODU-CAUSE: Computer Based Learning Lab.

ERIC Educational Resources Information Center

Sachon, Michael W.; Copeland, Gary E.

This paper describes the Computer Based Learning Lab (CBLL) at Old Dominion University (ODU) as a component of the ODU-Comprehensive Assistance to Undergraduate Science Education (CAUSE) Project. Emphasis is directed to the structure and management of the facility and to the software under development by the staff. Serving the ODU-CAUSE User Group…

Teach or No Teach: Is Large System Education Resurging?

ERIC Educational Resources Information Center

Sharma, Aditya; Murphy, Marianne C.

2011-01-01

Legacy or not, mainframe education is being taught at many U.S. universities. Some computer science programs have always had some large system content but there does appear to be resurgence of mainframe related content in business programs such as Management Information Systems (MIS) and Computer Information Systems (CIS). Many companies such as…

Building Professionalism and Employability Skills: Embedding Employer Engagement within First-Year Computing Modules

ERIC Educational Resources Information Center

Hanna, Philip; Allen, Angela; Kane, Russell; Anderson, Neil; McGowan, Aidan; Collins, Matthew; Hutchison, Malcolm

2015-01-01

This paper outlines a means of improving the employability skills of first-year university students through a closely integrated model of employer engagement within computer science modules. The outlined approach illustrates how employability skills, including communication, teamwork and time management skills, can be contextualised in a manner…

A Disciplined Architectural Approach to Scaling Data Analysis for Massive, Scientific Data

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Braverman, A. J.; Cinquini, L.; Turmon, M.; Lee, H.; Law, E.

2014-12-01

Data collections across remote sensing and ground-based instruments in astronomy, Earth science, and planetary science are outpacing scientists' ability to analyze them. Furthermore, the distribution, structure, and heterogeneity of the measurements themselves pose challenges that limit the scalability of data analysis using traditional approaches. Methods for developing science data processing pipelines, distribution of scientific datasets, and performing analysis will require innovative approaches that integrate cyber-infrastructure, algorithms, and data into more systematic approaches that can more efficiently compute and reduce data, particularly distributed data. This requires the integration of computer science, machine learning, statistics and domain expertise to identify scalable architectures for data analysis. The size of data returned from Earth Science observing satellites and the magnitude of data from climate model output, is predicted to grow into the tens of petabytes challenging current data analysis paradigms. This same kind of growth is present in astronomy and planetary science data. One of the major challenges in data science and related disciplines defining new approaches to scaling systems and analysis in order to increase scientific productivity and yield. Specific needs include: 1) identification of optimized system architectures for analyzing massive, distributed data sets; 2) algorithms for systematic analysis of massive data sets in distributed environments; and 3) the development of software infrastructures that are capable of performing massive, distributed data analysis across a comprehensive data science framework. NASA/JPL has begun an initiative in data science to address these challenges. Our goal is to evaluate how scientific productivity can be improved through optimized architectural topologies that identify how to deploy and manage the access, distribution, computation, and reduction of massive, distributed data, while managing the uncertainties of scientific conclusions derived from such capabilities. This talk will provide an overview of JPL's efforts in developing a comprehensive architectural approach to data science.

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators

PubMed Central

2017-01-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology. PMID:29049281

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators.

PubMed

Barone, Lindsay; Williams, Jason; Micklos, David

2017-10-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC-acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.

The Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Kirby, Michael

2014-06-01

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere; 2) an extensive data management system for managing local and remote caches, cataloging, querying, moving, and tracking the use of data; 3) custom and generic database applications for calibrations, beam information, and other purposes; 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.

Information revolution in nursing and health care: educating for tomorrow's challenge.

PubMed

Kooker, B M; Richardson, S S

1994-06-01

Current emphasis on the national electronic highway and a national health database for comparative health care reporting demonstrates society's increasing reliance on information technology. The efficient electronic processing and managing of data, information, and knowledge are critical for survival in tomorrow's health care organization. To take a leadership role in this information revolution, informatics nurse specialists must possess competencies that incorporate information science, computer science, and nursing science for successful information system development. In selecting an appropriate informatics educational program or to hire an individual capable of meeting this challenge, nurse administrators must look for the following technical knowledge and skill set: information management principles, system development life cycle, programming languages, file design and access, hardware and network architecture, project management skills, and leadership abilities.

Research and technology at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

1983-01-01

Cryogenic engineering, hypergolic engineering, hazardous warning, structures and mechanics, computer sciences, communications, meteorology, technology applications, safety engineering, materials analysis, biomedicine, and engineering management and training aids research are reviewed.

The DEVELOP Program as a Unique Applied Science Internship

NASA Astrophysics Data System (ADS)

Skiles, J. W.; Schmidt, C. L.; Ruiz, M. L.; Cawthorn, J.

2004-12-01

The NASA mission includes "Inspiring the next generation of explorers" and "Understanding and protecting our home planet". DEVELOP students conduct research projects in Earth Systems Science, gaining valuable training and work experience, which support accomplishing this mission. This presentation will describe the DEVELOP Program, a NASA human capital development initiative, which is student run and student led with NASA scientists serving as mentors. DEVELOP began in 1998 at NASA's Langley Research Center in Virginia and expanded to NASA's Stennis Space Center in Mississippi and Marshall Space Flight Center in Alabama in 2002. NASA's Ames Research Center in California began DEVELOP activity in 2003. DEVELOP is a year round activity. High school through graduate school students participate in DEVELOP with students' backgrounds encompassing a wide variety of academic majors such as engineering, biology, physics, mathematics, computer science, remote sensing, geographic information systems, business, and geography. DEVELOP projects are initiated when county, state, or tribal governments submit a proposal requesting students work on local projects. When a project is selected, science mentors guide students in the application of NASA applied science and technology to enhance decision support tools for customers. Partnerships are established with customers, professional organizations and state and federal agencies in order to leverage resources needed to complete research projects. Student teams are assigned a project and are responsible for creating an inclusive project plan beginning with the design and approach of the study, the timeline, and the deliverables for the customer. Project results can consist of student papers, both team and individually written, face-to-face meetings and seminars with customers, presentations at national meetings in the form of posters and oral papers, displays at the Western and Southern Governors' Associations, and visualizations produced by the students. Projects have included Homeland Security in Virginia, Energy Management in New Mexico, Water Management in Mississippi, Air Quality Management in Alabama, Invasive Species mapping in Nevada, Public Health risk assessment in California, Disaster Management in Oklahoma, Agricultural Efficiency in South Dakota, Coastal Management in Louisiana and Carbon Management in Oregon. DEVELOP students gain experience in applied science, computer technology, and project management. Several DEVELOP projects will be demonstrated and discussed during this presentation. DEVELOP is sponsored by the Applications Division of NASA's Science Mission Directorate.

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.

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

NASA Technical Reports Server (NTRS)

1991-01-01

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement.

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.

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

CPE--A New Perspective: The Impact of the Technology Revolution. Proceedings of the Computer Performance Evaluation Users Group Meeting (19th, San Francisco, California, October 25-28, 1983). Final Report. Reports on Computer Science and Technology.

ERIC Educational Resources Information Center

Mobray, Deborah, Ed.

Papers on local area networks (LANs), modelling techniques, software improvement, capacity planning, software engineering, microcomputers and end user computing, cost accounting and chargeback, configuration and performance management, and benchmarking presented at this conference include: (1) "Theoretical Performance Analysis of Virtual…

Open Component Portability Infrastructure (OPENCPI)

DTIC Science & Technology

2009-11-01

Disk Drive 7 1 www.antec.com P182 $120. ATX Mid Tower Computer Case 8 1 www.xilinx.com HW-V5-ML555-G $2200. Xilinx ML555 V5 Dev Kit Notes: Cost...s/ GEORGE RAMSEYER EDWARD J. JONES, Deputy Chief Work Unit Manager Advanced Computing ...uniquely positioned to meet the goals of the Software Systems Stockroom (S3) since in some sense component-based systems are computer -science’s

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

Progress on the FabrIc for Frontier Experiments project at Fermilab

DOE PAGES

Box, Dennis; Boyd, Joseph; Dykstra, Dave; ...

2015-12-23

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercialmore » cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. Hence, the progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide« less

Computer Sciences and Data Systems, volume 1

NASA Technical Reports Server (NTRS)

1987-01-01

Topics addressed include: software engineering; university grants; institutes; concurrent processing; sparse distributed memory; distributed operating systems; intelligent data management processes; expert system for image analysis; fault tolerant software; and architecture research.

7 CFR 2.93 - Director, Office of Procurement and Property Management.

Code of Federal Regulations, 2012 CFR

2012-01-01

... agricultural sciences, related to establishing and implementing Federal biobased procurement and voluntary... available to organizations excess or surplus computers or other technical equipment of the Department for...

Extratropical Cyclone

Atmospheric Science Data Center

2013-04-16

... using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

7 CFR 2.93 - Director, Office of Procurement and Property Management.

Code of Federal Regulations, 2014 CFR

2014-01-01

... agricultural sciences, related to establishing and implementing Federal biobased procurement and voluntary... available to organizations excess or surplus computers or other technical equipment of the Department for...

7 CFR 2.93 - Director, Office of Procurement and Property Management.

Code of Federal Regulations, 2013 CFR

2013-01-01

... agricultural sciences, related to establishing and implementing Federal biobased procurement and voluntary... available to organizations excess or surplus computers or other technical equipment of the Department for...

7 CFR 2.93 - Director, Office of Procurement and Property Management.

Code of Federal Regulations, 2011 CFR

2011-01-01

... agricultural sciences, related to establishing and implementing Federal biobased procurement and voluntary... available to organizations excess or surplus computers or other technical equipment of the Department for...

Command and data handling of science signals on Spacelab

NASA Technical Reports Server (NTRS)

Mccain, H. G.

1975-01-01

The Orbiter Avionics and the Spacelab Command and Data Management System (CDMS) combine to provide a relatively complete command, control, and data handling service to the instrument complement during a Shuttle Sortie Mission. The Spacelab CDMS services the instruments and the Orbiter in turn services the Spacelab. The CDMS computer system includes three computers, two I/O units, a mass memory, and a variable number of remote acquisition units. Attention is given to the CDMS high rate multiplexer, CDMS tape recorders, closed circuit television for the visual monitoring of payload bay and cabin area activities, methods of science data acquisition, questions of transmission and recording, CDMS experiment computer usage, and experiment electronics.

Multidimensional Space-Time Methodology for Development of Planetary and Space Sciences, S-T Data Management and S-T Computational Tomography

NASA Astrophysics Data System (ADS)

Andonov, Zdravko

This R&D represent innovative multidimensional 6D-N(6n)D Space-Time (S-T) Methodology, 6D-6nD Coordinate Systems, 6D Equations, new 6D strategy and technology for development of Planetary Space Sciences, S-T Data Management and S-T Computational To-mography. . . The Methodology is actual for brain new RS Microwaves' Satellites and Compu-tational Tomography Systems development, aimed to defense sustainable Earth, Moon, & Sun System evolution. Especially, extremely important are innovations for monitoring and protec-tion of strategic threelateral system H-OH-H2O Hydrogen, Hydroxyl and Water), correspond-ing to RS VHRS (Very High Resolution Systems) of 1.420-1.657-22.089GHz microwaves. . . One of the Greatest Paradox and Challenge of World Science is the "transformation" of J. L. Lagrange 4D Space-Time (S-T) System to H. Minkovski 4D S-T System (O-X,Y,Z,icT) for Einstein's "Theory of Relativity". As a global result: -In contemporary Advanced Space Sciences there is not real adequate 4D-6D Space-Time Coordinate System and 6D Advanced Cosmos Strategy & Methodology for Multidimensional and Multitemporal Space-Time Data Management and Tomography. . . That's one of the top actual S-T Problems. Simple and optimal nD S-T Methodology discovery is extremely important for all Universities' Space Sci-ences' Education Programs, for advances in space research and especially -for all young Space Scientists R&D!... The top ten 21-Century Challenges ahead of Planetary and Space Sciences, Space Data Management and Computational Space Tomography, important for successfully de-velopment of Young Scientist Generations, are following: 1. R&D of W. R. Hamilton General Idea for transformation all Space Sciences to Time Sciences, beginning with 6D Eukonal for 6D anisotropic mediums & velocities. Development of IERS Earth & Space Systems (VLBI; LLR; GPS; SLR; DORIS Etc.) for Planetary-Space Data Management & Computational Planetary & Space Tomography. 2. R&D of S. W. Hawking Paradigm for 2D Complex Time and Quan-tum Wave Cosmology Paradigm for Decision of the Main Problem of Contemporary Physics. 3. R&D of Einstein-Minkowski Geodesies' Paradigm in the 4D-Space-Time Continuum to 6D-6nD Space-Time Continuum Paradigms and 6D S-T Equations. . . 4. R&D of Erwin Schrüdinger 4D S-T Universe' Evolutional Equation; It's David Bohm 4D generalization for anisotropic mediums and innovative 6D -for instantaneously quantum measurement -Bohm-Schrüdinger 6D S-T Universe' Evolutional Equation. 5. R&D of brain new 6D Planning of S-T Experi-ments, brain new 6D Space Technicks and Space Technology Generalizations, especially for 6D RS VHRS Research, Monitoring and 6D Computational Tomography. 6. R&D of "6D Euler-Poisson Equations" and "6D Kolmogorov Turbulence Theory" for GeoDynamics and for Space Dynamics as evolution of Gauss-Riemann Paradigms. 7. R&D of N. Boneff NASA RD for Asteroid "Eros" & Space Science' Laws Evolution. 8. R&D of H. Poincare Paradigm for Nature and Cosmos as 6D Group of Transferences. 9. R&D of K. Popoff N-Body General Problem & General Thermodynamic S-T Theory as Einstein-Prigogine-Landau' Paradigms Development. ü 10. R&D of 1st GUT since 1958 by N. S. Kalitzin (Kalitzin N. S., 1958: Uber eine einheitliche Feldtheorie. ZAHeidelberg-ARI, WZHUmnR-B., 7 (2), 207-215) and "Multitemporal Theory of Relativity" -With special applications to Photon Rockets and all Space-Time R&D. GENERAL CONCLUSION: Multidimensional Space-Time Methodology is advance in space research, corresponding to the IAF-IAA-COSPAR Innovative Strategy and R&D Programs -UNEP, UNDP, GEOSS, GMES, Etc.

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

Situation resolution with context-sensitive fuzzy relations

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel; Buford, John; Lewis, Lundy

2009-05-01

Context plays a significant role in situation resolution by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of context have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of context in situation management, particularly how to resolve situations that are described by using fuzzy (inexact) relations among their components. We propose a language for describing context sensitive inexact constraints and an algorithm for interpreting relations using inexact (fuzzy) computations.

Generic, Type-Safe and Object Oriented Computer Algebra Software

NASA Astrophysics Data System (ADS)

Kredel, Heinz; Jolly, Raphael

Advances in computer science, in particular object oriented programming, and software engineering have had little practical impact on computer algebra systems in the last 30 years. The software design of existing systems is still dominated by ad-hoc memory management, weakly typed algorithm libraries and proprietary domain specific interactive expression interpreters. We discuss a modular approach to computer algebra software: usage of state-of-the-art memory management and run-time systems (e.g. JVM) usage of strongly typed, generic, object oriented programming languages (e.g. Java) and usage of general purpose, dynamic interactive expression interpreters (e.g. Python) To illustrate the workability of this approach, we have implemented and studied computer algebra systems in Java and Scala. In this paper we report on the current state of this work by presenting new examples.

Applications of Computer Science to the Management and Evaluation of the Educational Process.

ERIC Educational Resources Information Center

Hebenstreit, Jacques

This synthesis of reports from authors representing seven different countries discusses computerization as it applies to the management and evaluation of the educational process at all levels in developed countries. Focusing on the computerization of educational administration, the first of three sections of the paper suggests that advantages of…

Computer Science and Technology: Modeling and Measurement Techniques for Evaluation of Design Alternatives in the Implementation of Database Management Software. Final Report.

ERIC Educational Resources Information Center

Deutsch, Donald R.

This report describes a research effort that was carried out over a period of several years to develop and demonstrate a methodology for evaluating proposed Database Management System designs. The major proposition addressed by this study is embodied in the thesis statement: Proposed database management system designs can be evaluated best through…

Hurricane Jeanne

Atmospheric Science Data Center

2013-04-19

... view. The cloud height map was produced by automated computer recognition of the distinctive spatial features between images ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

High Performance Active Database Management on a Shared-Nothing Parallel Processor

DTIC Science & Technology

1998-05-01

either stored or virtual. A stored node is like a materialized view. It actually contains the specified tuples. A virtual node is like a real view...90292-6695 DL-5 COLUMBIA UNIV/DEPT COMPUTER SCIENCi ATTN: OR GAIL £. KAISER 450 COMPUTER SCIENCE 3LDG 500 WEST 12ÖTH STRSET NEW YORK NY 10027

System Architecture Development for Energy and Water Infrastructure Data Management and Geovisual Analytics

NASA Astrophysics Data System (ADS)

Berres, A.; Karthik, R.; Nugent, P.; Sorokine, A.; Myers, A.; Pang, H.

2017-12-01

Building an integrated data infrastructure that can meet the needs of a sustainable energy-water resource management requires a robust data management and geovisual analytics platform, capable of cross-domain scientific discovery and knowledge generation. Such a platform can facilitate the investigation of diverse complex research and policy questions for emerging priorities in Energy-Water Nexus (EWN) science areas. Using advanced data analytics, machine learning techniques, multi-dimensional statistical tools, and interactive geovisualization components, such a multi-layered federated platform is being developed, the Energy-Water Nexus Knowledge Discovery Framework (EWN-KDF). This platform utilizes several enterprise-grade software design concepts and standards such as extensible service-oriented architecture, open standard protocols, event-driven programming model, enterprise service bus, and adaptive user interfaces to provide a strategic value to the integrative computational and data infrastructure. EWN-KDF is built on the Compute and Data Environment for Science (CADES) environment in Oak Ridge National Laboratory (ORNL).

Enabling Earth Science: The Facilities and People of the NCCS

NASA Technical Reports Server (NTRS)

2002-01-01

The NCCS's mass data storage system allows scientists to store and manage the vast amounts of data generated by these computations, and its high-speed network connections allow the data to be accessed quickly from the NCCS archives. Some NCCS users perform studies that are directly related to their ability to run computationally expensive and data-intensive simulations. Because the number and type of questions scientists research often are limited by computing power, the NCCS continually pursues the latest technologies in computing, mass storage, and networking technologies. Just as important as the processors, tapes, and routers of the NCCS are the personnel who administer this hardware, create and manage accounts, maintain security, and assist the scientists, often working one on one with them.

Science Support: The Building Blocks of Active Data Curation

NASA Astrophysics Data System (ADS)

Guillory, A.

2013-12-01

While the scientific method is built on reproducibility and transparency, and results are published in peer reviewed literature, we have come to the digital age of very large datasets (now of the order of petabytes and soon exabytes) which cannot be published in the traditional way. To preserve reproducibility and transparency, active curation is necessary to keep and protect the information in the long term, and 'science support' activities provide the building blocks for active data curation. With the explosive growth of data in all fields in recent years, there is a pressing urge for data centres to now provide adequate services to ensure long-term preservation and digital curation of project data outputs, however complex those may be. Science support provides advice and support to science projects on data and information management, from file formats through to general data management awareness. Another purpose of science support is to raise awareness in the science community of data and metadata standards and best practice, engendering a culture where data outputs are seen as valued assets. At the heart of Science support is the Data Management Plan (DMP) which sets out a coherent approach to data issues pertaining to the data generating project. It provides an agreed record of the data management needs and issues within the project. The DMP is agreed upon with project investigators to ensure that a high quality documented data archive is created. It includes conditions of use and deposit to clearly express the ownership, responsibilities and rights associated with the data. Project specific needs are also identified for data processing, visualization tools and data sharing services. As part of the National Centre for Atmospheric Science (NCAS) and National Centre for Earth Observation (NCEO), the Centre for Environmental Data Archival (CEDA) fulfills this science support role of facilitating atmospheric and Earth observation data generating projects to ensure successful management of the data and accompanying information for reuse and repurpose. Specific examples at CEDA include science support provided to FAAM (Facility for Airborne Atmospheric Measurements) aircraft campaigns and large-scale modelling projects such as UPSCALE, the largest ever PRACE (Partnership for Advanced Computing in Europe) computational project, dependent on CEDA to provide the high-performance storage, transfer capability and data analysis environment on the 'super-data-cluster' JASMIN. The impact of science support on scientific research is conspicuous: better documented datasets with an increasing collection of metadata associated to the archived data, ease of data sharing with the use of standards in formats and metadata and data citation. These establish a high-quality of data management ensuring long-term preservation and enabling re-use by peer scientists which ultimately leads to faster paced progress in science.

Building a Data Science capability for USGS water research and communication

NASA Astrophysics Data System (ADS)

Appling, A.; Read, E. K.

2015-12-01

Interpreting and communicating water issues in an era of exponentially increasing information requires a blend of domain expertise, computational proficiency, and communication skills. The USGS Office of Water Information has established a Data Science team to meet these needs, providing challenging careers for diverse domain scientists and innovators in the fields of information technology and data visualization. Here, we detail the experience of building a Data Science capability as a bridging element between traditional water resources analyses and modern computing tools and data management techniques. This approach includes four major components: 1) building reusable research tools, 2) documenting data-intensive research approaches in peer reviewed journals, 3) communicating complex water resources issues with interactive web visualizations, and 4) offering training programs for our peers in scientific computing. These components collectively improve the efficiency, transparency, and reproducibility of USGS data analyses and scientific workflows.

Peculiarities of organization of project and research activity of students in computer science, physics and technology

NASA Astrophysics Data System (ADS)

Stolyarov, I. V.

2017-01-01

The author of this article manages a project and research activity of students in the areas of computer science, physics, engineering and biology, basing on the acquired experience in these fields. Pupils constantly become winners of competitions and conferences of different levels, for example, three of the finalists of Intel ISEF in 2013 in Phoenix (Arizona, USA) and in 2014 in Los Angeles (California, USA). In 2013 A. Makarychev received the "Small Nobel prize" in Computer Science section and special award sponsors - the company's CAST. Scientific themes and methods suggested by the author and developed in joint publications of students from Russia, Germany and Austria are the patents for invention and certificates for registration in the ROSPATENT. The article presents the results of the implementation of specific software and hardware systems in physics, engineering and medicine.

Prognocean Plus: the Science-Oriented Sea Level Prediction System as a Tool for Public Stakeholders

NASA Astrophysics Data System (ADS)

Świerczyńska, M. G.; Miziński, B.; Niedzielski, T.

2015-12-01

The novel real-time system for sea level prediction, known as Prognocean Plus, has been developed as a new generation service available through the Polish supercomputing grid infrastructure. The researchers can access the service at https://prognocean.plgrid.pl/. Although the system is science-oriented, we wish to discuss herein its potentials to enhance ocean management studies carried out routinely by public stakeholders. The system produces the short- and medium-term predictions of global altimetric gridded Sea Level Anomaly (SLA) time series, updated daily. The spatial resolution of the SLA forecasts is 1/4° x 1/4°, while the temporal resolution of prognoses is equal to 1 day. The system computes the predictions of time-variable ocean topography using five data-based models, which are not computationally demanding, enabling us to compare their skillfulness in respect to physically-based approaches commonly used by different sea level prediction systems. However, the aim of the system is not only to compute the predictions for science purposes, but primarily to build a user-oriented platform that serves the prognoses and their statistics to a broader community. Thus, we deliver the SLA forecasts as a rapid service available online. In order to provide potential users with the access to science results the Web Map Service (WMS) for Prognocean Plus is designed. We regularly publish the forecasts, both in the interactive graphical WMS service, available from the browser, as well as through the Web Coverage Service (WCS) standard. The Prognocean Plus system, as an early-response system, may be interesting for public stakeholders. It may be used for marine navigation as well as for climate risk management (delineate areas vulnerable to local sea level rise), marine management (advise offered for offshore activities) and coastal management (early warnings against coastal floodings).

FermiGrid - experience and future plans

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

Chadwick, K.; Berman, E.; Canal, P.

2007-09-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid and the WLCG. FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the Open Science Grid (OSG), EGEE and themore » Worldwide LHC Computing Grid Collaboration (WLCG). Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure--the successes and the problems.« less

DataHub: Science data management in support of interactive exploratory analysis

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Rubin, Mark R.

1993-01-01

The DataHub addresses four areas of significant needs: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactives nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc), in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

DataHub - Science data management in support of interactive exploratory analysis

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Rubin, Mark R.

1993-01-01

DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactive nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc.) in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis is on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Computer Simulation for Pain Management Education: A Pilot Study.

PubMed

Allred, Kelly; Gerardi, Nicole

2017-10-01

Effective pain management is an elusive concept in acute care. Inadequate knowledge has been identified as a barrier to providing optimal pain management. This study aimed to determine student perceptions of an interactive computer simulation as a potential method for learning pain management, as a motivator to read and learn more about pain management, preference over traditional lecture, and its potential to change nursing practice. A post-computer simulation survey with a mixed-methods descriptive design was used in this study. A college of nursing in a large metropolitan university in the Southeast United States. A convenience sample of 30 nursing students in a Bachelor of Science nursing program. An interactive computer simulation was developed as a potential alternative method of teaching pain management to nursing students. Increases in educational gain as well as its potential to change practice were explored. Each participant was asked to complete a survey consisting of 10 standard 5-point Likert scale items and 5 open-ended questions. The survey was used to evaluate the students' perception of the simulation, specifically related to educational benefit, preference compared with traditional teaching methods, and perceived potential to change nursing practice. Data provided descriptive statistics for initial evaluation of the computer simulation. The responses on the survey suggest nursing students perceive the computer simulation to be entertaining, fun, educational, occasionally preferred over regular lecture, and with potential to change practice. Preliminary data support the use of computer simulation in educating nursing students about pain management. Copyright © 2017 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

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

NONE

This document comprises Pacific Northwest National Laboratory`s report for Fiscal Year 1996 on research and development programs. The document contains 161 project summaries in 16 areas of research and development. The 16 areas of research and development reported on are: atmospheric sciences, biotechnology, chemical instrumentation and analysis, computer and information science, ecological science, electronics and sensors, health protection and dosimetry, hydrological and geologic sciences, marine sciences, materials science and engineering, molecular science, process science and engineering, risk and safety analysis, socio-technical systems analysis, statistics and applied mathematics, and thermal and energy systems. In addition, this report provides an overview ofmore » the research and development program, program management, program funding, and Fiscal Year 1997 projects.« less

Kepler Science Operations Center Architecture

NASA Technical Reports Server (NTRS)

Middour, Christopher; Klaus, Todd; Jenkins, Jon; Pletcher, David; Cote, Miles; Chandrasekaran, Hema; Wohler, Bill; Girouard, Forrest; Gunter, Jay P.; Uddin, Kamal;

A Requirements Analysis Model for Selection of Personal Computer (PC) software in Air Force Organizations

DTIC Science & Technology

1988-09-01

Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Systems Management Dexter R... management system software Diag/Prob Diagnosis and problem solving or problem finding GR Graphics software Int/Transp Interoperability and...language software Plan/D.S. Planning and decision support or decision making PM Program management software SC Systems for Command, Control, Communications

A survey of university students' perceptions of learning management systems in a low-resource setting using a technology acceptance model.

PubMed

Chipps, Jennifer; Kerr, Jane; Brysiewicz, Petra; Walters, Fiona

2015-02-01

Learning management systems have been widely advocated for the support of distance learning. In low-resource settings, the uptake of these systems by students has been mixed. This study aimed to identify, through the use of the Technology Acceptance Model, the individual, organizational, and technological factors that could be influencing the use of learning management systems. A simple quantitative descriptive survey was conducted of nursing and health science students at a university in South Africa as part of their first exposure to a learning management system. A total of 274 respondents (56.7%) completed the survey questionnaire, made up of 213 nursing respondents (87.7%) and 61 health sciences respondents (25%). Overall, the respondents found the learning management system easy to use and useful for learning. There were significant differences between the two groups of respondents, with the respondents from health sciences being both younger and more computer literate. The nursing respondents, who received more support and orientations, reported finding the learning management system more useful. Recommendations are made for training and support to ensure uptake.

The Kepler Science Operations Center Pipeline Framework Extensions

NASA Technical Reports Server (NTRS)

Klaus, Todd C.; Cote, Miles T.; McCauliff, Sean; Girouard, Forrest R.; Wohler, Bill; Allen, Christopher; Chandrasekaran, Hema; Bryson, Stephen T.; Middour, Christopher; Caldwell, Douglas A.;

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

NASA Astrophysics Data System (ADS)

Klimentov, A.; De, K.; Jha, S.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Wells, J.; Wenaus, T.

2016-10-01

The.LHC, operating at CERN, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than grid can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility. Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full pro duction for the ATLAS since September 2015. We will present our current accomplishments with running PanDA at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Common Database Interface for Heterogeneous Software Engineering Tools.

DTIC Science & Technology

1987-12-01

SUB-GROUP Database Management Systems ;Programming(Comuters); 1e 05 Computer Files;Information Transfer;Interfaces; 19. ABSTRACT (Continue on reverse...Air Force Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Information Systems ...Literature ..... 8 System 690 Configuration ......... 8 Database Functionis ............ 14 Software Engineering Environments ... 14 Data Manager

Mexico Fires

Atmospheric Science Data Center

2013-04-18

... on the right. This quantity is retrieved using an automated computer algorithm that takes advantage of MISR's multi-angle capability. Areas ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

Hurricane Juliette

Atmospheric Science Data Center

2013-04-19

... right is the cloud-top height field derived using automated computer processing of the data from multiple MISR cameras. Relative height ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

78 FR 36754 - Agency Information Collection Activities; Submission to the Office of Management and Budget for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-19

...-year-olds which focuses on assessing students science, mathematics, and reading literacy. PISA was... test will also include computer- based assessments in reading, mathematics, and collaborative problem...

Jackson State University's Center for Spatial Data Research and Applications: New facilities and new paradigms

NASA Technical Reports Server (NTRS)

Davis, Bruce E.; Elliot, Gregory

1989-01-01

Jackson State University recently established the Center for Spatial Data Research and Applications, a Geographical Information System (GIS) and remote sensing laboratory. Taking advantage of new technologies and new directions in the spatial (geographic) sciences, JSU is building a Center of Excellence in Spatial Data Management. New opportunities for research, applications, and employment are emerging. GIS requires fundamental shifts and new demands in traditional computer science and geographic training. The Center is not merely another computer lab but is one setting the pace in a new applied frontier. GIS and its associated technologies are discussed. The Center's facilities are described. An ARC/INFO GIS runs on a Vax mainframe, with numerous workstations. Image processing packages include ELAS, LIPS, VICAR, and ERDAS. A host of hardware and software peripheral are used in support. Numerous projects are underway, such as the construction of a Gulf of Mexico environmental data base, development of AI in image processing, a land use dynamics study of metropolitan Jackson, and others. A new academic interdisciplinary program in Spatial Data Management is under development, combining courses in Geography and Computer Science. The broad range of JSU's GIS and remote sensing activities is addressed. The impacts on changing paradigms in the university and in the professional world conclude the discussion.

NASA Exhibits

NASA Technical Reports Server (NTRS)

Deardorff, Glenn; Djomehri, M. Jahed; Freeman, Ken; Gambrel, Dave; Green, Bryan; Henze, Chris; Hinke, Thomas; Hood, Robert; Kiris, Cetin; Moran, Patrick;

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.

The Fabric for Frontier Experiments Project at Fermilab

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

Kirby, Michael

2014-01-01

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere, 2) an extensive data management system for managing local and remote caches, cataloging, querying,more » moving, and tracking the use of data, 3) custom and generic database applications for calibrations, beam information, and other purposes, 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.« less

An Overview of High Performance Computing and Challenges for the Future

ScienceCinema

Google Tech Talks

2017-12-09

In this talk we examine how high performance computing has changed over the last 10-year and look toward the future in terms of trends. These changes have had and will continue to have a major impact on our software. A new generation of software libraries and lgorithms are needed for the effective and reliable use of (wide area) dynamic, distributed and parallel environments. Some of the software and algorithm challenges have already been encountered, such as management of communication and memory hierarchies through a combination of compile--time and run--time techniques, but the increased scale of computation, depth of memory hierarchies, range of latencies, and increased run--time environment variability will make these problems much harder. We will focus on the redesign of software to fit multicore architectures. Speaker: Jack Dongarra University of Tennessee Oak Ridge National Laboratory University of Manchester Jack Dongarra received a Bachelor of Science in Mathematics from Chicago State University in 1972 and a Master of Science in Computer Science from the Illinois Institute of Technology in 1973. He received his Ph.D. in Applied Mathematics from the University of New Mexico in 1980. He worked at the Argonne National Laboratory until 1989, becoming a senior scientist. He now holds an appointment as University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee, has the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), Turing Fellow in the Computer Science and Mathematics Schools at the University of Manchester, and an Adjunct Professor in the Computer Science Department at Rice University. He specializes in numerical algorithms in linear algebra, parallel computing, the use of advanced-computer architectures, programming methodology, and tools for parallel computers. His research includes the development, testing and documentation of high quality mathematical software. He has contributed to the design and implementation of the following open source software packages and systems: EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. He has published approximately 200 articles, papers, reports and technical memoranda and he is coauthor of several books. He was awarded the IEEE Sid Fernbach Award in 2004 for his contributions in the application of high performance computers using innovative approaches. He is a Fellow of the AAAS, ACM, and the IEEE and a member of the National Academy of Engineering.

An Overview of High Performance Computing and Challenges for the Future

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

Google Tech Talks

In this talk we examine how high performance computing has changed over the last 10-year and look toward the future in terms of trends. These changes have had and will continue to have a major impact on our software. A new generation of software libraries and lgorithms are needed for the effective and reliable use of (wide area) dynamic, distributed and parallel environments. Some of the software and algorithm challenges have already been encountered, such as management of communication and memory hierarchies through a combination of compile--time and run--time techniques, but the increased scale of computation, depth of memory hierarchies,more » range of latencies, and increased run--time environment variability will make these problems much harder. We will focus on the redesign of software to fit multicore architectures. Speaker: Jack Dongarra University of Tennessee Oak Ridge National Laboratory University of Manchester Jack Dongarra received a Bachelor of Science in Mathematics from Chicago State University in 1972 and a Master of Science in Computer Science from the Illinois Institute of Technology in 1973. He received his Ph.D. in Applied Mathematics from the University of New Mexico in 1980. He worked at the Argonne National Laboratory until 1989, becoming a senior scientist. He now holds an appointment as University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee, has the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), Turing Fellow in the Computer Science and Mathematics Schools at the University of Manchester, and an Adjunct Professor in the Computer Science Department at Rice University. He specializes in numerical algorithms in linear algebra, parallel computing, the use of advanced-computer architectures, programming methodology, and tools for parallel computers. His research includes the development, testing and documentation of high quality mathematical software. He has contributed to the design and implementation of the following open source software packages and systems: EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. He has published approximately 200 articles, papers, reports and technical memoranda and he is coauthor of several books. He was awarded the IEEE Sid Fernbach Award in 2004 for his contributions in the application of high performance computers using innovative approaches. He is a Fellow of the AAAS, ACM, and the IEEE and a member of the National Academy of Engineering.« less

Johnson Space Center Research and Technology 1997 Annual Report

NASA Technical Reports Server (NTRS)

1998-01-01

This report highlights key projects and technologies at Johnson Space Center for 1997. The report focuses on the commercial potential of the projects and technologies and is arranged by CorpTech Major Products Groups. Emerging technologies in these major disciplines we summarized: solar system sciences, life sciences, technology transfer, computer sciences, space technology, and human support technology. Them NASA advances have a range of potential commercial applications, from a school internet manager for networks to a liquid metal mirror for optical measurements.

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

DOE PAGES

Klimentov, A.; Buncic, P.; De, K.; ...

2015-05-22

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

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

Klimentov, A.; Buncic, P.; De, K.

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less

Distributed information system (water fact sheet)

USGS Publications Warehouse

Harbaugh, A.W.

1986-01-01

During 1982-85, the Water Resources Division (WRD) of the U.S. Geological Survey (USGS) installed over 70 large minicomputers in offices across the country to support its mission in the science of hydrology. These computers are connected by a communications network that allows information to be shared among computers in each office. The computers and network together are known as the Distributed Information System (DIS). The computers are accessed through the use of more than 1500 terminals and minicomputers. The WRD has three fundamentally different needs for computing: data management; hydrologic analysis; and administration. Data management accounts for 50% of the computational workload of WRD because hydrologic data are collected in all 50 states, Puerto Rico, and the Pacific trust territories. Hydrologic analysis consists of 40% of the computational workload of WRD. Cost accounting, payroll, personnel records, and planning for WRD programs occupies an estimated 10% of the computer workload. The DIS communications network is shown on a map. (Lantz-PTT)

The Management of Information and Knowledge; a Compilation of Papers Prepared for the Eleventh Meeting of the Panel on Science and Technology.

ERIC Educational Resources Information Center

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

A special document, published separately from the complete proceedings of the eleventh meeting of the Panel on Science and Technology, is justified because the papers presented discuss the impact of the rapid development of the computer and the revolution in communication technology upon our society. This impact is critically examined by 10…

Earth Science Data Grid System

NASA Astrophysics Data System (ADS)

Chi, Y.; Yang, R.; Kafatos, M.

2004-12-01

The Earth Science Data Grid System (ESDGS) is a software in support of earth science data storage and access. It is built upon the Storage Resource Broker (SRB) data grid technology. We have developed a complete data grid system consistent of SRB server providing users uniform access to diverse storage resources in a heterogeneous computing environment and metadata catalog server (MCAT) managing the metadata associated with data set, users, and resources. We are also developing additional services of 1) metadata management, 2) geospatial, temporal, and content-based indexing, and 3) near/on site data processing, in response to the unique needs of Earth science applications. In this paper, we will describe the software architecture and components of the system, and use a practical example in support of storage and access of rainfall data from the Tropical Rainfall Measuring Mission (TRMM) to illustrate its functionality and features.

28 CFR 58.25 - Qualifications for approval as providers of a personal financial management instructional course.

Code of Federal Regulations, 2011 CFR

2011-07-01

... organization; (4) Certification by the American Association of Family and Consumer Sciences; (5) Registered as... computer capabilities to issue certificates of completion of an instructional course in conformance with...

28 CFR 58.25 - Qualifications for approval as providers of a personal financial management instructional course.

Code of Federal Regulations, 2012 CFR

2012-07-01

... organization; (4) Certification by the American Association of Family and Consumer Sciences; (5) Registered as... computer capabilities to issue certificates of completion of an instructional course in conformance with...

EPA'S TOXICOGENOMICS PARTNERSHIPS ACROSS GOVERNMENT, ACADEMIA AND INDUSTRY

EPA Science Inventory

Genomics, proteomics and metabonomics technologies are transforming the science of toxicology, and concurrent advances in computing and informatics are providing management and analysis solutions for this onslaught of toxicogenomic data. EPA has been actively developing an intra...

Research and technology, 1984 report

NASA Technical Reports Server (NTRS)

1984-01-01

Research and technology projects in the following areas are described: cryogenic engineering, hypergolic engineering, hazardous warning instrumentation, structures and mechanics, sensors and controls, computer sciences, communications, material analysis, biomedicine, meteorology, engineering management, logistics, training and maintenance aids, and technology applications.

Approaches for Measuring the Management Effectiveness of Software Projects

DTIC Science & Technology

2008-04-01

John S. Osmundson Research Assoc. Professor of...and Department of Computer Science Dean of Research ...caused otherwise good projects grind to a halt.” [RO]. Various other studies, researchers and practitioners report similar issues regarding the

NSI security task: Overview

NASA Technical Reports Server (NTRS)

Tencati, Ron

1991-01-01

An overview is presented of the NASA Science Internet (NSI) security task. The task includes the following: policies and security documentation; risk analysis and management; computer emergency response team; incident handling; toolkit development; user consulting; and working groups, conferences, and committees.

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

Kervin, Karina E.; Cook, Robert B.; Michener, William K.

Conventional wisdom makes the suggestion that there are benefits to the creation of shared repositories of scientific data. Funding agencies require that the data from sponsored projects be shared publicly, but individual researchers often see little personal benefit to offset the work of creating easily sharable data. These conflicting forces have led to the emergence of a new role to support researchers: data managers. This paper identifies key differences between the socio-technical context of data managers and other "human infrastructure" roles articulated previously in Computer Supported Cooperative Work (CSCW) literature and summarizes the challenges that data managers face when acceptingmore » data for archival and reuse. Finally, while data managers' work is critical for advancing science and science policy, their work is often invisible and under-appreciated since it takes place behind the scenes.« less

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.

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.

Improving Royal Australian Air Force Strategic Airlift Planning by Application of a Computer Based Management Information System

DTIC Science & Technology

1991-12-01

AUSTRALIAN AIR FORCE STRATEGIC AIRLIFT PLANNING bY APPLICATION OF A COMPTER BASED MANAGEMENT INFO4ATION SYSTEM THESIS Presented to the Faculty of the...Master of Science in Information Management Neil A. Cooper, BBus Squadron Leader, RAAF December 1991 Approved for public release; distribution unlimited...grateful to the time and honest views given to me by the ADANS manager , Lieutenant Colonel Charlie Davis. For my Canadian research, I relied on the

Discussion on the management system technology implementation of multimedia classrooms in the digital campus

NASA Astrophysics Data System (ADS)

Wang, Bo

2018-04-01

Based on the digitized information and network, digital campus is an integration of teaching, management, science and research, life service and technology service, and it is one of the current mainstream construction form of campus function. This paper regarded the "mobile computing" core digital environment construction development as the background, explored the multiple management system technology content design and achievement of multimedia classrooms in digital campus and scientifically proved the technology superiority of management system.

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

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

Herner, K.; Alba Hernandex, A. F.; Bhat, S.

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasinglymore » complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.« less

Advances in Grid Computing for the Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Herner, K.; Alba Hernandez, A. F.; Bhat, S.; Box, D.; Boyd, J.; Di Benedetto, V.; Ding, P.; Dykstra, D.; Fattoruso, M.; Garzoglio, G.; Kirby, M.; Kreymer, A.; Levshina, T.; Mazzacane, A.; Mengel, M.; Mhashilkar, P.; Podstavkov, V.; Retzke, K.; Sharma, N.; Teheran, J.

2017-10-01

The Fabric for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientific Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of differing size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certificate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have significantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the efforts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production workflows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular workflows, and support troubleshooting and triage in case of problems. Recently a new certificate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specific third-party Certificate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Executive Guide to Software Maintenance. Reports on Computer Science and Technology.

ERIC Educational Resources Information Center

Osborne, Wilma M.

This guide is designed for federal executives and managers who have a responsibility for the planning and management of software projects and for federal staff members who are affected by, or involved in, making software changes, and who need to be aware of steps that can reduce both the difficulty and cost of software maintenance. Organized in a…

Understanding and Managing Causality of Change in Socio-Technical Systems II

DTIC Science & Technology

2011-01-25

SUBJECT TERMS Cognition , Human Effectiveness, Information Science 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18...at large taking into account the cognitive interaction between humans and technology. 8 Hussein Abbass Professor Abbass leads the...Network Centric Operations Future Air Traffic Management Systems Cognitive Engineering including Human-Computer Integration In all of the

TCP Resynchronization

DTIC Science & Technology

1976-01-11

Centinela and Teale Streets Culver City, CA 90230 IBM Dr. Patrick Mantey, Manager L’cer Oriented Systems International Business Machines Corp. K54...282, Monterey and Cottle Roads San Jose, CA 95193 Dr. Leonard Y. Liu, Manager Computer Science International Business Machines Corp. K51-282...Monterey and Cottle Roads San Jose, CA 95193 Mr. Harry Reinstein International Business Machines Corp. 1501 California Avenue Palo Alto, Ca 94303

A new approach to the design of information systems for foodservice management in health care facilities.

PubMed

Matthews, M E; Norback, J P

1984-06-01

An organizational framework for integrating foodservice data into an information system for management decision making is presented. The framework involves the application to foodservice of principles developed by the disciplines of managerial economics and accounting, mathematics, computer science, and information systems. The first step is to conceptualize a foodservice system from an input-output perspective, in which inputs are units of resources available to managers and outputs are servings of menu items. Next, methods of full cost accounting, from the management accounting literature, are suggested as a mechanism for developing and assigning costs of using resources within a foodservice operation. Then matrix multiplication is used to illustrate types of information that matrix data structures could make available for management planning and control when combined with a conversational mode of computer programming.

Institutional Computing Executive Group Review of Multi-programmatic & Institutional Computing, Fiscal Year 2005 and 2006

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

Langer, S; Rotman, D; Schwegler, E

The Institutional Computing Executive Group (ICEG) review of FY05-06 Multiprogrammatic and Institutional Computing (M and IC) activities is presented in the attached report. In summary, we find that the M and IC staff does an outstanding job of acquiring and supporting a wide range of institutional computing resources to meet the programmatic and scientific goals of LLNL. The responsiveness and high quality of support given to users and the programs investing in M and IC reflects the dedication and skill of the M and IC staff. M and IC has successfully managed serial capacity, parallel capacity, and capability computing resources.more » Serial capacity computing supports a wide range of scientific projects which require access to a few high performance processors within a shared memory computer. Parallel capacity computing supports scientific projects that require a moderate number of processors (up to roughly 1000) on a parallel computer. Capability computing supports parallel jobs that push the limits of simulation science. M and IC has worked closely with Stockpile Stewardship, and together they have made LLNL a premier institution for computational and simulation science. Such a standing is vital to the continued success of laboratory science programs and to the recruitment and retention of top scientists. This report provides recommendations to build on M and IC's accomplishments and improve simulation capabilities at LLNL. We recommend that institution fully fund (1) operation of the atlas cluster purchased in FY06 to support a few large projects; (2) operation of the thunder and zeus clusters to enable 'mid-range' parallel capacity simulations during normal operation and a limited number of large simulations during dedicated application time; (3) operation of the new yana cluster to support a wide range of serial capacity simulations; (4) improvements to the reliability and performance of the Lustre parallel file system; (5) support for the new GDO petabyte-class storage facility on the green network for use in data intensive external collaborations; and (6) continued support for visualization and other methods for analyzing large simulations. We also recommend that M and IC begin planning in FY07 for the next upgrade of its parallel clusters. LLNL investments in M and IC have resulted in a world-class simulation capability leading to innovative science. We thank the LLNL management for its continued support and thank the M and IC staff for its vision and dedicated efforts to make it all happen.« less

Interleaving Semantic Web Reasoning and Service Discovery to Enforce Context-Sensitive Security and Privacy Policies

DTIC Science & Technology

2005-07-01

policies in pervasive computing environments. In this context, the owner of information sources (e.g. user, sensor, application, or organization...work in decentralized trust management and semantic web technologies . Section 3 introduces an Information Disclosure Agent architecture for...Norman Sadeh July 2005 CMU-ISRI-05-113 School of Computer Science, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA, 15213

Next Generation Space Telescope Integrated Science Module Data System

NASA Technical Reports Server (NTRS)

Schnurr, Richard G.; Greenhouse, Matthew A.; Jurotich, Matthew M.; Whitley, Raymond; Kalinowski, Keith J.; Love, Bruce W.; Travis, Jeffrey W.; Long, Knox S.

1999-01-01

The Data system for the Next Generation Space Telescope (NGST) Integrated Science Module (ISIM) is the primary data interface between the spacecraft, telescope, and science instrument systems. This poster includes block diagrams of the ISIM data system and its components derived during the pre-phase A Yardstick feasibility study. The poster details the hardware and software components used to acquire and process science data for the Yardstick instrument compliment, and depicts the baseline external interfaces to science instruments and other systems. This baseline data system is a fully redundant, high performance computing system. Each redundant computer contains three 150 MHz power PC processors. All processors execute a commercially available real time multi-tasking operating system supporting, preemptive multi-tasking, file management and network interfaces. These six processors in the system are networked together. The spacecraft interface baseline is an extension of the network, which links the six processors. The final selection for Processor busses, processor chips, network interfaces, and high-speed data interfaces will be made during mid 2002.

High-performance scientific computing in the cloud

NASA Astrophysics Data System (ADS)

Jorissen, Kevin; Vila, Fernando; Rehr, John

2011-03-01

Cloud computing has the potential to open up high-performance computational science to a much broader class of researchers, owing to its ability to provide on-demand, virtualized computational resources. However, before such approaches can become commonplace, user-friendly tools must be developed that hide the unfamiliar cloud environment and streamline the management of cloud resources for many scientific applications. We have recently shown that high-performance cloud computing is feasible for parallelized x-ray spectroscopy calculations. We now present benchmark results for a wider selection of scientific applications focusing on electronic structure and spectroscopic simulation software in condensed matter physics. These applications are driven by an improved portable interface that can manage virtual clusters and run various applications in the cloud. We also describe a next generation of cluster tools, aimed at improved performance and a more robust cluster deployment. Supported by NSF grant OCI-1048052.

Alaska

Atmospheric Science Data Center

2014-05-15

... help to darken the room lights when viewing the image on a computer screen. The Yukon River is seen wending its way from upper left to ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

Interdisciplinary Introductory Course in Bioinformatics

ERIC Educational Resources Information Center

Kortsarts, Yana; Morris, Robert W.; Utell, Janine M.

2010-01-01

Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…

e-Science and data management resources on the Web.

PubMed

Gore, Sally A

2011-01-01

The way research is conducted has changed over time, from simple experiments to computer modeling and simulation, from individuals working in isolated laboratories to global networks of researchers collaborating on a single topic. Often, this new paradigm results in the generation of staggering amounts of data. The intensive use of data and the existence of networks of researchers characterize e-Science. The role of libraries and librarians in e-Science has been a topic of interest for some time now. This column looks at tools, resources, and projects that demonstrate successful collaborations between libraries and researchers in e-Science.

The Naval Postgraduate School SECURE ARCHIVAL STORAGE SYSTEM. Part II. Segment and Process Management Implementation.

DTIC Science & Technology

1981-03-01

Research Instructor of Computer Scienr-. Reviewed by: Released by: WILLIAM M. TOLLES Department puter Science Dean of Research 4c t SECURITY...Lyle A. Cox, Roger R. Schell, and Sonja L. Perdue 9. PERFORMING ORGANIZATION NAME ANO ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK AREA A WORK UNIT... Computer Networks, Operating Systems, Computer Security 20. AftUrCT (Cnthm, w v re eae old* It n..*p and idm 0 F W blk ..m.m.o’) ",A_;he security

Computer and Internet use by home care and hospice agencies.

PubMed

Long, C O; Greenberg, E A; Ismeurt, R L; Smith, G

2000-01-01

Nurses in home healthcare and hospice are embracing the advances in computer science and technology to provide an edge in administration and clinical practice. Of concern to nurse managers is the extent to which personal computers and the Internet have been used in home healthcare and hospice, and what information, opportunities, and needs related to education are on the horizon. This article discusses the results of a national survey conducted exclusively on the World Wide Web to answer these questions.

Applications of hybrid and digital computation methods in aerospace-related sciences and engineering. [problem solving methods at the University of Houston

NASA Technical Reports Server (NTRS)

Huang, C. J.; Motard, R. L.

1978-01-01

The computing equipment in the engineering systems simulation laboratory of the Houston University Cullen College of Engineering is described and its advantages are summarized. The application of computer techniques in aerospace-related research psychology and in chemical, civil, electrical, industrial, and mechanical engineering is described in abstracts of 84 individual projects and in reprints of published reports. Research supports programs in acoustics, energy technology, systems engineering, and environment management as well as aerospace engineering.

Telescience workstation

NASA Technical Reports Server (NTRS)

Brown, Robert L.; Doyle, Dee; Haines, Richard F.; Slocum, Michael

1989-01-01

As part of the Telescience Testbed Pilot Program, the Universities Space Research Association/ Research Institute for Advanced Computer Science (USRA/RIACS) proposed to support remote communication by providing a network of human/machine interfaces, computer resources, and experimental equipment which allows: remote science, collaboration, technical exchange, and multimedia communication. The telescience workstation is intended to provide a local computing environment for telescience. The purpose of the program are as follows: (1) to provide a suitable environment to integrate existing and new software for a telescience workstation; (2) to provide a suitable environment to develop new software in support of telescience activities; (3) to provide an interoperable environment so that a wide variety of workstations may be used in the telescience program; (4) to provide a supportive infrastructure and a common software base; and (5) to advance, apply, and evaluate the telescience technolgy base. A prototype telescience computing environment designed to bring practicing scientists in domains other than their computer science into a modern style of doing their computing was created and deployed. This environment, the Telescience Windowing Environment, Phase 1 (TeleWEn-1), met some, but not all of the goals stated above. The TeleWEn-1 provided a window-based workstation environment and a set of tools for text editing, document preparation, electronic mail, multimedia mail, raster manipulation, and system management.

Cloudbursting - Solving the 3-body problem

NASA Astrophysics Data System (ADS)

Chang, G.; Heistand, S.; Vakhnin, A.; Huang, T.; Zimdars, P.; Hua, H.; Hood, R.; Koenig, J.; Mehrotra, P.; Little, M. M.; Law, E.

2014-12-01

Many science projects in the future will be accomplished through collaboration among 2 or more NASA centers along with, potentially, external scientists. Science teams will be composed of more geographically dispersed individuals and groups. However, the current computing environment does not make this easy and seamless. By being able to share computing resources among members of a multi-center team working on a science/ engineering project, limited pre-competition funds could be more efficiently applied and technical work could be conducted more effectively with less time spent moving data or waiting for computing resources to free up. Based on the work from an NASA CIO IT Labs task, this presentation will highlight our prototype work in identifying the feasibility and identify the obstacles, both technical and management, to perform "Cloudbursting" among private clouds located at three different centers. We will demonstrate the use of private cloud computing infrastructure at the Jet Propulsion Laboratory, Langley Research Center, and Ames Research Center to provide elastic computation to each other to perform parallel Earth Science data imaging. We leverage elastic load balancing and auto-scaling features at each data center so that each location can independently define how many resources to allocate to a particular job that was "bursted" from another data center and demonstrate that compute capacity scales up and down with the job. We will also discuss future work in the area, which could include the use of cloud infrastructure from different cloud framework providers as well as other cloud service providers.

A PICKSC Science Gateway for enabling the common plasma physicist to run kinetic software

NASA Astrophysics Data System (ADS)

Hu, Q.; Winjum, B. J.; Zonca, A.; Youn, C.; Tsung, F. S.; Mori, W. B.

2017-10-01

Computer simulations offer tremendous opportunities for studying plasmas, ranging from simulations for students that illuminate fundamental educational concepts to research-level simulations that advance scientific knowledge. Nevertheless, there is a significant hurdle to using simulation tools. Users must navigate codes and software libraries, determine how to wrangle output into meaningful plots, and oftentimes confront a significant cyberinfrastructure with powerful computational resources. Science gateways offer a Web-based environment to run simulations without needing to learn or manage the underlying software and computing cyberinfrastructure. We discuss our progress on creating a Science Gateway for the Particle-in-Cell and Kinetic Simulation Software Center that enables users to easily run and analyze kinetic simulations with our software. We envision that this technology could benefit a wide range of plasma physicists, both in the use of our simulation tools as well as in its adaptation for running other plasma simulation software. Supported by NSF under Grant ACI-1339893 and by the UCLA Institute for Digital Research and Education.

Trends in computer applications in science assessment

NASA Astrophysics Data System (ADS)

Kumar, David D.; Helgeson, Stanley L.

1995-03-01

Seven computer applications to science assessment are reviewed. Conventional test administration includes record keeping, grading, and managing test banks. Multiple-choice testing involves forced selection of an answer from a menu, whereas constructed-response testing involves options for students to present their answers within a set standard deviation. Adaptive testing attempts to individualize the test to minimize the number of items and time needed to assess a student's knowledge. Figurai response testing assesses science proficiency in pictorial or graphic mode and requires the student to construct a mental image rather than selecting a response from a multiple choice menu. Simulations have been found useful for performance assessment on a large-scale basis in part because they make it possible to independently specify different aspects of a real experiment. An emerging approach to performance assessment is solution pathway analysis, which permits the analysis of the steps a student takes in solving a problem. Virtually all computer-based testing systems improve the quality and efficiency of record keeping and data analysis.

Infrastructure for Training and Partnershipes: California Water and Coastal Ocean Resources

NASA Technical Reports Server (NTRS)

Siegel, David A.; Dozier, Jeffrey; Gautier, Catherine; Davis, Frank; Dickey, Tommy; Dunne, Thomas; Frew, James; Keller, Arturo; MacIntyre, Sally; Melack, John

2000-01-01

The purpose of this project was to advance the existing ICESS/Bren School computing infrastructure to allow scientists, students, and research trainees the opportunity to interact with environmental data and simulations in near-real time. Improvements made with the funding from this project have helped to strengthen the research efforts within both units, fostered graduate research training, and helped fortify partnerships with government and industry. With this funding, we were able to expand our computational environment in which computer resources, software, and data sets are shared by ICESS/Bren School faculty researchers in all areas of Earth system science. All of the graduate and undergraduate students associated with the Donald Bren School of Environmental Science and Management and the Institute for Computational Earth System Science have benefited from the infrastructure upgrades accomplished by this project. Additionally, the upgrades fostered a significant number of research projects (attached is a list of the projects that benefited from the upgrades). As originally proposed, funding for this project provided the following infrastructure upgrades: 1) a modem file management system capable of interoperating UNIX and NT file systems that can scale to 6.7 TB, 2) a Qualstar 40-slot tape library with two AIT tape drives and Legato Networker backup/archive software, 3) previously unavailable import/export capability for data sets on Zip, Jaz, DAT, 8mm, CD, and DLT media in addition to a 622Mb/s Internet 2 connection, 4) network switches capable of 100 Mbps to 128 desktop workstations, 5) Portable Batch System (PBS) computational task scheduler, and vi) two Compaq/Digital Alpha XP1000 compute servers each with 1.5 GB of RAM along with an SGI Origin 2000 (purchased partially using funds from this project along with funding from various other sources) to be used for very large computations, as required for simulation of mesoscale meteorology or climate.

Journal of Undergraduate Research, Volume IX, 2009

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

Stiner, K. S.; Graham, S.; Khan, M.

Each year more than 600 undergraduate students are awarded paid internships at the Department of Energy’s (DOE) National Laboratories. Th ese interns are paired with research scientists who serve as mentors in authentic research projects. All participants write a research abstract and present at a poster session and/or complete a fulllength research paper. Abstracts and selected papers from our 2007–2008 interns that represent the breadth and depth of undergraduate research performed each year at our National Laboratories are published here in the Journal of Undergraduate Research. The fields in which these students worked included: Biology; Chemistry; Computer Science; Engineering; Environmentalmore » Science; General Science; Materials Science; Medical and Health Sciences; Nuclear Science; Physics; Science Policy; and Waste Management.« less

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

Bland, Arthur S Buddy; Hack, James J; Baker, Ann E

Oak Ridge National Laboratory's (ORNL's) Cray XT5 supercomputer, Jaguar, kicked off the era of petascale scientific computing in 2008 with applications that sustained more than a thousand trillion floating point calculations per second - or 1 petaflop. Jaguar continues to grow even more powerful as it helps researchers broaden the boundaries of knowledge in virtually every domain of computational science, including weather and climate, nuclear energy, geosciences, combustion, bioenergy, fusion, and materials science. Their insights promise to broaden our knowledge in areas that are vitally important to the Department of Energy (DOE) and the nation as a whole, particularly energymore » assurance and climate change. The science of the 21st century, however, will demand further revolutions in computing, supercomputers capable of a million trillion calculations a second - 1 exaflop - and beyond. These systems will allow investigators to continue attacking global challenges through modeling and simulation and to unravel longstanding scientific questions. Creating such systems will also require new approaches to daunting challenges. High-performance systems of the future will need to be codesigned for scientific and engineering applications with best-in-class communications networks and data-management infrastructures and teams of skilled researchers able to take full advantage of these new resources. The Oak Ridge Leadership Computing Facility (OLCF) provides the nation's most powerful open resource for capability computing, with a sustainable path that will maintain and extend national leadership for DOE's Office of Science (SC). The OLCF has engaged a world-class team to support petascale science and to take a dramatic step forward, fielding new capabilities for high-end science. This report highlights the successful delivery and operation of a petascale system and shows how the OLCF fosters application development teams, developing cutting-edge tools and resources for next-generation systems.« less

A Publications Sampler.

ERIC Educational Resources Information Center

Hess, Sheila

1984-01-01

Lists over 100 association publications on topics of: aeronautics and space, aging, arts and architecture, computers, consumer guides, education, educational directories, government and politics, handicapped, health and medicine, housing and land use, libraries, management, recreation and hobbies, science and technology, social issues. A list of…

78 FR 5179 - Granting of Request for Early Termination of the Waiting Period Under the Premerger Notification...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-24

... & Co. 20130257 G Equifax Inc.; Computer Sciences Corporation; Equifax Inc. 20130279 G Arsenal Capital.... 20130429 G Lagardere SCA; Excel Sports Management, LLC; Lagardere SCA. 12/19/2012 20130236 G Cisco Systems...

Large-Scale Data Collection Metadata Management at the National Computation Infrastructure

NASA Astrophysics Data System (ADS)

Wang, J.; Evans, B. J. K.; Bastrakova, I.; Ryder, G.; Martin, J.; Duursma, D.; Gohar, K.; Mackey, T.; Paget, M.; Siddeswara, G.

2014-12-01

Data Collection management has become an essential activity at the National Computation Infrastructure (NCI) in Australia. NCI's partners (CSIRO, Bureau of Meteorology, Australian National University, and Geoscience Australia), supported by the Australian Government and Research Data Storage Infrastructure (RDSI), have established a national data resource that is co-located with high-performance computing. This paper addresses the metadata management of these data assets over their lifetime. NCI manages 36 data collections (10+ PB) categorised as earth system sciences, climate and weather model data assets and products, earth and marine observations and products, geosciences, terrestrial ecosystem, water management and hydrology, astronomy, social science and biosciences. The data is largely sourced from NCI partners, the custodians of many of the national scientific records, and major research community organisations. The data is made available in a HPC and data-intensive environment - a ~56000 core supercomputer, virtual labs on a 3000 core cloud system, and data services. By assembling these large national assets, new opportunities have arisen to harmonise the data collections, making a powerful cross-disciplinary resource.To support the overall management, a Data Management Plan (DMP) has been developed to record the workflows, procedures, the key contacts and responsibilities. The DMP has fields that can be exported to the ISO19115 schema and to the collection level catalogue of GeoNetwork. The subset or file level metadata catalogues are linked with the collection level through parent-child relationship definition using UUID. A number of tools have been developed that support interactive metadata management, bulk loading of data, and support for computational workflows or data pipelines. NCI creates persistent identifiers for each of the assets. The data collection is tracked over its lifetime, and the recognition of the data providers, data owners, data generators and data aggregators are updated. A Digital Object Identifier is assigned using the Australian National Data Service (ANDS). Once the data has been quality assured, a DOI is minted and the metadata record updated. NCI's data citation policy establishes the relationship between research outcomes, data providers, and the data.

Introduction to the scientific application system of DAMPE (On behalf of DAMPE collaboration)

NASA Astrophysics Data System (ADS)

Zang, Jingjing

2016-07-01

The Dark Matter Particle Explorer (DAMPE) is a high energy particle physics experiment satellite, launched on 17 Dec 2015. The science data processing and payload operation maintenance for DAMPE will be provided by the DAMPE Scientific Application System (SAS) at the Purple Mountain Observatory (PMO) of Chinese Academy of Sciences. SAS is consisted of three subsystems - scientific operation subsystem, science data and user management subsystem and science data processing subsystem. In cooperation with the Ground Support System (Beijing), the scientific operation subsystem is responsible for proposing observation plans, monitoring the health of satellite, generating payload control commands and participating in all activities related to payload operation. Several databases developed by the science data and user management subsystem of DAMPE methodically manage all collected and reconstructed science data, down linked housekeeping data, payload configuration and calibration data. Under the leadership of DAMPE Scientific Committee, this subsystem is also responsible for publication of high level science data and supporting all science activities of the DAMPE collaboration. The science data processing subsystem of DAMPE has already developed a series of physics analysis software to reconstruct basic information about detected cosmic ray particle. This subsystem also maintains the high performance computing system of SAS to processing all down linked science data and automatically monitors the qualities of all produced data. In this talk, we will describe all functionalities of whole DAMPE SAS system and show you main performances of data processing ability.

Using Virtualization and Automatic Evaluation: Adapting Network Services Management Courses to the EHEA

ERIC Educational Resources Information Center

Ros, S.; Robles-Gomez, A.; Hernandez, R.; Caminero, A. C.; Pastor, R.

2012-01-01

This paper outlines the adaptation of a course on the management of network services in operating systems, called NetServicesOS, to the context of the new European Higher Education Area (EHEA). NetServicesOS is a mandatory course in one of the official graduate programs in the Faculty of Computer Science at the Universidad Nacional de Educacion a…

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.

TELNET under Single-Connection TCP Specification

DTIC Science & Technology

1976-02-02

Manager User Oriented Systems International Business Machines Corp. K54-282, Monterey and Cottle Roads San Jose, CA 95193 Dr. Leonard Y. Liu...Manager Computer Science International Business Machines Corp. K51-282, Monterey and Cottle Roads San Jose, CA 95193 Mr. Harry Reinstein... International Business Machines Corp. 1501 California Avenue Palo Alto, Ca 94303 Illinois, University of Mr. John D. Day University of Illinois Center for

ARPA Internetwork Protocols Project Status Report

DTIC Science & Technology

1975-11-15

and Teale Streets Culver City, CA 90230 IBM Dr. Patrick Mantey, Manager User Oriented Systems International Business Machines Corp. K54-282...Monterey and Cottle Roads San Jose, CA 95193 Dr. Leonard Y. Liu, Manager Computer Science International Business Machines Corp. K51-282. Monterey...and Cottle Roads San Jose, CA 95193 Mr. Harry Reinstein International Business Machines Corp. 1501 California Avenue Palo Alto, Ca 94303 Illinois

A decision-theoretic approach to the display of information for time-critical decisions: The Vista project

NASA Technical Reports Server (NTRS)

Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath; Barry, Matthew

1993-01-01

We describe a collaborative research and development effort between the Palo Alto Laboratory of the Rockwell Science Center, Rockwell Space Operations Company, and the Propulsion Systems Section of NASA JSC to design computational tools that can manage the complexity of information displayed to human operators in high-stakes, time-critical decision contexts. We shall review an application from NASA Mission Control and describe how we integrated a probabilistic diagnostic model and a time-dependent utility model, with techniques for managing the complexity of computer displays. Then, we shall describe the behavior of VPROP, a system constructed to demonstrate promising display-management techniques. Finally, we shall describe our current research directions on the Vista 2 follow-on project.

Personal Information Management for Nurses Returning to School.

PubMed

Bowman, Katherine

2015-12-01

Registered nurses with a diploma or an associate's degree are encouraged to return to school to earn a Bachelor of Science in Nursing degree. Until they return to school, many RNs have little need to regularly write, store, and retrieve work-related papers, but they are expected to complete the majority of assignments using a computer when in the student role. Personal information management (PIM) is a system of organizing and managing electronic information that will reduce computer clutter, while enhancing time use, task management, and productivity. This article introduces three PIM strategies for managing school work. Nesting is the creation of a system of folders to form a hierarchy for storing and retrieving electronic documents. Each folder, subfolder, and document must be given a meaningful unique name. Numbering is used to create different versions of the same paper, while preserving the original document. Copyright 2015, SLACK Incorporated.

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

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

De, K; Jha, S; Klimentov, A

2016-01-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less

Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

NASA Technical Reports Server (NTRS)

Pham, Long; Chen, Aijun; Kempler, Steven; Lynnes, Christopher; Theobald, Michael; Asghar, Esfandiari; Campino, Jane; Vollmer, Bruce

2011-01-01

Cloud Computing has been implemented in several commercial arenas. The NASA Nebula Cloud Computing platform is an Infrastructure as a Service (IaaS) built in 2008 at NASA Ames Research Center and 2010 at GSFC. Nebula is an open source Cloud platform intended to: a) Make NASA realize significant cost savings through efficient resource utilization, reduced energy consumption, and reduced labor costs. b) Provide an easier way for NASA scientists and researchers to efficiently explore and share large and complex data sets. c) Allow customers to provision, manage, and decommission computing capabilities on an as-needed bases

Salary-Trend Studies of Faculty of the Years 1988-89 and 1991-92 in the Following Academic Disciplines/Major Fields: Accounting; Agribusiness and Agriproduction; Anthropology; Area and Ethnic Studies; Business Administration and Management; Business and Management; Business Economics; Chemistry; Communication Technologies; Communications; Computer and Information Sciences; Dramatic Arts; Drawing; Education; and Engineering.

ERIC Educational Resources Information Center

Howe, Richard D.; And Others

This volume provides comparative data for faculty salaries in public and private colleges, based on an annual survey of over 600 colleges and universities. Data cover the following disciplines: Accounting, Agribusiness and Agriproduction, Anthropology, Area and Ethnic Studies, Business Administration and Management, Business and Management,…

Spiral and Project-Based Learning with Peer Assessment in a Computer Science Project Management Course

NASA Astrophysics Data System (ADS)

Jaime, Arturo; Blanco, José Miguel; Domínguez, César; Sánchez, Ana; Heras, Jónathan; Usandizaga, Imanol

2016-06-01

Different learning methods such as project-based learning, spiral learning and peer assessment have been implemented in science disciplines with different outcomes. This paper presents a proposal for a project management course in the context of a computer science degree. Our proposal combines three well-known methods: project-based learning, spiral learning and peer assessment. Namely, the course is articulated during a semester through the structured (progressive and incremental) development of a sequence of four projects, whose duration, scope and difficulty of management increase as the student gains theoretical and instrumental knowledge related to planning, monitoring and controlling projects. Moreover, the proposal is complemented using peer assessment. The proposal has already been implemented and validated for the last 3 years in two different universities. In the first year, project-based learning and spiral learning methods were combined. Such a combination was also employed in the other 2 years; but additionally, students had the opportunity to assess projects developed by university partners and by students of the other university. A total of 154 students have participated in the study. We obtain a gain in the quality of the subsequently projects derived from the spiral project-based learning. Moreover, this gain is significantly bigger when peer assessment is introduced. In addition, high-performance students take advantage of peer assessment from the first moment, whereas the improvement in poor-performance students is delayed.

Standards guide for space and earth sciences computer software

NASA Technical Reports Server (NTRS)

Mason, G.; Chapman, R.; Klinglesmith, D.; Linnekin, J.; Putney, W.; Shaffer, F.; Dapice, R.

1972-01-01

Guidelines for the preparation of systems analysis and programming work statements are presented. The data is geared toward the efficient administration of available monetary and equipment resources. Language standards and the application of good management techniques to software development are emphasized.

Advanced Training Techniques Using Computer Generated Imagery.

DTIC Science & Technology

1981-09-15

Annual Technical Report for Period- 16 May 1980 - 15 July 1981 LJ Prepared for AIR FORCE OFFICE OF SCIENTIFIC RESEARCH Director of Life Sciences Building...Simulation Management Branch, ATC, Randolph AFB, TX 78148, November 1977. Allbee, K. F., Semple C. A.; Aircrew Training Devices Life Cycle Cost and Worth...in Simulator Design and Application, Life Sciences, Inc., 227 Lood 820 NE, Hurst, Texas 76053, AFOSR-TR-77- 0965, 30 September 1976 McDonnell Aircraft

Users guide for information retrieval using APL

NASA Technical Reports Server (NTRS)

Shapiro, A.

1974-01-01

A Programming Language (APL) is a precise, concise, and powerful computer programming language. Several features make APL useful to managers and other potential computer users. APL is interactive; therefore, the user can communicate with his program or data base in near real-time. This, coupled with the fact that APL has excellent debugging features, reduces program checkout time to minutes or hours rather than days or months. Of particular importance is the fact that APL can be utilized as a management science tool using such techniques as operations research, statistical analysis, and forecasting. The gap between the scientist and the manager could be narrowed by showing how APL can be used to do what the scientists and the manager each need to do, retrieve information. Sometimes, the information needs to be retrieved rapidly. In this case APL is ideally suited for this challenge.

The 6th International Conference on Computer Science and Computational Mathematics (ICCSCM 2017)

NASA Astrophysics Data System (ADS)

2017-09-01

The ICCSCM 2017 (The 6th International Conference on Computer Science and Computational Mathematics) has aimed to provide a platform to discuss computer science and mathematics related issues including Algebraic Geometry, Algebraic Topology, Approximation Theory, Calculus of Variations, Category Theory; Homological Algebra, Coding Theory, Combinatorics, Control Theory, Cryptology, Geometry, Difference and Functional Equations, Discrete Mathematics, Dynamical Systems and Ergodic Theory, Field Theory and Polynomials, Fluid Mechanics and Solid Mechanics, Fourier Analysis, Functional Analysis, Functions of a Complex Variable, Fuzzy Mathematics, Game Theory, General Algebraic Systems, Graph Theory, Group Theory and Generalizations, Image Processing, Signal Processing and Tomography, Information Fusion, Integral Equations, Lattices, Algebraic Structures, Linear and Multilinear Algebra; Matrix Theory, Mathematical Biology and Other Natural Sciences, Mathematical Economics and Financial Mathematics, Mathematical Physics, Measure Theory and Integration, Neutrosophic Mathematics, Number Theory, Numerical Analysis, Operations Research, Optimization, Operator Theory, Ordinary and Partial Differential Equations, Potential Theory, Real Functions, Rings and Algebras, Statistical Mechanics, Structure Of Matter, Topological Groups, Wavelets and Wavelet Transforms, 3G/4G Network Evolutions, Ad-Hoc, Mobile, Wireless Networks and Mobile Computing, Agent Computing & Multi-Agents Systems, All topics related Image/Signal Processing, Any topics related Computer Networks, Any topics related ISO SC-27 and SC- 17 standards, Any topics related PKI(Public Key Intrastructures), Artifial Intelligences(A.I.) & Pattern/Image Recognitions, Authentication/Authorization Issues, Biometric authentication and algorithms, CDMA/GSM Communication Protocols, Combinatorics, Graph Theory, and Analysis of Algorithms, Cryptography and Foundation of Computer Security, Data Base(D.B.) Management & Information Retrievals, Data Mining, Web Image Mining, & Applications, Defining Spectrum Rights and Open Spectrum Solutions, E-Comerce, Ubiquitous, RFID, Applications, Fingerprint/Hand/Biometrics Recognitions and Technologies, Foundations of High-performance Computing, IC-card Security, OTP, and Key Management Issues, IDS/Firewall, Anti-Spam mail, Anti-virus issues, Mobile Computing for E-Commerce, Network Security Applications, Neural Networks and Biomedical Simulations, Quality of Services and Communication Protocols, Quantum Computing, Coding, and Error Controls, Satellite and Optical Communication Systems, Theory of Parallel Processing and Distributed Computing, Virtual Visions, 3-D Object Retrievals, & Virtual Simulations, Wireless Access Security, etc. The success of ICCSCM 2017 is reflected in the received papers from authors around the world from several countries which allows a highly multinational and multicultural idea and experience exchange. The accepted papers of ICCSCM 2017 are published in this Book. Please check http://www.iccscm.com for further news. A conference such as ICCSCM 2017 can only become successful using a team effort, so herewith we want to thank the International Technical Committee and the Reviewers for their efforts in the review process as well as their valuable advices. We are thankful to all those who contributed to the success of ICCSCM 2017. The Secretary

Data Base Management Systems Panel Workshop: Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

Data base management systems (DBMS) for space acquired and associated data are discussed. The full range of DBMS needs is covered including acquiring, managing, storing, archiving, accessing and dissemination of data for an application. Existing bottlenecks in DBMS operations, expected developments in the field of remote sensing, communications, and computer science are discussed, and an overview of existing conditions and expected problems is presented. The requirements for a proposed spatial information system and characteristics of a comprehensive browse facility for earth observations applications are included.

The Design and Implementation of a Relational to Network Query Translator for a Distributed Database Management System.

DTIC Science & Technology

1985-12-01

RELATIONAL TO NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM TH ESI S .L Kevin H. Mahoney -- Captain, USAF AFIT/GCS/ENG/85D-7...NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM - THESIS Presented to the Faculty of the School of Engineering of the Air Force...Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Systems - Kevin H. Mahoney

Life science research and drug discovery at the turn of the 21st century: the experience of SwissBioGrid.

PubMed

den Besten, Matthijs; Thomas, Arthur J; Schroeder, Ralph

2009-04-22

It is often said that the life sciences are transforming into an information science. As laboratory experiments are starting to yield ever increasing amounts of data and the capacity to deal with those data is catching up, an increasing share of scientific activity is seen to be taking place outside the laboratories, sifting through the data and modelling "in silico" the processes observed "in vitro." The transformation of the life sciences and similar developments in other disciplines have inspired a variety of initiatives around the world to create technical infrastructure to support the new scientific practices that are emerging. The e-Science programme in the United Kingdom and the NSF Office for Cyberinfrastructure are examples of these. In Switzerland there have been no such national initiatives. Yet, this has not prevented scientists from exploring the development of similar types of computing infrastructures. In 2004, a group of researchers in Switzerland established a project, SwissBioGrid, to explore whether Grid computing technologies could be successfully deployed within the life sciences. This paper presents their experiences as a case study of how the life sciences are currently operating as an information science and presents the lessons learned about how existing institutional and technical arrangements facilitate or impede this operation. SwissBioGrid gave rise to two pilot projects: one for proteomics data analysis and the other for high-throughput molecular docking ("virtual screening") to find new drugs for neglected diseases (specifically, for dengue fever). The proteomics project was an example of a data management problem, applying many different analysis algorithms to Terabyte-sized datasets from mass spectrometry, involving comparisons with many different reference databases; the virtual screening project was more a purely computational problem, modelling the interactions of millions of small molecules with a limited number of protein targets on the coat of the dengue virus. Both present interesting lessons about how scientific practices are changing when they tackle the problems of large-scale data analysis and data management by means of creating a novel technical infrastructure. In the experience of SwissBioGrid, data intensive discovery has a lot to gain from close collaboration with industry and harnessing distributed computing power. Yet the diversity in life science research implies only a limited role for generic infrastructure; and the transience of support means that researchers need to integrate their efforts with others if they want to sustain the benefits of their success, which are otherwise lost.

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.

Laboratory Directed Research and Development Annual Report for 2009

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

Hughes, Pamela J.

This report documents progress made on all LDRD-funded projects during fiscal year 2009. As a US Department of Energy (DOE) Office of Science (SC) national laboratory, Pacific Northwest National Laboratory (PNNL) has an enduring mission to bring molecular and environmental sciences and engineering strengths to bear on DOE missions and national needs. Their vision is to be recognized worldwide and valued nationally for leadership in accelerating the discovery and deployment of solutions to challenges in energy, national security, and the environment. To achieve this mission and vision, they provide distinctive, world-leading science and technology in: (1) the design and scalablemore » synthesis of materials and chemicals; (2) climate change science and emissions management; (3) efficient and secure electricity management from generation to end use; and (4) signature discovery and exploitation for threat detection and reduction. PNNL leadership also extends to operating EMSL: the Environmental Molecular Sciences Laboratory, a national scientific user facility dedicated to providing itnegrated experimental and computational resources for discovery and technological innovation in the environmental molecular sciences.« less

Big Data: An Opportunity for Collaboration with Computer Scientists on Data-Driven Science

NASA Astrophysics Data System (ADS)

Baru, C.

2014-12-01

Big data technologies are evolving rapidly, driven by the need to manage ever increasing amounts of historical data; process relentless streams of human and machine-generated data; and integrate data of heterogeneous structure from extremely heterogeneous sources of information. Big data is inherently an application-driven problem. Developing the right technologies requires an understanding of the applications domain. Though, an intriguing aspect of this phenomenon is that the availability of the data itself enables new applications not previously conceived of! In this talk, we will discuss how the big data phenomenon creates an imperative for collaboration among domain scientists (in this case, geoscientists) and computer scientists. Domain scientists provide the application requirements as well as insights about the data involved, while computer scientists help assess whether problems can be solved with currently available technologies or require adaptaion of existing technologies and/or development of new technologies. The synergy can create vibrant collaborations potentially leading to new science insights as well as development of new data technologies and systems. The area of interface between geosciences and computer science, also referred to as geoinformatics is, we believe, a fertile area for interdisciplinary research.

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

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.

Computational Unification: a Vision for Connecting Researchers

NASA Astrophysics Data System (ADS)

Troy, R. M.; Kingrey, O. J.

2002-12-01

Computational Unification of science, once only a vision, is becoming a reality. This technology is based upon a scientifically defensible, general solution for Earth Science data management and processing. The computational unification of science offers a real opportunity to foster inter and intra-discipline cooperation, and the end of 're-inventing the wheel'. As we move forward using computers as tools, it is past time to move from computationally isolating, "one-off" or discipline-specific solutions into a unified framework where research can be more easily shared, especially with researchers in other disciplines. The author will discuss how distributed meta-data, distributed processing and distributed data objects are structured to constitute a working interdisciplinary system, including how these resources lead to scientific defensibility through known lineage of all data products. Illustration of how scientific processes are encapsulated and executed illuminates how previously written processes and functions are integrated into the system efficiently and with minimal effort. Meta-data basics will illustrate how intricate relationships may easily be represented and used to good advantage. Retrieval techniques will be discussed including trade-offs of using meta-data versus embedded data, how the two may be integrated, and how simplifying assumptions may or may not help. This system is based upon the experience of the Sequoia 2000 and BigSur research projects at the University of California, Berkeley, whose goals were to find an alternative to the Hughes EOS-DIS system and is presently offered by Science Tools corporation, of which the author is a principal.

A Framework for Evaluating Digital Library Services; Interdisciplinarity: The Road Ahead for Education in Digital Libraries; Federated Digital Rights Management: A Proposed DRM Solution for Research and Education; Learning Lessons Holistically in the Glasgow Digital Library.

ERIC Educational Resources Information Center

Choudhury, Sayeed; Hobbs, Benjamin; Lorie, Mark; Flores, Nicholas; Coleman, Anita; Martin, Mairead; Kuhlman, David L.; McNair, John H.; Rhodes, William A.; Tipton, Ron; Agnew, Grace; Nicholson, Dennis; Macgregor, George

2002-01-01

Includes four articles that address issues related to digital libraries. Highlights include a framework for evaluating digital library services, particularly academic research libraries; interdisciplinary approaches to education about digital libraries that includes library and information science and computing; digital rights management; and the…

Computer Based Instruction in the U.S. Army’s Entry Level Enlisted Training.

DTIC Science & Technology

1985-03-13

rosters with essential personal data, and graduation rosters with class standings and printed diplomas. The computer also managed the progress of the...discussion is presented in Chapter Three. Methods of Employment Course administration. In 1980 the US Army Research Center for Behaviorial and Social Studies...contained in Appendix C. Data Presentation All responses from the questionaires were coded for use by the Statistical Package for the Social Sciences

Computational Difficulties in the Identification and Optimization of Control Systems.

DTIC Science & Technology

1980-01-01

necessary and Identify by block number) - -. 3. iABSTRACT (Continue on revers, side It necessary and Identify by block number) As more realistic models ...Island 02912 ABSTRACT As more realistic models for resource management are developed, the need for efficient computational techniques for parameter...optimization (optimal control) in "state" models which This research was supported in part by ttfe National Science Foundation under grant NSF-MCS 79-05774

Conversational Agents in Virtual Worlds: Bridging Disciplines

ERIC Educational Resources Information Center

Veletsianos, George; Heller, Robert; Overmyer, Scott; Procter, Mike

2010-01-01

This paper examines the effective deployment of conversational agents in virtual worlds from the perspective of researchers/practitioners in cognitive psychology, computing science, learning technologies and engineering. From a cognitive perspective, the major challenge lies in the coordination and management of the various channels of information…

A Multidimensional Software Engineering Course

ERIC Educational Resources Information Center

Barzilay, O.; Hazzan, O.; Yehudai, A.

2009-01-01

Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a…

TEACHING "MATH-LITE" CONSERVATION (BOOK REVIEW OF CONSERVATION BIOLOGY WITH RAMAS ECOLAB)

EPA Science Inventory

This book is designed to serve as a laboratory workbook for an undergraduate course in conservation biology, environmental science, or natural resource management. By integrating with RAMAS EcoLab software, the book provides instructors with hands-on computer exercises that can ...

Tony Magri | NREL

Science.gov Websites

Windows System Engineer with the Computational Science Center. He implements, supports, and integrates Windows-based technology solutions at the ESIF and manages a portion of the VMware infrastructure . Throughout his career, Tony has built a strong skillset in enterprise Windows Engineering and Active

Design and Implementation of a Modern Automatic Deformation Monitoring System

NASA Astrophysics Data System (ADS)

Engel, Philipp; Schweimler, Björn

2016-03-01

The deformation monitoring of structures and buildings is an important task field of modern engineering surveying, ensuring the standing and reliability of supervised objects over a long period. Several commercial hardware and software solutions for the realization of such monitoring measurements are available on the market. In addition to them, a research team at the University of Applied Sciences in Neubrandenburg (NUAS) is actively developing a software package for monitoring purposes in geodesy and geotechnics, which is distributed under an open source licence and free of charge. The task of managing an open source project is well-known in computer science, but it is fairly new in a geodetic context. This paper contributes to that issue by detailing applications, frameworks, and interfaces for the design and implementation of open hardware and software solutions for sensor control, sensor networks, and data management in automatic deformation monitoring. It will be discussed how the development effort of networked applications can be reduced by using free programming tools, cloud computing technologies, and rapid prototyping methods.

Climate Analytics as a Service

NASA Technical Reports Server (NTRS)

Schnase, John L.; Duffy, Daniel Q.; McInerney, Mark A.; Webster, W. Phillip; Lee, Tsengdar J.

2014-01-01

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

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…

Functional requirements document for NASA/MSFC Earth Science and Applications Division: Data and information system (ESAD-DIS). Interoperability, 1992

NASA Technical Reports Server (NTRS)

Stephens, J. Briscoe; Grider, Gary W.

1992-01-01

These Earth Science and Applications Division-Data and Information System (ESAD-DIS) interoperability requirements are designed to quantify the Earth Science and Application Division's hardware and software requirements in terms of communications between personal and visualization workstation, and mainframe computers. The electronic mail requirements and local area network (LAN) requirements are addressed. These interoperability requirements are top-level requirements framed around defining the existing ESAD-DIS interoperability and projecting known near-term requirements for both operational support and for management planning. Detailed requirements will be submitted on a case-by-case basis. This document is also intended as an overview of ESAD-DIs interoperability for new-comers and management not familiar with these activities. It is intended as background documentation to support requests for resources and support requirements.

Exploring Best Practices for Research Data Management in Earth Science through Collaborating with University Libraries

NASA Astrophysics Data System (ADS)

Wang, T.; Branch, B. D.

2013-12-01

Earth Science research data, its data management, informatics processing and its data curation are valuable in allowing earth scientists to make new discoveries. But how to actively manage these research assets to ensure them safe and secure, accessible and reusable for long term is a big challenge. Nowadays, the data deluge makes this challenge become even more difficult. To address the growing demand for managing earth science data, the Council on Library and Information Resources (CLIR) partners with the Library and Technology Services (LTS) of Lehigh University and Purdue University Libraries (PUL) on hosting postdoctoral fellows in data curation activity. This inter-disciplinary fellowship program funded by the SLOAN Foundation innovatively connects university libraries and earth science departments and provides earth science Ph.D.'s opportunities to use their research experiences in earth science and data curation trainings received during their fellowship to explore best practices for research data management in earth science. In the process of exploring best practices for data curation in earth science, the CLIR Data Curation Fellows have accumulated rich experiences and insights on the data management behaviors and needs of earth scientists. Specifically, Ting Wang, the postdoctoral fellow at Lehigh University has worked together with the LTS support team for the College of Arts and Sciences, Web Specialists and the High Performance Computing Team, to assess and meet the data management needs of researchers at the Department of Earth and Environmental Sciences (EES). By interviewing the faculty members and graduate students at EES, the fellow has identified a variety of data-related challenges at different research fields of earth science, such as climate, ecology, geochemistry, geomorphology, etc. The investigation findings of the fellow also support the LTS for developing campus infrastructure for long-term data management in the sciences. Likewise, Benjamin D. Branch, the postdoctoral fellow at PUL conducted GIS (Geographic Information Systems) data curation interviews and worked closely with the GIS Information Specialist towards GIS-related instructional programs in order to recognize the data management needs in GIS research. Conceptually, the research implemented grounded theory approach of campus wide interviews for spatial GIS inquiry. To date, research analysis of a subset of 32 individual interviews with faculty, graduate students, or geospatial staff users is underway with the intent of publication. Collectively, CLIR fellowship program should work to expand the capacity and job resiliency of the library as necessary vehicle of institutional competitiveness via its prominence in data services for future consideration in the areas of data science, data curation, data rescue and collaborative support of the scientific community. In addition, the digital data service aspects of library transformation may be showcased in the results of the fellows' accomplishments.

Big questions, big science: meeting the challenges of global ecology.

PubMed

Schimel, David; Keller, Michael

2015-04-01

Ecologists are increasingly tackling questions that require significant infrastucture, large experiments, networks of observations, and complex data and computation. Key hypotheses in ecology increasingly require more investment, and larger data sets to be tested than can be collected by a single investigator's or s group of investigator's labs, sustained for longer than a typical grant. Large-scale projects are expensive, so their scientific return on the investment has to justify the opportunity cost-the science foregone because resources were expended on a large project rather than supporting a number of individual projects. In addition, their management must be accountable and efficient in the use of significant resources, requiring the use of formal systems engineering and project management to mitigate risk of failure. Mapping the scientific method into formal project management requires both scientists able to work in the context, and a project implementation team sensitive to the unique requirements of ecology. Sponsoring agencies, under pressure from external and internal forces, experience many pressures that push them towards counterproductive project management but a scientific community aware and experienced in large project science can mitigate these tendencies. For big ecology to result in great science, ecologists must become informed, aware and engaged in the advocacy and governance of large ecological projects.

Visual analytics as a translational cognitive science.

PubMed

Fisher, Brian; Green, Tera Marie; Arias-Hernández, Richard

2011-07-01

Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway for development of visual analytics as a translational cognitive science that bridges fundamental research in human/computer cognitive systems and design and evaluation of information systems in situ. Achieving this goal will require the development of enhanced field methods for conceptual decomposition of human/computer cognitive systems that maps onto laboratory studies, and improved methods for conducting laboratory investigations that might better map onto real-world cognitive processes in technology-rich environments. Copyright © 2011 Cognitive Science Society, Inc.

Integration of Panda Workload Management System with supercomputers

NASA Astrophysics Data System (ADS)

De, K.; Jha, S.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Nilsson, P.; Novikov, A.; Oleynik, D.; Panitkin, S.; Poyda, A.; Read, K. F.; Ryabinkin, E.; Teslyuk, A.; Velikhov, V.; Wells, J. C.; Wenaus, T.

2016-09-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), Supercomputer at the National Research Center "Kurchatov Institute", IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run singlethreaded workloads in parallel on Titan's multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accomplishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility's infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Mark F. Davis | NREL

Science.gov Websites

| 303-384-6140 Orcid ID http://orcid.org/0000-0003-4541-9852 Research Interests Dr. Mark Davis is the years, he has served as the Platform Program Manager for Thermochemical and has directed research Science Center, including high throughput recalcitrance assays, omics research, computational modeling

Science and Technology Text Mining: Hypersonic and Supersonic Flow

DTIC Science & Technology

2003-11-17

Saussure , 1949]. A summary of co-word origins, and evolution of co-word into computational linguistics, can be found in Kostoff [1993b]. Co-word...Global Thesauri. Information Processing and Management. 26:5. 1990. De Saussure , F. (1949). Cours de Linguistique Generale. 4eme Edition

Efficient Dependency Computation for Dynamic Hybrid Bayesian Network in On-line System Health Management Applications

DTIC Science & Technology

2014-10-02

intervals (Neil, Tailor, Marquez, Fenton , & Hear, 2007). This is cumbersome, error prone and usually inaccurate. Even though a universal framework...Science. Neil, M., Tailor, M., Marquez, D., Fenton , N., & Hear. (2007). Inference in Bayesian networks using dynamic discretisation. Statistics

Steve Hammond | NREL

Science.gov Websites

Hammond Photo of Steven Hammond Steve Hammond Center Director II-Technical Steven.Hammond@nrel.gov | 303-275-4121 Steve Hammond is director of the Computational Science Center at the National Renewable includes leading NREL's efforts in energy efficient data centers. Prior to NREL, Steve managed the

Volunteered Cloud Computing for Disaster Management

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster management relies increasingly on interpreting earth observations and running numerical models; which require significant computing capacity - usually on short notice and at irregular intervals. Peak computing demand during event detection, hazard assessment, or incident response may exceed agency budgets; however some of it can be met through volunteered computing, which distributes subtasks to participating computers via the Internet. This approach has enabled large projects in mathematics, basic science, and climate research to harness the slack computing capacity of thousands of desktop computers. This capacity is likely to diminish as desktops give way to battery-powered mobile devices (laptops, smartphones, tablets) in the consumer market; but as cloud computing becomes commonplace, it may offer significant slack capacity -- if its users are given an easy, trustworthy mechanism for participating. Such a "volunteered cloud computing" mechanism would also offer several advantages over traditional volunteered computing: tasks distributed within a cloud have fewer bandwidth limitations; granular billing mechanisms allow small slices of "interstitial" computing at no marginal cost; and virtual storage volumes allow in-depth, reversible machine reconfiguration. Volunteered cloud computing is especially suitable for "embarrassingly parallel" tasks, including ones requiring large data volumes: examples in disaster management include near-real-time image interpretation, pattern / trend detection, or large model ensembles. In the context of a major disaster, we estimate that cloud users (if suitably informed) might volunteer hundreds to thousands of CPU cores across a large provider such as Amazon Web Services. To explore this potential, we are building a volunteered cloud computing platform and targeting it to a disaster management context. Using a lightweight, fault-tolerant network protocol, this platform helps cloud users join parallel computing projects; automates reconfiguration of their virtual machines; ensures accountability for donated computing; and optimizes the use of "interstitial" computing. Initial applications include fire detection from multispectral satellite imagery and flood risk mapping through hydrological simulations.

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

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

Peisert, Sean; Potok, Thomas E.; Jones, Todd

At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues includedmore » research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the three topics and a representative of each of the four major DOE Office of Science Advanced Scientific Computing Research Facilities: the Argonne Leadership Computing Facility (ALCF), the Energy Sciences Network (ESnet), the National Energy Research Scientific Computing Center (NERSC), and the Oak Ridge Leadership Computing Facility (OLCF). The rest of the workshop consisted of topical breakout discussions and focused writing periods that produced much of this report.« less

Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland

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

Windus, Theresa; Banda, Michael; Devereaux, Thomas

Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. Wemore » could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.« less

Understanding initial undergraduate expectations and identity in computing studies

NASA Astrophysics Data System (ADS)

Kinnunen, Päivi; Butler, Matthew; Morgan, Michael; Nylen, Aletta; Peters, Anne-Kathrin; Sinclair, Jane; Kalvala, Sara; Pesonen, Erkki

2018-03-01

There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students' initial expectations of university study and career. This paper reports on a study of CS first-year students' expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students' eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.

GSDC: A Unique Data Center in Korea for HEP research

NASA Astrophysics Data System (ADS)

Ahn, Sang-Un

2017-04-01

Global Science experimental Data hub Center (GSDC) at Korea Institute of Science and Technology Information (KISTI) is a unique data center in South Korea established for promoting the fundamental research fields by supporting them with the expertise on Information and Communication Technology (ICT) and the infrastructure for High Performance Computing (HPC), High Throughput Computing (HTC) and Networking. GSDC has supported various research fields in South Korea dealing with the large scale of data, e.g. RENO experiment for neutrino research, LIGO experiment for gravitational wave detection, Genome sequencing project for bio-medical, and HEP experiments such as CDF at FNAL, Belle at KEK, and STAR at BNL. In particular, GSDC has run a Tier-1 center for ALICE experiment using the LHC at CERN since 2013. In this talk, we present the overview on computing infrastructure that GSDC runs for the research fields and we discuss on the data center infrastructure management system deployed at GSDC.

Northeast Artificial Intelligence Consortium (NAIC). Volume 12. Computer Architecture for Very Large Knowledge Bases

DTIC Science & Technology

1990-12-01

data rate to the electronics would be much lower on the average and the data much "richer" in information. Intelligent use of...system bottleneck, a high data rate should be provided by I/O systems. 2. machines with intelligent storage management specially designed for logic...management information processing, surveillance sensors, intelligence data collection and handling, solid state sciences, electromagnetics, and propagation, and electronic reliability/maintainability and compatibility.

Workforce Retention Study in Support of the U.S. Army Aberdeen Test Center Human Capital Management Strategy

DTIC Science & Technology

2016-09-01

Sciences Group 6% 1550s Computer Scientists Group 5% Other 1500s ORSAa, Mathematics, & Statistics Group 3% 1600s Equipment & Facilities Group 4...Employee removal based on misconduct, delinquency , suitability, unsatisfactory performance, or failure to qualify for conversion to a career appointment...average of 10.4% in many areas, but over double the average for the 1550s (Computer Scientists) and other 1500s (ORSA, Mathematics, and Statistics ). Also

White paper on science operations

NASA Technical Reports Server (NTRS)

Schreier, Ethan J.

1991-01-01

Major changes are taking place in the way astronomy gets done. There are continuing advances in observational capabilities across the frequency spectrum, involving both ground-based and space-based facilities. There is also very rapid evolution of relevant computing and data management technologies. However, although the new technologies are filtering in to the astronomy community, and astronomers are looking at their computing needs in new ways, there is little coordination or coherent policy. Furthermore, although there is great awareness of the evolving technologies in the arena of operations, much of the existing operations infrastructure is ill-suited to take advantage of them. Astronomy, especially space astronomy, has often been at the cutting edge of computer use in data reduction and image analysis, but has been somewhat removed from advanced applications in operations, which have tended to be implemented by industry rather than by the end-user scientists. The purpose of this paper is threefold. First, we briefly review the background and general status of astronomy-related computing. Second, we make recommendations in three areas: data analysis; operations (directed primarily to NASA-related activities); and issues of management and policy, believing that these must be addressed to enable technological progress and to proceed through the next decade. Finally, we recommend specific NASA-related work as part of the Astrotech-21 plans, to enable better science operations in the operations of the Great Observatories and in the lunar outpost era.

Production Management System for AMS Computing Centres

NASA Astrophysics Data System (ADS)

Choutko, V.; Demakov, O.; Egorov, A.; Eline, A.; Shan, B. S.; Shi, R.

2017-10-01

The Alpha Magnetic Spectrometer [1] (AMS) has collected over 95 billion cosmic ray events since it was installed on the International Space Station (ISS) on May 19, 2011. To cope with enormous flux of events, AMS uses 12 computing centers in Europe, Asia and North America, which have different hardware and software configurations. The centers are participating in data reconstruction, Monte-Carlo (MC) simulation [2]/Data and MC production/as well as in physics analysis. Data production management system has been developed to facilitate data and MC production tasks in AMS computing centers, including job acquiring, submitting, monitoring, transferring, and accounting. It was designed to be modularized, light-weighted, and easy-to-be-deployed. The system is based on Deterministic Finite Automaton [3] model, and implemented by script languages, Python and Perl, and the built-in sqlite3 database on Linux operating systems. Different batch management systems, file system storage, and transferring protocols are supported. The details of the integration with Open Science Grid are presented as well.

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

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

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

DOE PAGES

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...

2015-07-14

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

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.

CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and Collaboration

NASA Astrophysics Data System (ADS)

Seul, M.; Brazil, L.; Castronova, A. M.

2017-12-01

CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and CollaborationEnabling research surrounding interdisciplinary topics often requires a combination of finding, managing, and analyzing large data sets and models from multiple sources. This challenge has led the National Science Foundation to make strategic investments in developing community data tools and cyberinfrastructure that focus on water data, as it is central need for many of these research topics. CUAHSI (The Consortium of Universities for the Advancement of Hydrologic Science, Inc.) is a non-profit organization funded by the National Science Foundation to aid students, researchers, and educators in using and managing data and models to support research and education in the water sciences. This presentation will focus on open-source CUAHSI-supported tools that enable enhanced data discovery online using advanced searching capabilities and computational analysis run in virtual environments pre-designed for educators and scientists so they can focus their efforts on data analysis rather than IT set-up.

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.

GES DISC Data Recipes in Jupyter Notebooks

NASA Astrophysics Data System (ADS)

Li, A.; Banavige, B.; Garimella, K.; Rice, J.; Shen, S.; Liu, Z.

2017-12-01

The Earth Science Data and Information System (ESDIS) Project manages twelve Distributed Active Archive Centers (DAACs) which are geographically dispersed across the United States. The DAACs are responsible for ingesting, processing, archiving, and distributing Earth science data produced from various sources (satellites, aircraft, field measurements, etc.). In response to projections of an exponential increase in data production, there has been a recent effort to prototype various DAAC activities in the cloud computing environment. This, in turn, led to the creation of an initiative, called the Cloud Analysis Toolkit to Enable Earth Science (CATEES), to develop a Python software package in order to transition Earth science data processing to the cloud. This project, in particular, supports CATEES and has two primary goals. One, transition data recipes created by the Goddard Earth Science Data and Information Service Center (GES DISC) DAAC into an interactive and educational environment using Jupyter Notebooks. Two, acclimate Earth scientists to cloud computing. To accomplish these goals, we create Jupyter Notebooks to compartmentalize the different steps of data analysis and help users obtain and parse data from the command line. We also develop a Docker container, comprised of Jupyter Notebooks, Python library dependencies, and command line tools, and configure it into an easy to deploy package. The end result is an end-to-end product that simulates the use case of end users working in the cloud computing environment.

Team Projects and Peer Evaluations

ERIC Educational Resources Information Center

Doyle, John Kevin; Meeker, Ralph D.

2008-01-01

The authors assign semester- or quarter-long team-based projects in several Computer Science and Finance courses. This paper reports on our experience in designing, managing, and evaluating such projects. In particular, we discuss the effects of team size and of various peer evaluation schemes on team performance and student learning. We report…

Markush enumeration to manage, mesh and manipulate substances of unknown or variable composition (ACS Fall meeting 5 of 12)

EPA Science Inventory

The National Center for Computational Toxicology (NCCT) at the US Environmental Protection Agency has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences. This includes high-throughput in vitro screening data, legacy in vivo...

Collaborative Approach in Software Engineering Education: An Interdisciplinary Case

ERIC Educational Resources Information Center

Vicente, Aileen Joan; Tan, Tiffany Adelaine; Yu, Alvin Ray

2018-01-01

Aim/Purpose: This study was aimed at enhancing students' learning of software engineering methods. A collaboration between the Computer Science, Business Management, and Product Design programs was formed to work on actual projects with real clients. This interdisciplinary form of collaboration simulates the realities of a diverse Software…

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.

Climbing the Slope of Enlightenment during NASA's Arctic Boreal Vulnerability Experiment

NASA Astrophysics Data System (ADS)

Griffith, P. C.; Hoy, E.; Duffy, D.; McInerney, M.

2015-12-01

The Arctic Boreal Vulnerability Experiment (ABoVE) is a new field campaign sponsored by NASA's Terrestrial Ecology Program and designed to improve understanding of the vulnerability and resilience of Arctic and boreal social-ecological systems to environmental change (http://above.nasa.gov). ABoVE is integrating field-based studies, modeling, and data from airborne and satellite remote sensing. The NASA Center for Climate Simulation (NCCS) has partnered with the NASA Carbon Cycle and Ecosystems Office (CCEO) to create a high performance science cloud for this field campaign. The ABoVE Science Cloud combines high performance computing with emerging technologies and data management with tools for analyzing and processing geographic information to create an environment specifically designed for large-scale modeling, analysis of remote sensing data, copious disk storage for "big data" with integrated data management, and integration of core variables from in-situ networks. The ABoVE Science Cloud is a collaboration that is accelerating the pace of new Arctic science for researchers participating in the field campaign. Specific examples of the utilization of the ABoVE Science Cloud by several funded projects will be presented.

Spacecraft computer resource margin management. [of Project Galileo Orbiter in-flight reprogramming task

NASA Technical Reports Server (NTRS)

Larman, B. T.

1981-01-01

The conduction of the Project Galileo Orbiter, with 18 microcomputers and the equivalent of 360K 8-bit bytes of memory contained within two major engineering subsystems and eight science instruments, requires that the key onboard computer system resources be managed in a very rigorous manner. Attention is given to the rationale behind the project policy, the development stage, the preliminary design stage, the design/implementation stage, and the optimization or 'scrubbing' stage. The implementation of the policy is discussed, taking into account the development of the Attitude and Articulation Control Subsystem (AACS) and the Command and Data Subsystem (CDS), the reporting of margin status, and the response to allocation oversubscription.

Real Time Flood Alert System (RTFAS) for Puerto Rico

USGS Publications Warehouse

Lopez-Trujillo, Dianne

2010-01-01

The Real Time Flood Alert System is a web-based computer program, developed as a data integration tool, and designed to increase the ability of emergency managers to rapidly and accurately predict flooding conditions of streams in Puerto Rico. The system includes software and a relational database to determine the spatial and temporal distribution of rainfall, water levels in streams and reservoirs, and associated storms to determine hazardous and potential flood conditions. The computer program was developed as part of a cooperative agreement between the U.S. Geological Survey Caribbean Water Science Center and the Puerto Rico Emergency Management Agency, and integrates information collected and processed by these two agencies and the National Weather Service.

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.

Bioinformatics.

PubMed

Moore, Jason H

2007-11-01

Bioinformatics is an interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences such as biochemistry, cell biology, developmental biology, genetics, genomics, and physiology. An important goal of bioinformatics is to facilitate the management, analysis, and interpretation of data from biological experiments and observational studies. The goal of this review is to introduce some of the important concepts in bioinformatics that must be considered when planning and executing a modern biological research study. We review database resources as well as data mining software tools.

Technology 2000, volume 1

NASA Technical Reports Server (NTRS)

1991-01-01

The purpose of the conference was to increase awareness of existing NASA developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. There were sessions on the following: Computer technology and software engineering; Human factors engineering and life sciences; Information and data management; Material sciences; Manufacturing and fabrication technology; Power, energy, and control systems; Robotics; Sensors and measurement technology; Artificial intelligence; Environmental technology; Optics and communications; and Superconductivity.

Robust Functionality and Active Data Management for Cooperative Networks in the Presence of WMD Stressors

DTIC Science & Technology

2011-09-01

topological impairments," Wiley Handbook of Science and Technology for Homeland Security, 2009. Technical Summary Introduction: DCSs offer a flexible...8217l , nfc ,approx = 1 - 2 2" N 1S t e second argest rugenv(.l..lue o Tapprox , where aN = .,., an subscript "nEe" denotes the eigenvalues for the case...robust distributed computing in the presence of topological impairmt~nts," Wiley Handbook of Science and Technology for Homeland Security, 2009. (3

Opportunities and challenges of big data for the social sciences: The case of genomic data.

PubMed

Liu, Hexuan; Guo, Guang

2016-09-01

In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research. Copyright © 2016 Elsevier Inc. All rights reserved.

The CCTC Quick-Reacting General War Gaming System (QUICK) Program Maintenance Manual. Volume I. Data Management Subsystem. Change 3.

DTIC Science & Technology

1980-05-22

cross -referenced with the number of the data transaction listed in the data module quality con- trol list NVB Integer variable used to...Organization of the Joint Chiefs of Staff. Technical support was provided by System Sciences, Incorporated under Contract Number DCA100-75-C-0019. Change set... Contract Number DCA 100-75-C-0019. Change set two was prepared u nder Contract Number DCA 100-78-C-0035. Computer Sciences Corporation prepared change

Tracking the NGS revolution: managing life science research on shared high-performance computing clusters.

PubMed

Dahlö, Martin; Scofield, Douglas G; Schaal, Wesley; Spjuth, Ola

2018-05-01

Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases.

The space physics analysis network

NASA Astrophysics Data System (ADS)

Green, James L.

1988-04-01

The Space Physics Analysis Network, or SPAN, is emerging as a viable method for solving an immediate communication problem for space and Earth scientists and has been operational for nearly 7 years. SPAN and its extension into Europe, utilizes computer-to-computer communications allowing mail, binary and text file transfer, and remote logon capability to over 1000 space science computer systems. The network has been used to successfully transfer real-time data to remote researchers for rapid data analysis but its primary function is for non-real-time applications. One of the major advantages for using SPAN is its spacecraft mission independence. Space science researchers using SPAN are located in universities, industries and government institutions all across the United States and Europe. These researchers are in such fields as magnetospheric physics, astrophysics, ionosperic physics, atmospheric physics, climatology, meteorology, oceanography, planetary physics and solar physics. SPAN users have access to space and Earth science data bases, mission planning and information systems, and computational facilities for the purposes of facilitating correlative space data exchange, data analysis and space research. For example, the National Space Science Data Center (NSSDC), which manages the network, is providing facilities on SPAN such as the Network Information Center (SPAN NIC). SPAN has interconnections with several national and international networks such as HEPNET and TEXNET forming a transparent DECnet network. The combined total number of computers now reachable over these combined networks is about 2000. In addition, SPAN supports full function capabilities over the international public packet switched networks (e.g. TELENET) and has mail gateways to ARPANET, BITNET and JANET.

Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

PubMed Central

2018-01-01

Abstract Background Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. Results The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Conclusions Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases. PMID:29659792

Long live the Data Scientist, but can he/she persist?

NASA Astrophysics Data System (ADS)

Wyborn, L. A.

2011-12-01

In recent years the fourth paradigm of data intensive science has slowly taken hold as the increased capacity of instruments and an increasing number of instruments (in particular sensor networks) have changed how fundamental research is undertaken. Most modern scientific research is about digital capture of data direct from instruments, processing it by computers, storing the results on computers and only publishing a small fraction of data in hard copy publications. At the same time, the rapid increase in capacity of supercomputers, particularly at petascale, means that far larger data sets can be analysed and to greater resolution than previously possible. The new cloud computing paradigm which allows distributed data, software and compute resources to be linked by seamless workflows, is creating new opportunities in processing of high volumes of data to an increasingly larger number of researchers. However, to take full advantage of these compute resources, data sets for analysis have to be aggregated from multiple sources to create high performance data sets. These new technology developments require that scientists must become more skilled in data management and/or have a higher degree of computer literacy. In almost every science discipline there is now an X-informatics branch and a computational X branch (eg, Geoinformatics and Computational Geoscience): both require a new breed of researcher that has skills in both the science fundamentals and also knowledge of some ICT aspects (computer programming, data base design and development, data curation, software engineering). People that can operate in both science and ICT are increasingly known as 'data scientists'. Data scientists are a critical element of many large scale earth and space science informatics projects, particularly those that are tackling current grand challenges at an international level on issues such as climate change, hazard prediction and sustainable development of our natural resources. These projects by their very nature require the integration of multiple digital data sets from multiple sources. Often the preparation of the data for computational analysis can take months and requires painstaking attention to detail to ensure that anomalies identified are real and are not just artefacts of the data preparation and/or the computational analysis. Although data scientists are increasingly vital to successful data intensive earth and space science projects, unless they are recognised for their capabilities in both the science and the computational domains they are likely to migrate to either a science role or an ICT role as their career advances. Most reward and recognition systems do not recognise those with skills in both, hence, getting trained data scientists to persist beyond one or two projects can be challenge. Those data scientists that persist in the profession are characteristically committed and enthusiastic people who have the support of their organisations to take on this role. They also tend to be people who share developments and are critical to the success of the open source software movement. However, the fact remains that survival of the data scientist as a species is being threatened unless something is done to recognise their invaluable contributions to the new fourth paradigm of science.

FermiGrid—experience and future plans

NASA Astrophysics Data System (ADS)

Chadwick, K.; Berman, E.; Canal, P.; Hesselroth, T.; Garzoglio, G.; Levshina, T.; Sergeev, V.; Sfiligoi, I.; Sharma, N.; Timm, S.; Yocum, D. R.

2008-07-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid (OSG) and the Worldwide LHC Computing Grid Collaboration (WLCG). FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the OSG, EGEE, and the WLCG. Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure - the successes and the problems.

TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

NASA Astrophysics Data System (ADS)

Nelson, J.; Jones, N.; Ames, D. P.

2015-12-01

Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

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

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.

Challenges and opportunities of cloud computing for atmospheric sciences

NASA Astrophysics Data System (ADS)

Pérez Montes, Diego A.; Añel, Juan A.; Pena, Tomás F.; Wallom, David C. H.

2016-04-01

Cloud computing is an emerging technological solution widely used in many fields. Initially developed as a flexible way of managing peak demand it has began to make its way in scientific research. One of the greatest advantages of cloud computing for scientific research is independence of having access to a large cyberinfrastructure to fund or perform a research project. Cloud computing can avoid maintenance expenses for large supercomputers and has the potential to 'democratize' the access to high-performance computing, giving flexibility to funding bodies for allocating budgets for the computational costs associated with a project. Two of the most challenging problems in atmospheric sciences are computational cost and uncertainty in meteorological forecasting and climate projections. Both problems are closely related. Usually uncertainty can be reduced with the availability of computational resources to better reproduce a phenomenon or to perform a larger number of experiments. Here we expose results of the application of cloud computing resources for climate modeling using cloud computing infrastructures of three major vendors and two climate models. We show how the cloud infrastructure compares in performance to traditional supercomputers and how it provides the capability to complete experiments in shorter periods of time. The monetary cost associated is also analyzed. Finally we discuss the future potential of this technology for meteorological and climatological applications, both from the point of view of operational use and research.

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.

Collaboratively Architecting a Scalable and Adaptable Petascale Infrastructure to Support Transdisciplinary Scientific Research for the Australian Earth and Environmental Sciences

NASA Astrophysics Data System (ADS)

Wyborn, L. A.; Evans, B. J. K.; Pugh, T.; Lescinsky, D. T.; Foster, C.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) at the Australian National University (ANU) is a partnership between CSIRO, ANU, Bureau of Meteorology (BoM) and Geoscience Australia. Recent investments in a 1.2 PFlop Supercomputer (Raijin), ~ 20 PB data storage using Lustre filesystems and a 3000 core high performance cloud have created a hybrid platform for higher performance computing and data-intensive science to enable large scale earth and climate systems modelling and analysis. There are > 3000 users actively logging in and > 600 projects on the NCI system. Efficiently scaling and adapting data and software systems to petascale infrastructures requires the collaborative development of an architecture that is designed, programmed and operated to enable users to interactively invoke different forms of in-situ computation over complex and large scale data collections. NCI makes available major and long tail 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, bio and social. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. Collections are the operational form for data management and access. Similar data types from individual custodians are managed cohesively. Use of international standards for discovery and interoperability allow complex interactions within and between the collections. This design facilitates a transdisciplinary approach to research and enables a shift from small scale, 'stove-piped' science efforts to large scale, collaborative systems science. This new and complex infrastructure requires a move to shared, globally trusted software frameworks that can be maintained and updated. Workflow engines become essential and need to integrate provenance, versioning, traceability, repeatability and publication. There are also human resource challenges as highly skilled HPC/HPD specialists, specialist programmers, and data scientists are required whose skills can support scaling to the new paradigm of effective and efficient data-intensive earth science analytics on petascale, and soon to be exascale systems.

Three dimensional adaptive mesh refinement on a spherical shell for atmospheric models with lagrangian coordinates

NASA Astrophysics Data System (ADS)

Penner, Joyce E.; Andronova, Natalia; Oehmke, Robert C.; Brown, Jonathan; Stout, Quentin F.; Jablonowski, Christiane; van Leer, Bram; Powell, Kenneth G.; Herzog, Michael

2007-07-01

One of the most important advances needed in global climate models is the development of atmospheric General Circulation Models (GCMs) that can reliably treat convection. Such GCMs require high resolution in local convectively active regions, both in the horizontal and vertical directions. During previous research we have developed an Adaptive Mesh Refinement (AMR) dynamical core that can adapt its grid resolution horizontally. Our approach utilizes a finite volume numerical representation of the partial differential equations with floating Lagrangian vertical coordinates and requires resolving dynamical processes on small spatial scales. For the latter it uses a newly developed general-purpose library, which facilitates 3D block-structured AMR on spherical grids. The library manages neighbor information as the blocks adapt, and handles the parallel communication and load balancing, freeing the user to concentrate on the scientific modeling aspects of their code. In particular, this library defines and manages adaptive blocks on the sphere, provides user interfaces for interpolation routines and supports the communication and load-balancing aspects for parallel applications. We have successfully tested the library in a 2-D (longitude-latitude) implementation. During the past year, we have extended the library to treat adaptive mesh refinement in the vertical direction. Preliminary results are discussed. This research project is characterized by an interdisciplinary approach involving atmospheric science, computer science and mathematical/numerical aspects. The work is done in close collaboration between the Atmospheric Science, Computer Science and Aerospace Engineering Departments at the University of Michigan and NOAA GFDL.

National Climate Change and Wildlife Science Center project accomplishments: highlights

USGS Publications Warehouse

Holl, Sally

2011-01-01

The National Climate Change and Wildlife Science Center (NCCWSC) has invested more than $20M since 2008 to put cutting-edge climate science research in the hands of resource managers across the Nation. With NCCWSC support, more than 25 cooperative research initiatives led by U.S. Geological Survey (USGS) researchers and technical staff are advancing our understanding of habitats and species to provide guidance to managers in the face of a changing climate. Projects focus on quantifying and predicting interactions between climate, habitats, species, and other natural resources such as water. Spatial scales of the projects range from the continent of North America, to a regional scale such as the Pacific Northwest United States, to a landscape scale such as the Florida Everglades. Time scales range from the outset of the 20th century to the end of the 21st century. Projects often lead to workshops, presentations, publications and the creation of new websites, computer models, and data visualization tools. Partnership-building is also a key focus of the NCCWSC-supported projects. New and on-going cooperative partnerships have been forged and strengthened with resource managers and scientists at Federal, tribal, state, local, academic, and non-governmental organizations. USGS scientists work closely with resource managers to produce timely and relevant results that can assist managers and policy makers in current resource management decisions. This fact sheet highlights accomplishments of five NCCWSC projects.

Wildlife software: procedures for publication of computer software

USGS Publications Warehouse

Samuel, M.D.

1990-01-01

Computers and computer software have become an integral part of the practice of wildlife science. Computers now play an important role in teaching, research, and management applications. Because of the specialized nature of wildlife problems, specific computer software is usually required to address a given problem (e.g., home range analysis). This type of software is not usually available from commercial vendors and therefore must be developed by those wildlife professionals with particular skill in computer programming. Current journal publication practices generally prevent a detailed description of computer software associated with new techniques. In addition, peer review of journal articles does not usually include a review of associated computer software. Thus, many wildlife professionals are usually unaware of computer software that would meet their needs or of major improvements in software they commonly use. Indeed most users of wildlife software learn of new programs or important changes only by word of mouth.

Kwf-Grid workflow management system for Earth science applications

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.

2009-04-01

In this paper, we present workflow management tool for Earth science applications in EGEE. The workflow management tool was originally developed within K-wf Grid project for GT4 middleware and has many advanced features like semi-automatic workflow composition, user-friendly GUI for managing workflows, knowledge management. In EGEE, we are porting the workflow management tool to gLite middleware for Earth science applications K-wf Grid workflow management system was developed within "Knowledge-based Workflow System for Grid Applications" under the 6th Framework Programme. The workflow mangement system intended to - semi-automatically compose a workflow of Grid services, - execute the composed workflow application in a Grid computing environment, - monitor the performance of the Grid infrastructure and the Grid applications, - analyze the resulting monitoring information, - capture the knowledge that is contained in the information by means of intelligent agents, - and finally to reuse the joined knowledge gathered from all participating users in a collaborative way in order to efficiently construct workflows for new Grid applications. Kwf Grid workflow engines can support different types of jobs (e.g. GRAM job, web services) in a workflow. New class of gLite job has been added to the system, allows system to manage and execute gLite jobs in EGEE infrastructure. The GUI has been adapted to the requirements of EGEE users, new credential management servlet is added to portal. Porting K-wf Grid workflow management system to gLite would allow EGEE users to use the system and benefit from its avanced features. The system is primarly tested and evaluated with applications from ES clusters.

Building Real World Domain-Specific Social Network Websites as a Capstone Project

ERIC Educational Resources Information Center

Yue, Kwok-Bun; De Silva, Dilhar; Kim, Dan; Aktepe, Mirac; Nagle, Stewart; Boerger, Chris; Jain, Anubha; Verma, Sunny

2009-01-01

This paper describes our experience of using Content Management Software (CMS), specifically Joomla, to build a real world domain-specific social network site (SNS) as a capstone project for graduate information systems and computer science students. As Web 2.0 technologies become increasingly important in driving business application development,…

A framework for propagation of uncertainty contributed by parameterization, input data, model structure, and calibration/validation data in watershed modeling

USDA-ARS?s Scientific Manuscript database

The progressive improvement of computer science and development of auto-calibration techniques means that calibration of simulation models is no longer a major challenge for watershed planning and management. Modelers now increasingly focus on challenges such as improved representation of watershed...

Research Methodologies Explored for a Paradigm Shift in University Teaching.

ERIC Educational Resources Information Center

Venter, I. M.; Blignaut, R. J.; Stoltz, D.

2001-01-01

Innovative teaching methods such as collaborative learning, teamwork, and mind maps were introduced to teach computer science and statistics courses at a South African university. Soft systems methodology was adapted and used to manage the research process of evaluating the effectiveness of the teaching methods. This research method provided proof…

Fusion Simulation Project Workshop Report

NASA Astrophysics Data System (ADS)

Kritz, Arnold; Keyes, David

2009-03-01

The mission of the Fusion Simulation Project is to develop a predictive capability for the integrated modeling of magnetically confined plasmas. This FSP report adds to the previous activities that defined an approach to integrated modeling in magnetic fusion. These previous activities included a Fusion Energy Sciences Advisory Committee panel that was charged to study integrated simulation in 2002. The report of that panel [Journal of Fusion Energy 20, 135 (2001)] recommended the prompt initiation of a Fusion Simulation Project. In 2003, the Office of Fusion Energy Sciences formed a steering committee that developed a project vision, roadmap, and governance concepts [Journal of Fusion Energy 23, 1 (2004)]. The current FSP planning effort involved 46 physicists, applied mathematicians and computer scientists, from 21 institutions, formed into four panels and a coordinating committee. These panels were constituted to consider: Status of Physics Components, Required Computational and Applied Mathematics Tools, Integration and Management of Code Components, and Project Structure and Management. The ideas, reported here, are the products of these panels, working together over several months and culminating in a 3-day workshop in May 2007.

Development of AN Open-Source Automatic Deformation Monitoring System for Geodetical and Geotechnical Measurements

NASA Astrophysics Data System (ADS)

Engel, P.; Schweimler, B.

2016-04-01

The deformation monitoring of structures and buildings is an important task field of modern engineering surveying, ensuring the standing and reliability of supervised objects over a long period. Several commercial hardware and software solutions for the realization of such monitoring measurements are available on the market. In addition to them, a research team at the Neubrandenburg University of Applied Sciences (NUAS) is actively developing a software package for monitoring purposes in geodesy and geotechnics, which is distributed under an open source licence and free of charge. The task of managing an open source project is well-known in computer science, but it is fairly new in a geodetic context. This paper contributes to that issue by detailing applications, frameworks, and interfaces for the design and implementation of open hardware and software solutions for sensor control, sensor networks, and data management in automatic deformation monitoring. It will be discussed how the development effort of networked applications can be reduced by using free programming tools, cloud computing technologies, and rapid prototyping methods.

Correlative visualization techniques for multidimensional data

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Goettsche, Craig

1989-01-01

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.

A WPS Based Architecture for Climate Data Analytic Services (CDAS) at NASA

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; McInerney, M.; Duffy, D.; Carriere, L.; Potter, G. L.; Doutriaux, C.

2015-12-01

Faced with unprecedented growth in the Big Data domain of climate science, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute trusted and tested analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using trusted climate data analysis tools (ESMF, CDAT, NCO, etc.). The framework is structured as a set of interacting modules allowing maximal flexibility in deployment choices. The current set of module managers include: Staging Manager: Runs the computation locally on the WPS server or remotely using tools such as celery or SLURM. Compute Engine Manager: Runs the computation serially or distributed over nodes using a parallelization framework such as celery or spark. Decomposition Manger: Manages strategies for distributing the data over nodes. Data Manager: Handles the import of domain data from long term storage and manages the in-memory and disk-based caching architectures. Kernel manager: A kernel is an encapsulated computational unit which executes a processor's compute task. Each kernel is implemented in python exploiting existing analysis packages (e.g. CDAT) and is compatible with all CDAS compute engines and decompositions. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be executed using either direct web service calls, a python script or application, or a javascript-based web application. Client packages in python or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends, compare multiple reanalysis datasets, and variability.

Computers in Medical Education: A Cooperative Approach to Planning and Implementation

PubMed Central

Ellis, Lynda B.M.; Fuller, Sherrilynne

1988-01-01

After years of ‘ad hoc’ growth in the use of computers in the curriculum, the University of Minnesota Medical School in cooperation with the Bio-Medical Library and Health Sciences Computing Services developed and began implementation of a plan for integration of medical informatics into all phases of medical education. Objectives were developed which focus on teaching skills related to: 1) accessing, retrieving, evaluating and managing medical information; 2) appropriate utilization of computer-assisted instruction lessons; 3) electronic communication with fellow students and medical faculty; and 4) fostering a lifelong commitment to effective use of computers to solve clinical problems. Surveys assessed the status of computer expertise among faculty and entering students. The results of these surveys, lessons learned from this experience, and implications for the future of computers in medical education are discussed.

The state of the Java universe

ScienceCinema

Gosling, James

2018-05-22

Speaker Bio: James Gosling received a B.Sc. in computer science from the University of Calgary, Canada in 1977. He received a Ph.D. in computer science from Carnegie-Mellon University in 1983. The title of his thesis was The Algebraic Manipulation of Constraints. He has built satellite data acquisition systems, a multiprocessor version of UNIX®, several compilers, mail systems, and window managers. He has also built a WYSIWYG text editor, a constraint-based drawing editor, and a text editor called Emacs, for UNIX systems. At Sun his early activity was as lead engineer of the NeWS window system. He did the original design of the Java programming language and implemented its original compiler and virtual machine. He has recently been a contributor to the Real-Time Specification for Java.

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

Gosling, James

Speaker Bio: James Gosling received a B.Sc. in computer science from the University of Calgary, Canada in 1977. He received a Ph.D. in computer science from Carnegie-Mellon University in 1983. The title of his thesis was The Algebraic Manipulation of Constraints. He has built satellite data acquisition systems, a multiprocessor version of UNIX®, several compilers, mail systems, and window managers. He has also built a WYSIWYG text editor, a constraint-based drawing editor, and a text editor called Emacs, for UNIX systems. At Sun his early activity was as lead engineer of the NeWS window system. He did the original designmore » of the Java programming language and implemented its original compiler and virtual machine. He has recently been a contributor to the Real-Time Specification for Java.« less

Reducing Time to Science: Unidata and JupyterHub Technology Using the Jetstream Cloud

NASA Astrophysics Data System (ADS)

Chastang, J.; Signell, R. P.; Fischer, J. L.

2017-12-01

Cloud computing can accelerate scientific workflows, discovery, and collaborations by reducing research and data friction. We describe the deployment of Unidata and JupyterHub technologies on the NSF-funded XSEDE Jetstream cloud. With the aid of virtual machines and Docker technology, we deploy a Unidata JupyterHub server co-located with a Local Data Manager (LDM), THREDDS data server (TDS), and RAMADDA geoscience content management system. We provide Jupyter Notebooks and the pre-built Python environments needed to run them. The notebooks can be used for instruction and as templates for scientific experimentation and discovery. We also supply a large quantity of NCEP forecast model results to allow data-proximate analysis and visualization. In addition, users can transfer data using Globus command line tools, and perform their own data-proximate analysis and visualization with Notebook technology. These data can be shared with others via a dedicated TDS server for scientific distribution and collaboration. There are many benefits of this approach. Not only is the cloud computing environment fast, reliable and scalable, but scientists can analyze, visualize, and share data using only their web browser. No local specialized desktop software or a fast internet connection is required. This environment will enable scientists to spend less time managing their software and more time doing science.

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.

AstroGrid-D: Grid technology for astronomical science

NASA Astrophysics Data System (ADS)

Enke, Harry; Steinmetz, Matthias; Adorf, Hans-Martin; Beck-Ratzka, Alexander; Breitling, Frank; Brüsemeister, Thomas; Carlson, Arthur; Ensslin, Torsten; Högqvist, Mikael; Nickelt, Iliya; Radke, Thomas; Reinefeld, Alexander; Reiser, Angelika; Scholl, Tobias; Spurzem, Rainer; Steinacker, Jürgen; Voges, Wolfgang; Wambsganß, Joachim; White, Steve

2011-02-01

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites (Section 2.1), and advanced applications for specific scientific purposes (Section 2.2), such as a connection to robotic telescopes (Section 2.2.3). We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.

New frontiers in design synthesis

NASA Technical Reports Server (NTRS)

Goldin, D. S.; Venneri, S. L.; Noor, A. K.

1999-01-01

The Intelligent Synthesis Environment (ISE), which is one of the major strategic technologies under development at NASA centers and the University of Virginia, is described. One of the major objectives of ISE is to significantly enhance the rapid creation of innovative affordable products and missions. ISE uses a synergistic combination of leading-edge technologies, including high performance computing, high capacity communications and networking, human-centered computing, knowledge-based engineering, computational intelligence, virtual product development, and product information management. The environment will link scientists, design teams, manufacturers, suppliers, and consultants who participate in the mission synthesis as well as in the creation and operation of the aerospace system. It will radically advance the process by which complex science missions are synthesized, and high-tech engineering Systems are designed, manufactured and operated. The five major components critical to ISE are human-centered computing, infrastructure for distributed collaboration, rapid synthesis and simulation tools, life cycle integration and validation, and cultural change in both the engineering and science creative process. The five components and their subelements are described. Related U.S. government programs are outlined and the future impact of ISE on engineering research and education is discussed.

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

Enabling New and More Transparent Science via DataONE—a Virtual Data Observation Network for Earth (Invited)

NASA Astrophysics Data System (ADS)

Michener, W.

2010-12-01

Addressing grand environmental science challenges requires unprecedented access to easily understood data that cross the breadth of temporal, spatial, and thematic scales. From a scientist’s perspective, the big challenges lie in discovering the relevant data, dealing with extreme data heterogeneity, and converting data to information and knowledge. Addressing these challenges requires new approaches for managing, preserving, analyzing, and sharing data. DataONE is designed to be the foundation of new innovative environmental research that addresses questions of relevance to science and society. DataONE will ensure preservation and access to multi-scale, multi-discipline, and multi-national data. Operationally, DataONE encompasses a distributed global network of Member Nodes (i.e., data repositories) that provide open and persistent access to well-described and easily discovered Earth observational data. In addition, a smaller number of Coordinating Nodes (i.e., metadata repositories and service centers) support network-wide services such as data replication and access to an array of enabling tools. DataONE’s objectives are to: make biological data available from the genome to the ecosystem; make environmental data available from atmospheric, ecological, hydrological, and oceanographic sources; provide secure and long-term preservation and access; and engage scientists, land-managers, policy makers, students, educators, and the public through logical access and intuitive visualizations. The foundation for excellence of DataONE is the established collaboration among participating organizations that have multi-decade expertise in a wide range of fields that includes: existing archive initiatives, libraries, environmental observing systems and research networks, data and information management, science synthesis centers, and professional societies. DataONE is a means to serve a broad range of science domains directly and indirectly through interoperability with partnering networks. DataONE engages its community of partners through working groups focused on identifying, describing, and implementing the DataONE cyberinfrastructure, governance, and sustainability models. These working groups, which consist of a diverse group of graduate students, educators, government and industry representatives, and leading computer, information, and library scientists: (1) perform computer science, informatics, and social science research related to all stages of the data life cycle; (2) develop DataONE interfaces and prototypes; (3) adopt/adapt interoperability standards; (4) create value-added technologies (e.g., semantic mediation, scientific workflow, and visualization) that facilitate data integration, analysis, and understanding; (5) address socio-cultural barriers to sustainable data preservation and data sharing; and (6) promote the adoption of best practices for managing the full data life cycle.

Sharing Responsibility for Data Stewardship Between Scientists and Curators

NASA Astrophysics Data System (ADS)

Hedstrom, M. L.

2012-12-01

Data stewardship is becoming increasingly important to support accurate conclusions from new forms of data, integration of and computation across heterogeneous data types, interactions between models and data, replication of results, data governance and long-term archiving. In addition to increasing recognition of the importance of data management, data science, and data curation by US and international scientific agencies, the National Academies of Science Board on Research Data and Information is sponsoring a study on Data Curation Education and Workforce Issues. Effective data stewardship requires a distributed effort among scientists who produce data, IT staff and/or vendors who provide data storage and computational facilities and services, and curators who enhance data quality, manage data governance, provide access to third parties, and assume responsibility for long-term archiving of data. The expertise necessary for scientific data management includes a mix of knowledge of the scientific domain; an understanding of domain data requirements, standards, ontologies and analytical methods; facility with leading edge information technology; and knowledge of data governance, standards, and best practices for long-term preservation and access that rarely are found in a single individual. Rather than developing data science and data curation as new and distinct occupations, this paper examines the set of tasks required for data stewardship. The paper proposes an alternative model that embeds data stewardship in scientific workflows and coordinates hand-offs between instruments, repositories, analytical processing, publishers, distributors, and archives. This model forms the basis for defining knowledge and skill requirements for specific actors in the processes required for data stewardship and the corresponding educational and training needs.

Federated and Cloud Enabled Resources for Data Management and Utilization

NASA Astrophysics Data System (ADS)

Rankin, R.; Gordon, M.; Potter, R. G.; Satchwill, B.

2011-12-01

The emergence of cloud computing over the past three years has led to a paradigm shift in how data can be managed, processed and made accessible. Building on the federated data management system offered through the Canadian Space Science Data Portal (www.cssdp.ca), we demonstrate how heterogeneous and geographically distributed data sets and modeling tools have been integrated to form a virtual data center and computational modeling platform that has services for data processing and visualization embedded within it. We also discuss positive and negative experiences in utilizing Eucalyptus and OpenStack cloud applications, and job scheduling facilitated by Condor and Star Cluster. We summarize our findings by demonstrating use of these technologies in the Cloud Enabled Space Weather Data Assimilation and Modeling Platform CESWP (www.ceswp.ca), which is funded through Canarie's (canarie.ca) Network Enabled Platforms program in Canada.

Computer networks for financial activity management, control and statistics of databases of economic administration at the Joint Institute for Nuclear Research

NASA Astrophysics Data System (ADS)

Tyupikova, T. V.; Samoilov, V. N.

2003-04-01

Modern information technologies urge natural sciences to further development. But it comes together with evaluation of infrastructures, to spotlight favorable conditions for the development of science and financial base in order to prove and protect legally new research. Any scientific development entails accounting and legal protection. In the report, we consider a new direction in software, organization and control of common databases on the example of the electronic document handling, which functions in some departments of the Joint Institute for Nuclear Research.

Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy-Aware Management in Green Cloud Computing

PubMed Central

Cotes-Ruiz, Iván Tomás; Prado, Rocío P.; García-Galán, Sebastián; Muñoz-Expósito, José Enrique; Ruiz-Reyes, Nicolás

2017-01-01

Nowadays, the growing computational capabilities of Cloud systems rely on the reduction of the consumed power of their data centers to make them sustainable and economically profitable. The efficient management of computing resources is at the heart of any energy-aware data center and of special relevance is the adaptation of its performance to workload. Intensive computing applications in diverse areas of science generate complex workload called workflows, whose successful management in terms of energy saving is still at its beginning. WorkflowSim is currently one of the most advanced simulators for research on workflows processing, offering advanced features such as task clustering and failure policies. In this work, an expected power-aware extension of WorkflowSim is presented. This new tool integrates a power model based on a computing-plus-communication design to allow the optimization of new management strategies in energy saving considering computing, reconfiguration and networks costs as well as quality of service, and it incorporates the preeminent strategy for on host energy saving: Dynamic Voltage Frequency Scaling (DVFS). The simulator is designed to be consistent in different real scenarios and to include a wide repertory of DVFS governors. Results showing the validity of the simulator in terms of resources utilization, frequency and voltage scaling, power, energy and time saving are presented. Also, results achieved by the intra-host DVFS strategy with different governors are compared to those of the data center using a recent and successful DVFS-based inter-host scheduling strategy as overlapped mechanism to the DVFS intra-host technique. PMID:28085932

Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy-Aware Management in Green Cloud Computing.

PubMed

Cotes-Ruiz, Iván Tomás; Prado, Rocío P; García-Galán, Sebastián; Muñoz-Expósito, José Enrique; Ruiz-Reyes, Nicolás

2017-01-01

Nowadays, the growing computational capabilities of Cloud systems rely on the reduction of the consumed power of their data centers to make them sustainable and economically profitable. The efficient management of computing resources is at the heart of any energy-aware data center and of special relevance is the adaptation of its performance to workload. Intensive computing applications in diverse areas of science generate complex workload called workflows, whose successful management in terms of energy saving is still at its beginning. WorkflowSim is currently one of the most advanced simulators for research on workflows processing, offering advanced features such as task clustering and failure policies. In this work, an expected power-aware extension of WorkflowSim is presented. This new tool integrates a power model based on a computing-plus-communication design to allow the optimization of new management strategies in energy saving considering computing, reconfiguration and networks costs as well as quality of service, and it incorporates the preeminent strategy for on host energy saving: Dynamic Voltage Frequency Scaling (DVFS). The simulator is designed to be consistent in different real scenarios and to include a wide repertory of DVFS governors. Results showing the validity of the simulator in terms of resources utilization, frequency and voltage scaling, power, energy and time saving are presented. Also, results achieved by the intra-host DVFS strategy with different governors are compared to those of the data center using a recent and successful DVFS-based inter-host scheduling strategy as overlapped mechanism to the DVFS intra-host technique.

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,…

MANTECH project book

NASA Astrophysics Data System (ADS)

The effective integration of processes, systems, and procedures used in the production of aerospace systems using computer technology is managed by the Integration Technology Division (MTI). Under its auspices are the Information Management Branch, which is actively involved with information management, information sciences and integration, and the Implementation Branch, whose technology areas include computer integrated manufacturing, engineering design, operations research, and material handling and assembly. The Integration Technology Division combines design, manufacturing, and supportability functions within the same organization. The Processing and Fabrication Division manages programs to improve structural and nonstructural materials processing and fabrication. Within this division, the Metals Branch directs the manufacturing methods program for metals and metal matrix composites processing and fabrication. The Nonmetals Branch directs the manufacturing methods programs, which include all manufacturing processes for producing and utilizing propellants, plastics, resins, fibers, composites, fluid elastomers, ceramics, glasses, and coatings. The objective of the Industrial Base Analysis Division is to act as focal point for the USAF industrial base program for productivity, responsiveness, and preparedness planning.

XPRESS: eXascale PRogramming Environment and System Software

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

Brightwell, Ron; Sterling, Thomas; Koniges, Alice

The XPRESS Project is one of four major projects of the DOE Office of Science Advanced Scientific Computing Research X-stack Program initiated in September, 2012. The purpose of XPRESS is to devise an innovative system software stack to enable practical and useful exascale computing around the end of the decade with near-term contributions to efficient and scalable operation of trans-Petaflops performance systems in the next two to three years; both for DOE mission-critical applications. To this end, XPRESS directly addresses critical challenges in computing of efficiency, scalability, and programmability through introspective methods of dynamic adaptive resource management and task scheduling.

Dealing with Y2K

NASA Astrophysics Data System (ADS)

Showstack, Randy

In 17 months, the ball drops in New York's Times Square to usher in a new millennium and new year ending in the digits 00. However, internal clocks in computers around the world may recognize the date as 1900 rather than 2000 if governments and businesses drop the ball in dealing with a simple computer design flaw that has ballooned into a complex management issue of correcting billions of lines of computer code worldwide.In a speech at the National Academy of Sciences in Washington, D.C, in July, U.S. President Bill Clinton proposed new legislation to make it easier for the private sector to collaborate in solving this problem.

Cumulative reports and publications through 31 December 1983

NASA Technical Reports Server (NTRS)

1983-01-01

All reports for the calendar years 1975 through December 1983 are listed by author. Since ICASE reports are intended to be preprints of articles for journals and conference proceedings, the published reference is included when available. Thirteen older journal and conference proceedings references are included as well as five additional reports by ICASE personnel. Major categories of research covered include: (1) numerical methods, with particular emphasis on the development and analysis of basic algorithms; (2) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; and (3) computer systems and software, especially vector and parallel computers, microcomputers, and data management.

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.

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

NASA Astrophysics Data System (ADS)

Vilotte, J. P.; Atkinson, M.; Spinuso, A.; Rietbrock, A.; Michelini, A.; Igel, H.; Frank, A.; Carpené, M.; Schwichtenberg, H.; Casarotti, E.; Filgueira, R.; Garth, T.; Germünd, A.; Klampanos, I.; Krause, A.; Krischer, L.; Leong, S. H.; Magnoni, F.; Matser, J.; Moguilny, G.

2015-12-01

Seismology addresses both fundamental problems in understanding the Earth's internal wave sources and structures and augmented societal applications, like earthquake and tsunami hazard assessment and risk mitigation; and puts a premium on open-data accessible by the Federated Digital Seismological Networks. The VERCE project, "Virtual Earthquake and seismology Research Community e-science environment in Europe", has initiated a virtual research environment to support complex orchestrated workflows combining state-of-art wave simulation codes and data analysis tools on distributed computing and data infrastructures (DCIs) along with multiple sources of observational data and new capabilities to combine simulation results with observational data. The VERCE Science Gateway provides a view of all the available resources, supporting collaboration with shared data and methods, with data access controls. The mapping to DCIs handles identity management, authority controls, transformations between representations and controls, and access to resources. The framework for computational science that provides simulation codes, like SPECFEM3D, democratizes their use by getting data from multiple sources, managing Earth models and meshes, distilling them as input data, and capturing results with meta-data. The dispel4py data-intensive framework allows for developing data-analysis applications using Python and the ObsPy library, which can be executed on different DCIs. A set of tools allows coupling with seismology and external data services. Provenance driven tools validate results and show relationships between data to facilitate method improvement. Lessons learned from VERCE training lead us to conclude that solid-Earth scientists could make significant progress by using VERCE e-science environment. VERCE has already contributed to the European Plate Observation System (EPOS), and is part of the EPOS implementation phase. Its cross-disciplinary capabilities are being extended for the EPOS implantation phase.

ICESat Science Investigator led Processing System (I-SIPS)

NASA Astrophysics Data System (ADS)

Bhardwaj, S.; Bay, J.; Brenner, A.; Dimarzio, J.; Hancock, D.; Sherman, M.

2003-12-01

The ICESat Science Investigator-led Processing System (I-SIPS) generates the GLAS standard data products. It consists of two main parts the Scheduling and Data Management System (SDMS) and the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software. The system has been operational since the successful launch of ICESat. It ingests data from the GLAS instrument, generates GLAS data products, and distributes them to the GLAS Science Computing Facility (SCF), the Instrument Support Facility (ISF) and the National Snow and Ice Data Center (NSIDC) ECS DAAC. The SDMS is the Planning, Scheduling and Data Management System that runs the GLAS Science Algorithm Software (GSAS). GSAS is based on the Algorithm Theoretical Basis Documents provided by the Science Team and is developed independently of SDMS. The SDMS provides the processing environment to plan jobs based on existing data, control job flow, data distribution, and archiving. The SDMS design is based on a mission-independent architecture that imposes few constraints on the science code thereby facilitating I-SIPS integration. I-SIPS currently works in an autonomous manner to ingest GLAS instrument data, distribute this data to the ISF, run the science processing algorithms to produce the GLAS standard products, reprocess data when new versions of science algorithms are released, and distributes the products to the SCF, ISF, and NSIDC. I-SIPS has a proven performance record, delivering the data to the SCF within hours after the initial instrument activation. The I-SIPS design philosophy gives this system a high potential for reuse in other science missions.

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!

Testimony to the House Science Space and Technology Committee.

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

Church, Michael Kenton; Tannenbaum, Benn

Chairman Smith, Ranking Member Johnson, and distinguished members of the Committee on Science, Space, and Technology, I thank you for the opportunity to testify today on the role of science, engineering, and research at Sandia National Laboratories, one of the nation’s premiere national labs and the nation’s largest Federally Funded Research and Development Center (FFRDC) laboratory. I am Dr. Susan Seestrom, Sandia’s Associate Laboratories Director for Advanced Science & Technology (AST) and Chief Research Officer (CRO). As CRO I am responsible for research strategy, Laboratory Directed Research & Development (LDRD), partnerships strategy, and technology transfer. As director and line managermore » for AST I manage capabilities and mission delivery across a variety of the physical and mathematical sciences and engineering disciplines, such as pulsed power, radiation effects, major environmental testing, high performance computing, and modeling and simulation.« less

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.

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

Multimedia Learning System and Its Effect on Self-Efficacy in Database Modeling and Design: An Exploratory Study

ERIC Educational Resources Information Center

Cheung, Waiman; Li, Eldon Y.; Yee, Lester W.

2003-01-01

Metadatabase modeling and design integrate process modeling and data modeling methodologies. Both are core topics in the information technology (IT) curriculum. Learning these topics has been an important pedagogical issue to the core studies for management information systems (MIS) and computer science (CSc) students. Unfortunately, the learning…

Hypermedia in the Plant Sciences: The Weed Key and Identification System/Videodisc.

ERIC Educational Resources Information Center

Ragan, Lawrence C.

1991-01-01

In cooperation with a university educational technology unit, an agronomy professor used hypercard and videodisk technology to develop a computer program for identification of 181 weed species based on user-selected characteristics. This solution was found during a search for a way to organize course content in a concise, manageable system. (MSE)

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…

Good enough practices in scientific computing.

PubMed

Wilson, Greg; Bryan, Jennifer; Cranston, Karen; Kitzes, Justin; Nederbragt, Lex; Teal, Tracy K

2017-06-01

Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1984-01-01

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.

New space sensor and mesoscale data analysis

NASA Technical Reports Server (NTRS)

Hickey, John S.

1987-01-01

The developed Earth Science and Application Division (ESAD) system/software provides the research scientist with the following capabilities: an extensive data base management capibility to convert various experiment data types into a standard format; and interactive analysis and display package (AVE80); an interactive imaging/color graphics capability utilizing the Apple III and IBM PC workstations integrated into the ESAD computer system; and local and remote smart-terminal capability which provides color video, graphics, and Laserjet output. Recommendations for updating and enhancing the performance of the ESAD computer system are listed.

EOS Laser Atmosphere Wind Sounder (LAWS) investigation

NASA Technical Reports Server (NTRS)

Emmitt, George D.

1991-01-01

The related activities of the contract are outlined for the first year. These include: (1) attend team member meetings; (2) support EOS Project with science related activities; (3) prepare and Execution Phase plan; and (4) support LAWS and EOSDIS related work. Attached to the report is an appendix, 'LAWS Algorithm Development and Evaluation Laboratory (LADEL)'. Also attached is a copy of a proposal to the NASA EOS for 'LAWS Sampling Strategies and Wind Computation Algorithms -- Storm-Top Divergence Studies. Volume I: Investigation and Technical Plan, Data Plan, Computer Facilities Plan, Management Plan.'

Multimission image processing and science data visualization

NASA Technical Reports Server (NTRS)

Green, William B.

1993-01-01

The Operational Science Analysis (OSA) Functional area supports science instrument data display, analysis, visualization and photo processing in support of flight operations of planetary spacecraft managed by the Jet Propulsion Laboratory (JPL). This paper describes the data products generated by the OSA functional area, and the current computer system used to generate these data products. The objectives on a system upgrade now in process are described. The design approach to development of the new system are reviewed, including use of the Unix operating system and X-Window display standards to provide platform independence, portability, and modularity within the new system, is reviewed. The new system should provide a modular and scaleable capability supporting a variety of future missions at JPL.

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…

Earth Science Data Grid System

NASA Astrophysics Data System (ADS)

Chi, Y.; Yang, R.; Kafatos, M.

2004-05-01

The Earth Science Data Grid System (ESDGS) is a software system in support of earth science data storage and access. It is built upon the Storage Resource Broker (SRB) data grid technology. We have developed a complete data grid system consistent of SRB server providing users uniform access to diverse storage resources in a heterogeneous computing environment and metadata catalog server (MCAT) managing the metadata associated with data set, users, and resources. We also develop the earth science application metadata; geospatial, temporal, and content-based indexing; and some other tools. In this paper, we will describe software architecture and components of the data grid system, and use a practical example in support of storage and access of rainfall data from the Tropical Rainfall Measuring Mission (TRMM) to illustrate its functionality and features.

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.

The role of gender on academic performance in STEM-related disciplines: Data from a tertiary institution.

PubMed

John, Temitope M; Badejo, Joke A; Popoola, Segun I; Omole, David O; Odukoya, Jonathan A; Ajayi, Priscilla O; Aboyade, Mary; Atayero, Aderemi A

2018-06-01

This data article presents data of academic performances of undergraduate students in Science, Technology, Engineering and Mathematics (STEM) disciplines in Covenant University, Nigeria. The data shows academic performances of Male and Female students who graduated from 2010 to 2014. The total population of samples in the observation is 3046 undergraduates mined from Biochemistry (BCH), Building technology (BLD), Computer Engineering (CEN), Chemical Engineering (CHE), Industrial Chemistry (CHM), Computer Science (CIS), Civil Engineering (CVE), Electrical and Electronics Engineering (EEE), Information and Communication Engineering (ICE), Mathematics (MAT), Microbiology (MCB), Mechanical Engineering (MCE), Management and Information System (MIS), Petroleum Engineering (PET), Industrial Physics-Electronics and IT Applications (PHYE), Industrial Physics-Applied Geophysics (PHYG) and Industrial Physics-Renewable Energy (PHYR). The detailed dataset is made available in form of a Microsoft Excel spreadsheet in the supplementary material of this article.

Design Analysis Kit for Optimization and Terascale Applications 6.0

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

2015-10-19

Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verificationmore » and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers.« less

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.

The StratusLab cloud distribution: Use-cases and support for scientific applications

NASA Astrophysics Data System (ADS)

Floros, E.

2012-04-01

The StratusLab project is integrating an open cloud software distribution that enables organizations to setup and provide their own private or public IaaS (Infrastructure as a Service) computing clouds. StratusLab distribution capitalizes on popular infrastructure virtualization solutions like KVM, the OpenNebula virtual machine manager, Claudia service manager and SlipStream deployment platform, which are further enhanced and expanded with additional components developed within the project. The StratusLab distribution covers the core aspects of a cloud IaaS architecture, namely Computing (life-cycle management of virtual machines), Storage, Appliance management and Networking. The resulting software stack provides a packaged turn-key solution for deploying cloud computing services. The cloud computing infrastructures deployed using StratusLab can support a wide range of scientific and business use cases. Grid computing has been the primary use case pursued by the project and for this reason the initial priority has been the support for the deployment and operation of fully virtualized production-level grid sites; a goal that has already been achieved by operating such a site as part of EGI's (European Grid Initiative) pan-european grid infrastructure. In this area the project is currently working to provide non-trivial capabilities like elastic and autonomic management of grid site resources. Although grid computing has been the motivating paradigm, StratusLab's cloud distribution can support a wider range of use cases. Towards this direction, we have developed and currently provide support for setting up general purpose computing solutions like Hadoop, MPI and Torque clusters. For what concerns scientific applications the project is collaborating closely with the Bioinformatics community in order to prepare VM appliances and deploy optimized services for bioinformatics applications. In a similar manner additional scientific disciplines like Earth Science can take advantage of StratusLab cloud solutions. Interested users are welcomed to join StratusLab's user community by getting access to the reference cloud services deployed by the project and offered to the public.

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…

When technology became language: the origins of the linguistic conception of computer programming, 1950-1960.

PubMed

Nofre, David; Priestley, Mark; Alberts, Gerard

2014-01-01

Language is one of the central metaphors around which the discipline of computer science has been built. The language metaphor entered modern computing as part of a cybernetic discourse, but during the second half of the 1950s acquired a more abstract meaning, closely related to the formal languages of logic and linguistics. The article argues that this transformation was related to the appearance of the commercial computer in the mid-1950s. Managers of computing installations and specialists on computer programming in academic computer centers, confronted with an increasing variety of machines, called for the creation of "common" or "universal languages" to enable the migration of computer code from machine to machine. Finally, the article shows how the idea of a universal language was a decisive step in the emergence of programming languages, in the recognition of computer programming as a proper field of knowledge, and eventually in the way we think of the computer.

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…

Cloud Pedagogy: Utilizing Web-Based Technologies for the Promotion of Social Constructivist Learning in Science Teacher Preparation Courses

NASA Astrophysics Data System (ADS)

Barak, Miri

2017-10-01

The new guidelines for science education emphasize the need to introduce computers and digital technologies as a means of enabling visualization and data collection and analysis. This requires science teachers to bring advanced technologies into the classroom and use them wisely. Hence, the goal of this study was twofold: to examine the application of web-based technologies in science teacher preparation courses and to examine pre-service teachers' perceptions of "cloud pedagogy"—an instructional framework that applies technologies for the promotion of social constructivist learning. The study included university teachers ( N = 48) and pre-service science teachers ( N = 73). Data were collected from an online survey, written reflections, and interviews. The findings indicated that university teachers use technologies mainly for information management and the distribution of learning materials and less for applying social constructivist pedagogy. University teachers expect their students (i.e., pre-service science teachers) to use digital tools in their future classroom to a greater extent than they themselves do. The findings also indicated that the "cloud pedagogy" was perceived as an appropriate instructional framework for contemporary science education. The application of the cloud pedagogy fosters four attributes: the ability to adapt to frequent changes and uncertain situations, the ability to collaborate and communicate in decentralized environments, the ability to generate data and manage it, and the ability to explore new venous.

Research and Technology 1997

NASA Technical Reports Server (NTRS)

1998-01-01

This report highlights the challenging work accomplished during fiscal year 1997 by Ames research scientists and engineers. The work is divided into accomplishments that support the goals of NASA s four Strategic Enterprises: Aeronautics and Space Transportation Technology, Space Science, Human Exploration and Development of Space (HEDS), and Earth Science. NASA Ames Research Center s research effort in the Space, Earth, and HEDS Enterprises is focused i n large part to support Ames lead role for Astrobiology, which broadly defined is the scientific study of the origin, distribution, and future of life in the universe. This NASA initiative in Astrobiology is a broad science effort embracing basic research, technology development, and flight missions. Ames contributions to the Space Science Enterprise are focused in the areas of exobiology, planetary systems, astrophysics, and space technology. Ames supports the Earth Science Enterprise by conducting research and by developing technology with the objective of expanding our knowledge of the Earth s atmosphere and ecosystems. Finallv, Ames supports the HEDS Enterprise by conducting research, managing spaceflight projects, and developing technologies. A key objective is to understand the phenomena surrounding the effects of gravity on living things. Ames has also heen designated the Agency s Center of Evcellence for Information Technnlogv. The three cornerstones of Information Technology research at Ames are automated reasoning, human-centered computing, and high performance computing and networking.

Data and Communications in Basic Energy Sciences: Creating a Pathway for Scientific Discovery

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

Nugent, Peter E.; Simonson, J. Michael

2011-10-24

This report is based on the Department of Energy (DOE) Workshop on “Data and Communications in Basic Energy Sciences: Creating a Pathway for Scientific Discovery” that was held at the Bethesda Marriott in Maryland on October 24-25, 2011. The workshop brought together leading researchers from the Basic Energy Sciences (BES) facilities and Advanced Scientific Computing Research (ASCR). The workshop was co-sponsored by these two Offices to identify opportunities and needs for data analysis, ownership, storage, mining, provenance and data transfer at light sources, neutron sources, microscopy centers and other facilities. Their charge was to identify current and anticipated issues inmore » the acquisition, analysis, communication and storage of experimental data that could impact the progress of scientific discovery, ascertain what knowledge, methods and tools are needed to mitigate present and projected shortcomings and to create the foundation for information exchanges and collaboration between ASCR and BES supported researchers and facilities. The workshop was organized in the context of the impending data tsunami that will be produced by DOE’s BES facilities. Current facilities, like SLAC National Accelerator Laboratory’s Linac Coherent Light Source, can produce up to 18 terabytes (TB) per day, while upgraded detectors at Lawrence Berkeley National Laboratory’s Advanced Light Source will generate ~10TB per hour. The expectation is that these rates will increase by over an order of magnitude in the coming decade. The urgency to develop new strategies and methods in order to stay ahead of this deluge and extract the most science from these facilities was recognized by all. The four focus areas addressed in this workshop were: Workflow Management - Experiment to Science: Identifying and managing the data path from experiment to publication. Theory and Algorithms: Recognizing the need for new tools for computation at scale, supporting large data sets and realistic theoretical models. Visualization and Analysis: Supporting near-real-time feedback for experiment optimization and new ways to extract and communicate critical information from large data sets. Data Processing and Management: Outlining needs in computational and communication approaches and infrastructure needed to handle unprecedented data volume and information content. It should be noted that almost all participants recognized that there were unlikely to be any turn-key solutions available due to the unique, diverse nature of the BES community, where research at adjacent beamlines at a given light source facility often span everything from biology to materials science to chemistry using scattering, imaging and/or spectroscopy. However, it was also noted that advances supported by other programs in data research, methodologies, and tool development could be implemented on reasonable time scales with modest effort. Adapting available standard file formats, robust workflows, and in-situ analysis tools for user facility needs could pay long-term dividends. Workshop participants assessed current requirements as well as future challenges and made the following recommendations in order to achieve the ultimate goal of enabling transformative science in current and future BES facilities: Theory and analysis components should be integrated seamlessly within experimental workflow. Develop new algorithms for data analysis based on common data formats and toolsets. Move analysis closer to experiment. Move the analysis closer to the experiment to enable real-time (in-situ) streaming capabilities, live visualization of the experiment and an increase of the overall experimental efficiency. Match data management access and capabilities with advancements in detectors and sources. Remove bottlenecks, provide interoperability across different facilities/beamlines and apply forefront mathematical techniques to more efficiently extract science from the experiments. This workshop report examines and reviews the status of several BES facilities and highlights the successes and shortcomings of the current data and communication pathways for scientific discovery. It then ascertains what methods and tools are needed to mitigate present and projected data bottlenecks to science over the next 10 years. The goal of this report is to create the foundation for information exchanges and collaborations among ASCR and BES supported researchers, the BES scientific user facilities, and ASCR computing and networking facilities. To jumpstart these activities, there was a strong desire to see a joint effort between ASCR and BES along the lines of the highly successful Scientific Discovery through Advanced Computing (SciDAC) program in which integrated teams of engineers, scientists and computer scientists were engaged to tackle a complete end-to-end workflow solution at one or more beamlines, to ascertain what challenges will need to be addressed in order to handle future increases in data« less

Computer Science | Classification | College of Engineering & Applied

Science.gov Websites

EMS 1011 profile photo Adrian Dumitrescu, Ph.D.ProfessorComputer Science(414) 229-4265Eng & Math @uwm.eduEng & Math Sciences 919 profile photo Hossein Hosseini, Ph.D.ProfessorComputer Science(414) 229 -5184hosseini@uwm.eduEng & Math Sciences 1091 profile photo Amol Mali, Ph.D.Associate ProfessorComputer

Computers in Science Education: Can They Go Far Enough? Have We Gone Too Far?

ERIC Educational Resources Information Center

Schrock, John Richard

1984-01-01

Indicates that although computers may churn out creative research, science is still dependent on science education, and that science education consists of increasing human experience. Also considers uses and misuses of computers in the science classroom, examining Edgar Dale's "cone of experience" related to laboratory computer and "extended…

Web portal on environmental sciences "ATMOS''

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Lykosov, V. N.; Fazliev, A. Z.

2006-06-01

The developed under INTAS grant web portal ATMOS (http://atmos.iao.ru and http://atmos.scert.ru) makes available to the international research community, environmental managers, and the interested public, a bilingual information source for the domain of Atmospheric Physics and Chemistry, and the related application domain of air quality assessment and management. It offers access to integrated thematic information, experimental data, analytical tools and models, case studies, and related information and educational resources compiled, structured, and edited by the partners into a coherent and consistent thematic information resource. While offering the usual components of a thematic site such as link collections, user group registration, discussion forum, news section etc., the site is distinguished by its scientific information services and tools: on-line models and analytical tools, and data collections and case studies together with tutorial material. The portal is organized as a set of interrelated scientific sites, which addressed basic branches of Atmospheric Sciences and Climate Modeling as well as the applied domains of Air Quality Assessment and Management, Modeling, and Environmental Impact Assessment. Each scientific site is open for external access information-computational system realized by means of Internet technologies. The main basic science topics are devoted to Atmospheric Chemistry, Atmospheric Spectroscopy and Radiation, Atmospheric Aerosols, Atmospheric Dynamics and Atmospheric Models, including climate models. The portal ATMOS reflects current tendency of Environmental Sciences transformation into exact (quantitative) sciences and is quite effective example of modern Information Technologies and Environmental Sciences integration. It makes the portal both an auxiliary instrument to support interdisciplinary projects of regional environment and extensive educational resource in this important domain.

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

NASA Technical Reports Server (NTRS)

Lynnes, Chris; Little, Mike; Huang, Thomas; Jacob, Joseph; Yang, Phil; Kuo, Kwo-Sen

2016-01-01

Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

NASA Astrophysics Data System (ADS)

Lynnes, C.; Little, M. M.; Huang, T.; Jacob, J. C.; Yang, C. P.; Kuo, K. S.

2016-12-01

Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based filesystems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.

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

BioSIGHT: Interactive Visualization Modules for Science Education

NASA Technical Reports Server (NTRS)

Wong, Wee Ling

1998-01-01

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

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.

Microgravity Science Glovebox

NASA Technical Reports Server (NTRS)

2001-01-01

Computer-generated drawing shows the relative scale and working space for the Microgravity Science Glovebox (MSG) being developed by NASA and the European Space Agency for science experiments aboard the International Space Station (ISS). The person at the glovebox repesents a 95th percentile American male. The MSG will be deployed first to the Destiny laboratory module and later will be moved to ESA's Columbus Attached Payload Module. Each module will be filled with International Standard Payload Racks (green) attached to standoff fittings (yellow) that hold the racks in position. Destiny is six racks in length. The MSG is being developed by the European Space Agency and NASA to provide a large working volume for hands-on experiments aboard the International Space Station. Scientists will use the MSG to carry out multidisciplinary studies in combustion science, fluid physics and materials science. The MSG is managed by NASA's Marshall Space Flight Center. (Credit: NASA/Marshall)

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science

NASA Technical Reports Server (NTRS)

1987-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period April, 1986 through September 30, 1986 is summarized.

78 FR 10180 - Annual Computational Science Symposium; Conference

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-13

...] Annual Computational Science Symposium; Conference AGENCY: Food and Drug Administration, HHS. ACTION... Computational Science Symposium.'' The purpose of the conference is to help the broader community align and share experiences to advance computational science. At the conference, which will bring together FDA...

Partner-built ecosystem science - The National Ocean Partnership Program as a builder of EBM Tools and Data

NASA Astrophysics Data System (ADS)

Hoffman, P. L.; Green, R. E.; Kohanowich, K. M.

2016-02-01

The National Ocean Partnership Program (NOPP) was created in 1997 by federal public law to identify "and carry out partnerships among federal agencies, academia, industry, and other members of the oceanographic scientific community in the areas of data, resources, education, and communications." Since that time, numerous federal agencies have pooled talent, funding, and scientific resources (e.g. ships, aircraft, remote sensors and computing capability) to address pressing ocean science needs which no one entity can manage alone. In this presentation, we will address the ways the National Ocean Policy identifies ecosystem-based management (EBM) as a foundation for providing sound science-based and adaptable management to maintain the health, productivity, and resilience of U.S. ocean, coastal, and Great Lakes ecosystems. Because EBM is an important approach for efficient and effective interagency, multi-jurisdictional, and cross-sectoral marine planning and management, ocean science partnerships such as those provided by NOPP create a pool of regionally-pertinent, nationally-available data from which EBM decision makers can draw to address critical management issues. Specifically, we will provide examples drawn from the last five years of funding to illustrate how the NOPP process works, how it is managed by a federal Interagency Working Group (IWG-OP), and how EBM practitioners can both partner with others through the NOPP and offer guidance on the implementation of projects beneficial to the regional needs of the EBM community. Projects to be discussed have been carried out under the following themes: Arctic Cumulative Impacts: Marine Arctic Ecosystem Study (MARES) - Ecosystem Dynamics and Monitoring of the Beaufort Sea: An Integrated Science Approach. Biodiversity Indicators: Demonstration of a U.S. Marine Biodiversity Observation Network (Marine BON) Long-Term Observations: Coordinated Regional Efforts That Further the U.S. Integrated Ocean Observing System (IOOS) Best Practices: Developing Environmental Protocols and Monitoring to Support Ocean Renewable Energy and Stewardship. We intend to leave the EBM community with a recognition that the NOPP already serves as a valuable partner source for science to inform EBM and to encourage participation in the process.

Partner-built ecosystem science - The National Ocean Partnership Program as a builder of EBM Tools and Data

NASA Astrophysics Data System (ADS)

Hoffman, P. L.; Green, R. E.; Kohanowich, K. M.

2016-12-01

The National Ocean Partnership Program (NOPP) was created in 1997 by federal public law to identify "and carry out partnerships among federal agencies, academia, industry, and other members of the oceanographic scientific community in the areas of data, resources, education, and communications." Since that time, numerous federal agencies have pooled talent, funding, and scientific resources (e.g. ships, aircraft, remote sensors and computing capability) to address pressing ocean science needs which no one entity can manage alone. In this presentation, we will address the ways the National Ocean Policy identifies ecosystem-based management (EBM) as a foundation for providing sound science-based and adaptable management to maintain the health, productivity, and resilience of U.S. ocean, coastal, and Great Lakes ecosystems. Because EBM is an important approach for efficient and effective interagency, multi-jurisdictional, and cross-sectoral marine planning and management, ocean science partnerships such as those provided by NOPP create a pool of regionally-pertinent, nationally-available data from which EBM decision makers can draw to address critical management issues. Specifically, we will provide examples drawn from the last five years of funding to illustrate how the NOPP process works, how it is managed by a federal Interagency Working Group (IWG-OP), and how EBM practitioners can both partner with others through the NOPP and offer guidance on the implementation of projects beneficial to the regional needs of the EBM community. Projects to be discussed have been carried out under the following themes: Arctic Cumulative Impacts: Marine Arctic Ecosystem Study (MARES) - Ecosystem Dynamics and Monitoring of the Beaufort Sea: An Integrated Science Approach. Biodiversity Indicators: Demonstration of a U.S. Marine Biodiversity Observation Network (Marine BON) Long-Term Observations: Coordinated Regional Efforts That Further the U.S. Integrated Ocean Observing System (IOOS) Best Practices: Developing Environmental Protocols and Monitoring to Support Ocean Renewable Energy and Stewardship. We intend to leave the EBM community with a recognition that the NOPP already serves as a valuable partner source for science to inform EBM and to encourage participation in the process.

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

Hules, John

This 1998 annual report from the National Scientific Energy Research Computing Center (NERSC) presents the year in review of the following categories: Computational Science; Computer Science and Applied Mathematics; and Systems and Services. Also presented are science highlights in the following categories: Basic Energy Sciences; Biological and Environmental Research; Fusion Energy Sciences; High Energy and Nuclear Physics; and Advanced Scientific Computing Research and Other Projects.

Development of an Innovative Interactive Virtual Classroom System for K-12 Education Using Google App Engine

ERIC Educational Resources Information Center

Mumba, Frackson; Zhu, Mengxia

2013-01-01

This paper presents a Simulation-based interactive Virtual ClassRoom web system (SVCR: www.vclasie.com) powered by the state-of-the-art cloud computing technology from Google SVCR integrates popular free open-source math, science and engineering simulations and provides functions such as secure user access control and management of courses,…

The Contribution of Human Factors in Military System Development: Methodological Considerations

DTIC Science & Technology

1980-07-01

Risk/Uncertainty Analysis - Project Scoring - Utility Scales - Relevance Tree Techniques (Reverse Factor Analysis) 2. Computer Simulation Simulation...effectiveness of mathematical models for R&D project selection. Management Science, April 1973, 18. 6-43 .1~ *.-. Souder, W.E. h scoring methodology for...per some interval PROFICIENCY test scores (written) RADIATION radiation effects aircrew performance on radiation environments REACTION TIME 1) (time

Computer Science and Technology: A Survey of Eleven Government-Developed Data Element Dictionary/Directory Systems.

ERIC Educational Resources Information Center

National Bureau of Standards (DOC), Washington, DC. Inst. for Computer Sciences and Technology.

This report presents the current state of the art of government developed Data Element Dictionary/Directory (DED/D) systems. DED/D's are software tools used for managing and controlling information and data. The introduction of the report includes a list of the government agency systems surveyed and a summary matrix presenting each system's…

Fuels planning: science synthesis and integration; environmental consequences fact sheet 10: The Understory Response Model

Treesearch

Steve Sutherland; Melanie Miller

2005-01-01

The Understory Response Model is a species-specific computer model that qualitatively predicts change in total species biomass for grasses, forbs, and shrubs after thinning, prescribed fire, or wildfire. The model examines the effect of fuels management on plant survivorship and reproduction. This fact sheet identifies the intended users and uses, required inputs, what...

Integrating citizen-science data with movement models to estimate the size of a migratory golden eagle population

Treesearch

Andrew J. Dennhardt; Adam E. Duerr; David Brandes; Todd E. Katzner

2015-01-01

Estimating population size is fundamental to conservation and management. Population size is typically estimated using survey data, computer models, or both. Some of the most extensive and often least expensive survey data are those collected by citizen-scientists. A challenge to citizen-scientists is that the vagility of many organisms can complicate data collection....

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

PubMed

Dinov, Ivo D

2016-01-01

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

Enduring Influence of Stereotypical Computer Science Role Models on Women's Academic Aspirations

ERIC Educational Resources Information Center

Cheryan, Sapna; Drury, Benjamin J.; Vichayapai, Marissa

2013-01-01

The current work examines whether a brief exposure to a computer science role model who fits stereotypes of computer scientists has a lasting influence on women's interest in the field. One-hundred undergraduate women who were not computer science majors met a female or male peer role model who embodied computer science stereotypes in appearance…

A Web of Resources for Introductory Computer Science.

ERIC Educational Resources Information Center

Rebelsky, Samuel A.

As the field of Computer Science has grown, the syllabus of the introductory Computer Science course has changed significantly. No longer is it a simple introduction to programming or a tutorial on computer concepts and applications. Rather, it has become a survey of the field of Computer Science, touching on a wide variety of topics from digital…

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science

NASA Technical Reports Server (NTRS)

1988-01-01

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period April l, 1988 through September 30, 1988.

Summary of research in applied mathematics, numerical analysis and computer science at the Institute for Computer Applications in Science and Engineering

NASA Technical Reports Server (NTRS)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science during the period October 1, 1983 through March 31, 1984 is summarized.

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science

NASA Technical Reports Server (NTRS)

1987-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period October 1, 1986 through March 31, 1987 is summarized.

High school computer science education paves the way for higher education: the Israeli case

NASA Astrophysics Data System (ADS)

Armoni, Michal; Gal-Ezer, Judith

2014-07-01

The gap between enrollments in higher education computing programs and the high-tech industry's demands is widely reported, and is especially prominent for women. Increasing the availability of computer science education in high school is one of the strategies suggested in order to address this gap. We look at the connection between exposure to computer science in high school and pursuing computing in higher education. We also examine the gender gap, in the context of high school computer science education. We show that in Israel, students who took the high-level computer science matriculation exam were more likely to pursue computing in higher education. Regarding the issue of gender, we will show that, in general, in Israel the difference between males and females who take computer science in high school is relatively small, and a larger, though still not very large difference exists only for the highest exam level. In addition, exposing females to high-level computer science in high school has more relative impact on pursuing higher education in computing.

The progress on time & frequency during the past 5 decades

NASA Astrophysics Data System (ADS)

Wang, Zheng-Ming

2002-06-01

The number and variety of applications using precise timing are astounding and increasing along with the new technology in communication, computer science, space science as well as in other fields. The world has evolved into the information age, and precise timing is at the heart of managing the flow of that information, which prompts the progress on precise timing itself rapidly. The development of time scales, UT1 determination, frequency standards, time transfer and the time dissemination for the past half century in the world and in China are described in this paper. The expectation in this field is discussed.

Maximizing reuse: Applying common sense and discipline

NASA Technical Reports Server (NTRS)

Waligora, Sharon; Langston, James

1992-01-01

Computer Sciences Corporation (CSC)/System Sciences Division (SSD) has maintained a long-term relationship with NASA/Goddard, providing satellite mission ground-support software and services for 23 years. As a partner in the Software Engineering Laboratory (SEL) since 1976, CSC has worked closely with NASA/Goddard to improve the software engineering process. This paper examines the evolution of reuse programs in this uniquely stable environment and formulates certain recommendations for developing reuse programs as a business strategy and as an integral part of production. It focuses on the management strategy and philosophy that have helped make reuse successful in this environment.

Complexity in Nature and Society: Complexity Management in the Age of Globalization

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. What are the laws of sociodynamics? Is there a socio-engineering of nonlinear problem solving? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the challenges of complexity in firms, institutions and other organizations? It is a main thesis of the talk that nature and society are basically governed by nonlinear and complex information dynamics. How computational is sociodynamics? What can we hope for social, economic and political problem solving in the age of globalization?.

Defining Computational Thinking for Mathematics and Science Classrooms

NASA Astrophysics Data System (ADS)

Weintrop, David; Beheshti, Elham; Horn, Michael; Orton, Kai; Jona, Kemi; Trouille, Laura; Wilensky, Uri

2016-02-01

Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include "computational thinking" as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.

NDE in aerospace-requirements for science, sensors and sense.

PubMed

Heyman, J S

1989-01-01

The complexity of modern NDE (nondestructive evaluation) arises from four main factors: quantitative measurement, science, physical models for computational analysis, realistic interfacing with engineering decisions, and direct access to management priorities. Recent advances in the four factors of NDE are addressed. Physical models of acoustic propagation are presented that have led to the development of measurement technologies advancing the ability to assure that materials and structures will perform a design. In addition, a brief discussion is given of current research for future mission needs such as smart structures that sense their own health. Such advances permit projects to integrate design for inspection into their plans, bringing NDE into engineering and management priorities. The measurement focus is on ultrasonics with generous case examples. Problem solutions highlighted include critical stress in fasteners, residual stress in steel, NDE laminography, and solid rocket motor NDE.

The Third Annual NASA Science Internet User Working Group Conference

NASA Technical Reports Server (NTRS)

Lev, Brian S. (Editor); Gary, J. Patrick (Editor)

1993-01-01

The NASA Science Internet (NSI) User Support Office (USO) sponsored the Third Annual NSI User Working Group (NSIUWG) Conference March 30 through April 3, 1992, in Greenbelt, MD. Approximately 130 NSI users attended to learn more about the NSI, hear from projects which use NSI, and receive updates about new networking technologies and services. This report contains material relevant to the conference; copies of the agenda, meeting summaries, presentations, and descriptions of exhibitors. Plenary sessions featured a variety of speakers, including NSI project management, scientists, and NSI user project managers whose projects and applications effectively use NSI, and notable citizens of the larger Internet community. The conference also included exhibits of advanced networking applications; tutorials on internetworking, computer security, and networking technologies; and user subgroup meetings on the future direction of the conference, networking, and user services and applications.

NDE in aerospace - Requirements for science, sensors and sense

NASA Technical Reports Server (NTRS)

Heyman, Joseph S.

1989-01-01

The complexity of modern nondestructive evaluation (NDE) arises from four main factors: quantitative measurement science, physical models for computational analysis, realistic interfacing with engineering decisions, and direct access to management priorities. Recent advances in the four factors of NDE are addressed. Physical models of acoustic propagation are presented that have led to the development of measurement technologies advancing the ability to assure that materials and structures will perform as designed. In addition, a brief discussion is given of current research for future mission needs such as smart structures that sense their own health. Such advances permit projects to integrate design for inspection into their plans, bringing NDE into engineering and management priorities. The measurement focus is on ultrasonics with generous case examples. Problem solutions highlighted include critical stress in fasteners, residual stress in steel, NDE laminography, and solid rocket motor NDE.

Computing with Beowulf

NASA Technical Reports Server (NTRS)

Cohen, Jarrett

1999-01-01

Parallel computers built out of mass-market parts are cost-effectively performing data processing and simulation tasks. The Supercomputing (now known as "SC") series of conferences celebrated its 10th anniversary last November. While vendors have come and gone, the dominant paradigm for tackling big problems still is a shared-resource, commercial supercomputer. Growing numbers of users needing a cheaper or dedicated-access alternative are building their own supercomputers out of mass-market parts. Such machines are generally called Beowulf-class systems after the 11th century epic. This modern-day Beowulf story began in 1994 at NASA's Goddard Space Flight Center. A laboratory for the Earth and space sciences, computing managers there threw down a gauntlet to develop a $50,000 gigaFLOPS workstation for processing satellite data sets. Soon, Thomas Sterling and Don Becker were working on the Beowulf concept at the University Space Research Association (USRA)-run Center of Excellence in Space Data and Information Sciences (CESDIS). Beowulf clusters mix three primary ingredients: commodity personal computers or workstations, low-cost Ethernet networks, and the open-source Linux operating system. One of the larger Beowulfs is Goddard's Highly-parallel Integrated Virtual Environment, or HIVE for short.

Here and now: the intersection of computational science, quantum-mechanical simulations, and materials science

NASA Astrophysics Data System (ADS)

Marzari, Nicola

The last 30 years have seen the steady and exhilarating development of powerful quantum-simulation engines for extended systems, dedicated to the solution of the Kohn-Sham equations of density-functional theory, often augmented by density-functional perturbation theory, many-body perturbation theory, time-dependent density-functional theory, dynamical mean-field theory, and quantum Monte Carlo. Their implementation on massively parallel architectures, now leveraging also GPUs and accelerators, has started a massive effort in the prediction from first principles of many or of complex materials properties, leading the way to the exascale through the combination of HPC (high-performance computing) and HTC (high-throughput computing). Challenges and opportunities abound: complementing hardware and software investments and design; developing the materials' informatics infrastructure needed to encode knowledge into complex protocols and workflows of calculations; managing and curating data; resisting the complacency that we have already reached the predictive accuracy needed for materials design, or a robust level of verification of the different quantum engines. In this talk I will provide an overview of these challenges, with the ultimate prize being the computational understanding, prediction, and design of properties and performance for novel or complex materials and devices.

Nicholas Brunhart-Lupo | NREL

Science.gov Websites

. Education Ph.D., Computer Science, Colorado School of Mines M.S., Computer Science, University of Queensland B.S., Computer Science, Colorado School of Mines Brunhart-Lupo Nicholas Brunhart-Lupo Computational Science Nicholas.Brunhart-Lupo@nrel.gov

The Need for Computer Science

ERIC Educational Resources Information Center

Margolis, Jane; Goode, Joanna; Bernier, David

2011-01-01

Broadening computer science learning to include more students is a crucial item on the United States' education agenda, these authors say. Although policymakers advocate more computer science expertise, computer science offerings in high schools are few--and actually shrinking. In addition, poorly resourced schools with a high percentage of…

Summary of research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science

NASA Technical Reports Server (NTRS)

1989-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period October 1, 1988 through March 31, 1989 is summarized.

The AIST Managed Cloud Environment

NASA Astrophysics Data System (ADS)

Cook, S.

2016-12-01

ESTO is currently in the process of developing and implementing the AIST Managed Cloud Environment (AMCE) to offer cloud computing services to ESTO-funded PIs to conduct their project research. AIST will provide projects access to a cloud computing framework that incorporates NASA security, technical, and financial standards, on which project can freely store, run, and process data. Currently, many projects led by research groups outside of NASA do not have the awareness of requirements or the resources to implement NASA standards into their research, which limits the likelihood of infusing the work into NASA applications. Offering this environment to PIs will allow them to conduct their project research using the many benefits of cloud computing. In addition to the well-known cost and time savings that it allows, it also provides scalability and flexibility. The AMCE will facilitate infusion and end user access by ensuring standardization and security. This approach will ultimately benefit ESTO, the science community, and the research, allowing the technology developments to have quicker and broader applications.

The AMCE (AIST Managed Cloud Environment)

NASA Astrophysics Data System (ADS)

Cook, S.

2017-12-01

ESTO has developed and implemented the AIST Managed Cloud Environment (AMCE) to offer cloud computing services to SMD-funded PIs to conduct their project research. AIST will provide projects access to a cloud computing framework that incorporates NASA security, technical, and financial standards, on which project can freely store, run, and process data. Currently, many projects led by research groups outside of NASA do not have the awareness of requirements or the resources to implement NASA standards into their research, which limits the likelihood of infusing the work into NASA applications. Offering this environment to PIs allows them to conduct their project research using the many benefits of cloud computing. In addition to the well-known cost and time savings that it allows, it also provides scalability and flexibility. The AMCE facilitates infusion and end user access by ensuring standardization and security. This approach will ultimately benefit ESTO, the science community, and the research, allowing the technology developments to have quicker and broader applications.

Alliance for Computational Science Collaboration HBCU Partnership at Fisk University. Final Report 2001

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

Collins, W. E.

2004-08-16

Computational Science plays a big role in research and development in mathematics, science, engineering and biomedical disciplines. The Alliance for Computational Science Collaboration (ACSC) has the goal of training African-American and other minority scientists in the computational science field for eventual employment with the Department of Energy (DOE). The involvements of Historically Black Colleges and Universities (HBCU) in the Alliance provide avenues for producing future DOE African-American scientists. Fisk University has been participating in this program through grants from the DOE. The DOE grant supported computational science activities at Fisk University. The research areas included energy related projects, distributed computing,more » visualization of scientific systems and biomedical computing. Students' involvement in computational science research included undergraduate summer research at Oak Ridge National Lab, on-campus research involving the participation of undergraduates, participation of undergraduate and faculty members in workshops, and mentoring of students. These activities enhanced research and education in computational science, thereby adding to Fisk University's spectrum of research and educational capabilities. Among the successes of the computational science activities are the acceptance of three undergraduate students to graduate schools with full scholarships beginning fall 2002 (one for master degree program and two for Doctoral degree program).« less

Procedural Quantum Programming

NASA Astrophysics Data System (ADS)

Ömer, Bernhard

2002-09-01

While classical computing science has developed a variety of methods and programming languages around the concept of the universal computer, the typical description of quantum algorithms still uses a purely mathematical, non-constructive formalism which makes no difference between a hydrogen atom and a quantum computer. This paper investigates, how the concept of procedural programming languages, the most widely used classical formalism for describing and implementing algorithms, can be adopted to the field of quantum computing, and how non-classical features like the reversibility of unitary transformations, the non-observability of quantum states or the lack of copy and erase operations can be reflected semantically. It introduces the key concepts of procedural quantum programming (hybrid target architecture, operator hierarchy, quantum data types, memory management, etc.) and presents the experimental language QCL, which implements these principles.

Curricular Influences on Female Afterschool Facilitators' Computer Science Interests and Career Choices

NASA Astrophysics Data System (ADS)

Koch, Melissa; Gorges, Torie

2016-10-01

Underrepresented populations such as women, African-Americans, and Latinos/as often come to STEM (science, technology, engineering, and mathematics) careers by less traditional paths than White and Asian males. To better understand how and why women might shift toward STEM, particularly computer science, careers, we investigated the education and career direction of afterschool facilitators, primarily women of color in their twenties and thirties, who taught Build IT, an afterschool computer science curriculum for middle school girls. Many of these women indicated that implementing Build IT had influenced their own interest in technology and computer science and in some cases had resulted in their intent to pursue technology and computer science education. We wanted to explore the role that teaching Build IT may have played in activating or reactivating interest in careers in computer science and to see whether in the years following implementation of Build IT, these women pursued STEM education and/or careers. We reached nine facilitators who implemented the program in 2011-12 or shortly after. Many indicated that while facilitating Build IT, they learned along with the participants, increasing their interest in and confidence with technology and computer science. Seven of the nine participants pursued further STEM or computer science learning or modified their career paths to include more of a STEM or computer science focus. Through interviews, we explored what aspects of Build IT influenced these facilitators' interest and confidence in STEM and when relevant their pursuit of technology and computer science education and careers.

Integrating Data Distribution and Data Assimilation Between the OOI CI and the NOAA DIF

NASA Astrophysics Data System (ADS)

Meisinger, M.; Arrott, M.; Clemesha, A.; Farcas, C.; Farcas, E.; Im, T.; Schofield, O.; Krueger, I.; Klacansky, I.; Orcutt, J.; Peach, C.; Chave, A.; Raymer, D.; Vernon, F.

2008-12-01

The Ocean Observatories Initiative (OOI) is an NSF funded program to establish the ocean observing infrastructure of the 21st century benefiting research and education. It is currently approaching final design and promises to deliver cyber and physical observatory infrastructure components as well as substantial core instrumentation to study environmental processes of the ocean at various scales, from coastal shelf-slope exchange processes to the deep ocean. The OOI's data distribution network lies at the heart of its cyber- infrastructure, which enables a multitude of science and education applications, ranging from data analysis, to processing, visualization and ontology supported query and mediation. In addition, it fundamentally supports a class of applications exploiting the knowledge gained from analyzing observational data for objective-driven ocean observing applications, such as automatically triggered response to episodic environmental events and interactive instrument tasking and control. The U.S. Department of Commerce through NOAA operates the Integrated Ocean Observing System (IOOS) providing continuous data in various formats, rates and scales on open oceans and coastal waters to scientists, managers, businesses, governments, and the public to support research and inform decision-making. The NOAA IOOS program initiated development of the Data Integration Framework (DIF) to improve management and delivery of an initial subset of ocean observations with the expectation of achieving improvements in a select set of NOAA's decision-support tools. Both OOI and NOAA through DIF collaborate on an effort to integrate the data distribution, access and analysis needs of both programs. We present details and early findings from this collaboration; one part of it is the development of a demonstrator combining web-based user access to oceanographic data through ERDDAP, efficient science data distribution, and scalable, self-healing deployment in a cloud computing environment. ERDDAP is a web-based front-end application integrating oceanographic data sources of various formats, for instance CDF data files as aggregated through NcML or presented using a THREDDS server. The OOI-designed data distribution network provides global traffic management and computational load balancing for observatory resources; it makes use of the OpenDAP Data Access Protocol (DAP) for efficient canonical science data distribution over the network. A cloud computing strategy is the basis for scalable, self-healing organization of an observatory's computing and storage resources, independent of the physical location and technical implementation of these resources.

INTEGRATION OF PANDA WORKLOAD MANAGEMENT SYSTEM WITH SUPERCOMPUTERS

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

De, K; Jha, S; Maeno, T

Abstract The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the funda- mental nature of matter and the basic forces that shape our universe, and were recently credited for the dis- covery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Datamore » Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data cen- ters are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Com- puting Facility (OLCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single- threaded workloads in parallel on Titan s multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accom- plishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility s infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less

On teaching computer ethics within a computer science department.

PubMed

Quinn, Michael J

2006-04-01

The author has surveyed a quarter of the accredited undergraduate computer science programs in the United States. More than half of these programs offer a 'social and ethical implications of computing' course taught by a computer science faculty member, and there appears to be a trend toward teaching ethics classes within computer science departments. Although the decision to create an 'in house' computer ethics course may sometimes be a pragmatic response to pressure from the accreditation agency, this paper argues that teaching ethics within a computer science department can provide students and faculty members with numerous benefits. The paper lists topics that can be covered in a computer ethics course and offers some practical suggestions for making the course successful.

Computational Science News | Computational Science | NREL

Science.gov Websites

-Cooled High-Performance Computing Technology at the ESIF February 28, 2018 NREL Launches New Website for High-Performance Computing System Users The National Renewable Energy Laboratory (NREL) Computational Science Center has launched a revamped website for users of the lab's high-performance computing (HPC

Stability Analysis of Finite Difference Approximations to Hyperbolic Systems, and Problems in Applied and Computational Matrix Theory

DTIC Science & Technology

1988-07-08

Marcus and C. Baczynski), Computer Science Press, Rockville, Maryland, 1986. 3. An Introduction to Pascal and Precalculus , Computer Science Press...Science Press, Rockville, Maryland, 1986. 35. An Introduction to Pascal and Precalculus , Computer Science Press, Rockville, Maryland, 1986. 36

Empirical Determination of Competence Areas to Computer Science Education

ERIC Educational Resources Information Center

Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia

2014-01-01

The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…

Factors Influencing Exemplary Science Teachers' Levels of Computer Use

ERIC Educational Resources Information Center

Hakverdi, Meral; Dana, Thomas M.; Swain, Colleen

2011-01-01

The purpose of this study was to examine 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…

Preparing Future Secondary Computer Science Educators

ERIC Educational Resources Information Center

Ajwa, Iyad

2007-01-01

Although nearly every college offers a major in computer science, many computer science teachers at the secondary level have received little formal training. This paper presents details of a project that could make a significant contribution to national efforts to improve computer science education by combining teacher education and professional…

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.

Building a digital library for the health sciences: information space complementing information place.

PubMed Central

Lucier, R E

1995-01-01

In 1990, the University of California, San Francisco, dedicated a new library to serve the faculty, staff, and students and to meet their academic information needs for several decades to come. Major environmental changes present new and additional information management challenges, which can effectively be handled only through the widespread use of computing and computing technologies. Over the next five years, a three-pronged strategy will be followed. We are refining the current physical, paper-based library through the continuous application of technology for modernization and functional improvement. At the same time, we have begun the planning, design, and implementation of a "free-standing" Digital Library of the Health Sciences, focusing on the innovative application of technology. To ensure complementarity and product integrity where the two libraries interface, we will look to technology to transform these separate entities into an eventual, integral whole. PMID:7581192

IAIMS development at Harvard Medical School.

PubMed Central

Barnett, G O; Greenes, R A; Zielstorff, R D

1988-01-01

The long-range goal of this IAIMS development project is to achieve an Integrated Academic Information Management System for the Harvard Medical School, the Francis A. Countway Library of Medicine, and Harvard's affiliated institutions and their respective libraries. An "opportunistic, incremental" approach to planning has been devised. The projects selected for the initial phase are to implement an increasingly powerful electronic communications network, to encourage the use of a variety of bibliographic and information access techniques, and to begin an ambitious program of faculty and student education in computer science and its applications to medical education, medical care, and research. In addition, we will explore means to promote better collaboration among the separate computer science units in the various schools and hospitals. We believe that our planning approach will have relevance to other educational institutions where lack of strong central organizational control prevents a "top-down" approach to planning. PMID:3416098

Life sciences Spacelab Mission Development test 3 (SMD 3) data management report

NASA Technical Reports Server (NTRS)

Moseley, E. C.

1977-01-01

Development of a permanent data system for SMD tests was studied that would simulate all elements of the shuttle onboard, telemetry, and ground data systems that are involved with spacelab operations. The onboard data system (ODS) and the ground data system (GDS) were utilized. The air-to-ground link was simulated by a hardwired computer-to-computer interface. A patch board system was used on board to select experiment inputs, and the downlink configuration from the ODS was changed by a crew keyboard entry to support each experiment. The ODS provided a CRT display of experiment parameters to enable the crew to monitor experiment performance. An onboard analog system, with recording capability, was installed to handle high rate data and to provide a backup to the digital system. The GDS accomplished engineering unit conversion and limit sensing, and provided realtime parameter display on CRT's in the science monitoring area and the test control area.

Catalog of US GeoData

USGS Publications Warehouse

,

1990-01-01

The development of geographic information systems (GIS) is a rapidly growing industry that supports natural resources, studies, land management, environmental analysis, and urban and transporation planning. The increasing use of computers for storing and analyzing earth science information has greatly expanded the demand for digital cartographic and geographic data. Digital cartography involves the collection, storage, processing, analysis, and display of map data with the aid of computers. The U.S. Geological Survey (USGS), the Nation's largest earth science research agency, through its National Mapping Program, has expanded digital cartography operations to include the collection of elevation, planimetric, land use and land cover, and geographic names information in digital form. This digital information is available on 9-track magnetic tapes and, in the case of 1:2,000,000-scale planimetric digital line graph data, in Compact Disc Read Only Memory (CD-ROM) format. Digital information can be used with all types of geographic and land information systems.

Enabling Wide-Scale Computer Science Education through Improved Automated Assessment Tools

NASA Astrophysics Data System (ADS)

Boe, Bryce A.

There is a proliferating demand for newly trained computer scientists as the number of computer science related jobs continues to increase. University programs will only be able to train enough new computer scientists to meet this demand when two things happen: when there are more primary and secondary school students interested in computer science, and when university departments have the resources to handle the resulting increase in enrollment. To meet these goals, significant effort is being made to both incorporate computational thinking into existing primary school education, and to support larger university computer science class sizes. We contribute to this effort through the creation and use of improved automated assessment tools. To enable wide-scale computer science education we do two things. First, we create a framework called Hairball to support the static analysis of Scratch programs targeted for fourth, fifth, and sixth grade students. Scratch is a popular building-block language utilized to pique interest in and teach the basics of computer science. We observe that Hairball allows for rapid curriculum alterations and thus contributes to wide-scale deployment of computer science curriculum. Second, we create a real-time feedback and assessment system utilized in university computer science classes to provide better feedback to students while reducing assessment time. Insights from our analysis of student submission data show that modifications to the system configuration support the way students learn and progress through course material, making it possible for instructors to tailor assignments to optimize learning in growing computer science classes.

The provision of feedback through computer-based technology to promote self-managed post-stroke rehabilitation in the home.

PubMed

Parker, Jack; Mawson, Susan; Mountain, Gail; Nasr, Nasrin; Davies, Richard; Zheng, Huiru

2014-11-01

Building on previous research findings, this article describes the development of the feedback interfaces for a Personalised Self-Managed Rehabilitation System (PSMrS) for home-based post-stroke rehabilitation using computer-based technology. Embedded within a realistic evaluative methodological approach, the development of the feedback interfaces for the PSMrS involved the incorporation of existing and emerging theories and a hybrid of health and social sciences research and user-centred design methods. User testing confirmed that extrinsic feedback for home-based post-stroke rehabilitation through computer-based technology needs to be personalisable, accurate, rewarding and measurable. In addition, user testing also confirmed the feasibility of using specific components of the PSMrS. A number of key elements are crucial for the development and potential utilisation of technology in what is an inevitable shift towards the use of innovative methods of delivering post-stroke rehabilitation. This includes the specific elements that are essential for the promotion of self-managed rehabilitation and rehabilitative behaviour change; the impact of the context on the mechanisms; and, importantly, the need for reliability and accuracy of the technology.

The Navajo Learning Network and the NASA Life Sciences/AFOSR Infrastructure Development Project

NASA Technical Reports Server (NTRS)

1999-01-01

The NSF-funded Navajo Learning Network project, with help from NASA Life Sciences and AFOSR, enabled Dine College to take a giant leap forward technologically - in a way that could never had been possible had these projects been managed separately. The combination of these and other efforts created a network of over 500 computers located at ten sites across the Navajo reservation. Additionally, the college was able to install a modern telephone system which shares network data, and purchase a new higher education management system. The NASA Life Sciences funds further allowed the college library system to go online and become available to the entire campus community. NSF, NASA and AFOSR are committed to improving minority access to higher education opportunities and promoting faculty development and undergraduate research through infrastructure support and development. This project has begun to address critical inequalities in access to science, mathematics, engineering and technology for Navajo students and educators. As a result, Navajo K-12 education has been bolstered and Dine College will therefore better prepare students to transfer successfully to four-year institutions. Due to the integration of the NSF and NASA/AFOSR components of the project, a unified project report is appropriate.

Data Management as a Cluster Middleware Centerpiece

NASA Technical Reports Server (NTRS)

Zero, Jose; McNab, David; Sawyer, William; Cheung, Samson; Duffy, Daniel; Rood, Richard; Webster, Phil; Palm, Nancy; Salmon, Ellen; Schardt, Tom

2004-01-01

Through earth and space modeling and the ongoing launches of satellites to gather data, NASA has become one of the largest producers of data in the world. These large data sets necessitated the creation of a Data Management System (DMS) to assist both the users and the administrators of the data. Halcyon Systems Inc. was contracted by the NASA Center for Computational Sciences (NCCS) to produce a Data Management System. The prototype of the DMS was produced by Halcyon Systems Inc. (Halcyon) for the Global Modeling and Assimilation Office (GMAO). The system, which was implemented and deployed within a relatively short period of time, has proven to be highly reliable and deployable. Following the prototype deployment, Halcyon was contacted by the NCCS to produce a production DMS version for their user community. The system is composed of several existing open source or government-sponsored components such as the San Diego Supercomputer Center s (SDSC) Storage Resource Broker (SRB), the Distributed Oceanographic Data System (DODS), and other components. Since Data Management is one of the foremost problems in cluster computing, the final package not only extends its capabilities as a Data Management System, but also to a cluster management system. This Cluster/Data Management System (CDMS) can be envisioned as the integration of existing packages.

Programmers, professors, and parasites: credit and co-authorship in computer science.

PubMed

Solomon, Justin

2009-12-01

This article presents an in-depth analysis of past and present publishing practices in academic computer science to suggest the establishment of a more consistent publishing standard. Historical precedent for academic publishing in computer science is established through the study of anecdotes as well as statistics collected from databases of published computer science papers. After examining these facts alongside information about analogous publishing situations and standards in other scientific fields, the article concludes with a list of basic principles that should be adopted in any computer science publishing standard. These principles would contribute to the reliability and scientific nature of academic publications in computer science and would allow for more straightforward discourse in future publications.

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA Technical Reports Server (NTRS)

Behnke, Jeanne; Mitchell, Andrew; Ramapriyan, Hampapuram

2018-01-01

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Integrating High-Throughput Parallel Processing Framework and Storage Area Network Concepts Into a Prototype Interactive Scientific Visualization Environment for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Smuga-Otto, M. J.; Garcia, R. K.; Knuteson, R. O.; Martin, G. D.; Flynn, B. M.; Hackel, D.

2006-12-01

The University of Wisconsin-Madison Space Science and Engineering Center (UW-SSEC) is developing tools to help scientists realize the potential of high spectral resolution instruments for atmospheric science. Upcoming satellite spectrometers like the Cross-track Infrared Sounder (CrIS), experimental instruments like the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and proposed instruments like the Hyperspectral Environmental Suite (HES) within the GOES-R project will present a challenge in the form of the overwhelmingly large amounts of continuously generated data. Current and near-future workstations will have neither the storage space nor computational capacity to cope with raw spectral data spanning more than a few minutes of observations from these instruments. Schemes exist for processing raw data from hyperspectral instruments currently in testing, that involve distributed computation across clusters. Data, which for an instrument like GIFTS can amount to over 1.5 Terabytes per day, is carefully managed on Storage Area Networks (SANs), with attention paid to proper maintenance of associated metadata. The UW-SSEC is preparing a demonstration integrating these back-end capabilities as part of a larger visualization framework, to assist scientists in developing new products from high spectral data, sourcing data volumes they could not otherwise manage. This demonstration focuses on managing storage so that only the data specifically needed for the desired product are pulled from the SAN, and on running computationally expensive intermediate processing on a back-end cluster, with the final product being sent to a visualization system on the scientist's workstation. Where possible, existing software and solutions are used to reduce cost of development. The heart of the computing component is the GIFTS Information Processing System (GIPS), developed at the UW- SSEC to allow distribution of processing tasks such as conversion of raw GIFTS interferograms into calibrated radiance spectra, and retrieving temperature and water vapor content atmospheric profiles from these spectra. The hope is that by demonstrating the capabilities afforded by a composite system like the one described here, scientists can be convinced to contribute further algorithms in support of this model of computing and visualization.

Increasing Diversity in Computer Science: Acknowledging, yet Moving Beyond, Gender

NASA Astrophysics Data System (ADS)

Larsen, Elizabeth A.; Stubbs, Margaret L.

Lack of diversity within the computer science field has, thus far, been examined most fully through the lens of gender. This article is based on a follow-on to Margolis and Fisher's (2002) study and includes interviews with 33 Carnegie Mellon University students from the undergraduate senior class of 2002 in the School of Computer Science. We found evidence of similarities among the perceptions of these women and men on definitions of computer science, explanations for the notoriously low proportion of women in the field, characterizations of a typical computer science student, impressions of recent curricular changes, a sense of the atmosphere/culture in the program, views of the Women@SCS campus organization, and suggestions for attracting and retaining well-rounded students in computer science. We conclude that efforts to increase diversity in the computer science field will benefit from a more broad-based approach that considers, but is not limited to, notions of gender difference.

Scalable data management, analysis and visualization (SDAV) Institute. Final Scientific/Technical Report

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

Geveci, Berk

The purpose of the SDAV institute is to provide tools and expertise in scientific data management, analysis, and visualization to DOE’s application scientists. Our goal is to actively work with application teams to assist them in achieving breakthrough science, and to provide technical solutions in the data management, analysis, and visualization regimes that are broadly used by the computational science community. Over the last 5 years members of our institute worked directly with application scientists and DOE leadership-class facilities to assist them by applying the best tools and technologies at our disposal. We also enhanced our tools based on inputmore » from scientists on their needs. Many of the applications we have been working with are based on connections with scientists established in previous years. However, we contacted additional scientists though our outreach activities, as well as engaging application teams running on leading DOE computing systems. Our approach is to employ an evolutionary development and deployment process: first considering the application of existing tools, followed by the customization necessary for each particular application, and then the deployment in real frameworks and infrastructures. The institute is organized into three areas, each with area leaders, who keep track of progress, engagement of application scientists, and results. The areas are: (1) Data Management, (2) Data Analysis, and (3) Visualization. Kitware has been involved in the Visualization area. This report covers Kitware’s contributions over the last 5 years (February 2012 – February 2017). For details on the work performed by the SDAV institute as a whole, please see the SDAV final report.« less

Challenges in Managing Trustworthy Large-scale Digital Science

NASA Astrophysics Data System (ADS)

Evans, B. J. K.

2017-12-01

The increased use of large-scale international digital science has opened a number of challenges for managing, handling, using and preserving scientific information. The large volumes of information are driven by three main categories - model outputs including coupled models and ensembles, data products that have been processing to a level of usability, and increasingly heuristically driven data analysis. These data products are increasingly the ones that are usable by the broad communities, and far in excess of the raw instruments data outputs. The data, software and workflows are then shared and replicated to allow broad use at an international scale, which places further demands of infrastructure to support how the information is managed reliably across distributed resources. Users necessarily rely on these underlying "black boxes" so that they are productive to produce new scientific outcomes. The software for these systems depend on computational infrastructure, software interconnected systems, and information capture systems. This ranges from the fundamentals of the reliability of the compute hardware, system software stacks and libraries, and the model software. Due to these complexities and capacity of the infrastructure, there is an increased emphasis of transparency of the approach and robustness of the methods over the full reproducibility. Furthermore, with large volume data management, it is increasingly difficult to store the historical versions of all model and derived data. Instead, the emphasis is on the ability to access the updated products and the reliability by which both previous outcomes are still relevant and can be updated for the new information. We will discuss these challenges and some of the approaches underway that are being used to address these issues.

Democratizing Computer Science

ERIC Educational Resources Information Center

Margolis, Jane; Goode, Joanna; Ryoo, Jean J.

2015-01-01

Computer science programs are too often identified with a narrow stratum of the student population, often white or Asian boys who have access to computers at home. But because computers play such a huge role in our world today, all students can benefit from the study of computer science and the opportunity to build skills related to computing. The…

Implementing an Affordable High-Performance Computing for Teaching-Oriented Computer Science Curriculum

ERIC Educational Resources Information Center

Abuzaghleh, Omar; Goldschmidt, Kathleen; Elleithy, Yasser; Lee, Jeongkyu

2013-01-01

With the advances in computing power, high-performance computing (HPC) platforms have had an impact on not only scientific research in advanced organizations but also computer science curriculum in the educational community. For example, multicore programming and parallel systems are highly desired courses in the computer science major. However,…

Computer Science and the Liberal Arts

ERIC Educational Resources Information Center

Shannon, Christine

2010-01-01

Computer science and the liberal arts have much to offer each other. Yet liberal arts colleges, in particular, have been slow to recognize the opportunity that the study of computer science provides for achieving the goals of a liberal education. After the precipitous drop in computer science enrollments during the first decade of this century,…

Marrying Content and Process in Computer Science Education

ERIC Educational Resources Information Center

Zendler, A.; Spannagel, C.; Klaudt, D.

2011-01-01

Constructivist approaches to computer science education emphasize that as well as knowledge, thinking skills and processes are involved in active knowledge construction. K-12 computer science curricula must not be based on fashions and trends, but on contents and processes that are observable in various domains of computer science, that can be…

Computing Whether She Belongs: Stereotypes Undermine Girls' Interest and Sense of Belonging in Computer Science

ERIC Educational Resources Information Center

Master, Allison; Cheryan, Sapna; Meltzoff, Andrew N.

2016-01-01

Computer science has one of the largest gender disparities in science, technology, engineering, and mathematics. An important reason for this disparity is that girls are less likely than boys to enroll in necessary "pipeline courses," such as introductory computer science. Two experiments investigated whether high-school girls' lower…

Approaching Gender Parity: Women in Computer Science at Afghanistan's Kabul University

ERIC Educational Resources Information Center

Plane, Jandelyn

2010-01-01

This study explores the representation of women in computer science at the tertiary level through data collected about undergraduate computer science education at Kabul University in Afghanistan. Previous studies have theorized reasons for underrepresentation of women in computer science, and while many of these reasons are indeed present in…

Some Hail 'Computational Science' as Biggest Advance Since Newton, Galileo.

ERIC Educational Resources Information Center

Turner, Judith Axler

1987-01-01

Computational science is defined as science done on a computer. A computer can serve as a laboratory for researchers who cannot experiment with their subjects, and as a calculator for those who otherwise might need centuries to solve some problems mathematically. The National Science Foundation's support of supercomputers is discussed. (MLW)

Infrastructure Systems for Advanced Computing in E-science applications

NASA Astrophysics Data System (ADS)

Terzo, Olivier

2013-04-01

In the e-science field are growing needs for having computing infrastructure more dynamic and customizable with a model of use "on demand" that follow the exact request in term of resources and storage capacities. The integration of grid and cloud infrastructure solutions allows us to offer services that can adapt the availability in terms of up scaling and downscaling resources. The main challenges for e-sciences domains will on implement infrastructure solutions for scientific computing that allow to adapt dynamically the demands of computing resources with a strong emphasis on optimizing the use of computing resources for reducing costs of investments. Instrumentation, data volumes, algorithms, analysis contribute to increase the complexity for applications who require high processing power and storage for a limited time and often exceeds the computational resources that equip the majority of laboratories, research Unit in an organization. Very often it is necessary to adapt or even tweak rethink tools, algorithms, and consolidate existing applications through a phase of reverse engineering in order to adapt them to a deployment on Cloud infrastructure. For example, in areas such as rainfall monitoring, meteorological analysis, Hydrometeorology, Climatology Bioinformatics Next Generation Sequencing, Computational Electromagnetic, Radio occultation, the complexity of the analysis raises several issues such as the processing time, the scheduling of tasks of processing, storage of results, a multi users environment. For these reasons, it is necessary to rethink the writing model of E-Science applications in order to be already adapted to exploit the potentiality of cloud computing services through the uses of IaaS, PaaS and SaaS layer. An other important focus is on create/use hybrid infrastructure typically a federation between Private and public cloud, in fact in this way when all resources owned by the organization are all used it will be easy with a federate cloud infrastructure to add some additional resources form the Public cloud for following the needs in term of computational and storage resources and release them where process are finished. Following the hybrid model, the scheduling approach is important for managing both cloud models. Thanks to this model infrastructure every time resources are available for additional request in term of IT capacities that can used "on demand" for a limited time without having to proceed to purchase additional servers.

African-American males in computer science---Examining the pipeline for clogs

NASA Astrophysics Data System (ADS)

Stone, Daryl Bryant

The literature on African-American males (AAM) begins with a statement to the effect that "Today young Black men are more likely to be killed or sent to prison than to graduate from college." Why are the numbers of African-American male college graduates decreasing? Why are those enrolled in college not majoring in the science, technology, engineering, and mathematics (STEM) disciplines? This research explored why African-American males are not filling the well-recognized industry need for Computer Scientist/Technologists by choosing college tracks to these careers. The literature on STEM disciplines focuses largely on women in STEM, as opposed to minorities, and within minorities, there is a noticeable research gap in addressing the needs and opportunities available to African-American males. The primary goal of this study was therefore to examine the computer science "pipeline" from the African-American male perspective. The method included a "Computer Science Degree Self-Efficacy Scale" be distributed to five groups of African-American male students, to include: (1) fourth graders, (2) eighth graders, (3) eleventh graders, (4) underclass undergraduate computer science majors, and (5) upperclass undergraduate computer science majors. In addition to a 30-question self-efficacy test, subjects from each group were asked to participate in a group discussion about "African-American males in computer science." The audio record of each group meeting provides qualitative data for the study. The hypotheses include the following: (1) There is no significant difference in "Computer Science Degree" self-efficacy between fourth and eighth graders. (2) There is no significant difference in "Computer Science Degree" self-efficacy between eighth and eleventh graders. (3) There is no significant difference in "Computer Science Degree" self-efficacy between eleventh graders and lower-level computer science majors. (4) There is no significant difference in "Computer Science Degree" self-efficacy between lower-level computer science majors and upper-level computer science majors. (5) There is no significant difference in "Computer Science Degree" self-efficacy between each of the five groups of students. Finally, the researcher selected African-American male students attending six primary schools, including the predominately African-American elementary, middle and high school that the researcher attended during his own academic career. Additionally, a racially mixed elementary, middle and high school was selected from the same county in Maryland. Bowie State University provided both the underclass and upperclass computer science majors surveyed in this study. Of the five hypotheses, the sample provided enough evidence to support the claim that there are significant differences in the "Computer Science Degree" self-efficacy between each of the five groups of students. ANOVA analysis by question and total self-efficacy scores provided more results of statistical significance. Additionally, factor analysis and review of the qualitative data provide more insightful results. Overall, the data suggest 'a clog' may exist in the middle school level and students attending racially mixed schools were more confident in their computer, math and science skills. African-American males admit to spending lots of time on social networking websites and emailing, but are 'dis-aware' of the skills and knowledge needed to study in the computing disciplines. The majority of the subjects knew little, if any, AAMs in the 'computing discipline pipeline'. The collegian African-American males, in this study, agree that computer programming is a difficult area and serves as a 'major clog in the pipeline'.

Preface: SciDAC 2005

NASA Astrophysics Data System (ADS)

Mezzacappa, Anthony

2005-01-01

On 26-30 June 2005 at the Grand Hyatt on Union Square in San Francisco several hundred computational scientists from around the world came together for what can certainly be described as a celebration of computational science. Scientists from the SciDAC Program and scientists from other agencies and nations were joined by applied mathematicians and computer scientists to highlight the many successes in the past year where computation has led to scientific discovery in a variety of fields: lattice quantum chromodynamics, accelerator modeling, chemistry, biology, materials science, Earth and climate science, astrophysics, and combustion and fusion energy science. Also highlighted were the advances in numerical methods and computer science, and the multidisciplinary collaboration cutting across science, mathematics, and computer science that enabled these discoveries. The SciDAC Program was conceived and funded by the US Department of Energy Office of Science. It is the Office of Science's premier computational science program founded on what is arguably the perfect formula: the priority and focus is science and scientific discovery, with the understanding that the full arsenal of `enabling technologies' in applied mathematics and computer science must be brought to bear if we are to have any hope of attacking and ultimately solving today's computational Grand Challenge problems. The SciDAC Program has been in existence for four years, and many of the computational scientists funded by this program will tell you that the program has given them the hope of addressing their scientific problems in full realism for the very first time. Many of these scientists will also tell you that SciDAC has also fundamentally changed the way they do computational science. We begin this volume with one of DOE's great traditions, and core missions: energy research. As we will see, computation has been seminal to the critical advances that have been made in this arena. Of course, to understand our world, whether it is to understand its very nature or to understand it so as to control it for practical application, will require explorations on all of its scales. Computational science has been no less an important tool in this arena than it has been in the arena of energy research. From explorations of quantum chromodynamics, the fundamental theory that describes how quarks make up the protons and neutrons of which we are composed, to explorations of the complex biomolecules that are the building blocks of life, to explorations of some of the most violent phenomena in our universe and of the Universe itself, computation has provided not only significant insight, but often the only means by which we have been able to explore these complex, multicomponent systems and by which we have been able to achieve scientific discovery and understanding. While our ultimate target remains scientific discovery, it certainly can be said that at a fundamental level the world is mathematical. Equations ultimately govern the evolution of the systems of interest to us, be they physical, chemical, or biological systems. The development and choice of discretizations of these underlying equations is often a critical deciding factor in whether or not one is able to model such systems stably, faithfully, and practically, and in turn, the algorithms to solve the resultant discrete equations are the complementary, critical ingredient in the recipe to model the natural world. The use of parallel computing platforms, especially at the TeraScale, and the trend toward even larger numbers of processors, continue to present significant challenges in the development and implementation of these algorithms. Computational scientists often speak of their `workflows'. A workflow, as the name suggests, is the sum total of all complex and interlocking tasks, from simulation set up, execution, and I/O, to visualization and scientific discovery, through which the advancement in our understanding of the natural world is realized. For the computational scientist, enabling such workflows presents myriad, signiflcant challenges, and it is computer scientists that are called upon at such times to address these challenges. Simulations are currently generating data at the staggering rate of tens of TeraBytes per simulation, over the course of days. In the next few years, these data generation rates are expected to climb exponentially to hundreds of TeraBytes per simulation, performed over the course of months. The output, management, movement, analysis, and visualization of these data will be our key to unlocking the scientific discoveries buried within the data. And there is no hope of generating such data to begin with, or of scientific discovery, without stable computing platforms and a sufficiently high and sustained performance of scientific applications codes on them. Thus, scientific discovery in the realm of computational science at the TeraScale and beyond will occur at the intersection of science, applied mathematics, and computer science. The SciDAC Program was constructed to mirror this reality, and the pages that follow are a testament to the efficacy of such an approach. We would like to acknowledge the individuals on whose talents and efforts the success of SciDAC 2005 was based. Special thanks go to Betsy Riley for her work on the SciDAC 2005 Web site and meeting agenda, for lining up our corporate sponsors, for coordinating all media communications, and for her efforts in processing the proceedings contributions, to Sherry Hempfling for coordinating the overall SciDAC 2005 meeting planning, for handling a significant share of its associated communications, and for coordinating with the ORNL Conference Center and Grand Hyatt, to Angela Harris for producing many of the documents and records on which our meeting planning was based and for her efforts in coordinating with ORNL Graphics Services, to Angie Beach of the ORNL Conference Center for her efforts in procurement and setting up and executing the contracts with the hotel, and to John Bui and John Smith for their superb wireless networking and A/V set up and support. We are grateful for the relentless efforts of all of these individuals, their remarkable talents, and for the joy of working with them during this past year. They were the cornerstones of SciDAC 2005. Thanks also go to Kymba A'Hearn and Patty Boyd for on-site registration, Brittany Hagen for administrative support, Bruce Johnston for netcast support, Tim Jones for help with the proceedings and Web site, Sherry Lamb for housing and registration, Cindy Lathum for Web site design, Carolyn Peters for on-site registration, and Dami Rich for graphic design. And we would like to express our appreciation to the Oak Ridge National Laboratory, especially Jeff Nichols, the Argonne National Laboratory, the Lawrence Berkeley National Laboratory, and to our corporate sponsors, Cray, IBM, Intel, and SGI, for their support. We would like to extend special thanks also to our plenary speakers, technical speakers, poster presenters, and panelists for all of their efforts on behalf of SciDAC 2005 and for their remarkable achievements and contributions. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas and Margaret Smith of Institute of Physics Publishing, who worked tirelessly in order to provide us with this finished volume within two months, which is nothing short of miraculous. Finally, we wish to express our heartfelt thanks to Michael Strayer, SciDAC Director, whose vision it was to focus SciDAC 2005 on scientific discovery, around which all of the excitement we experienced revolved, and to our DOE SciDAC program managers, especially Fred Johnson, for their support, input, and help throughout.

Girls in computer science: A female only introduction class in high school

NASA Astrophysics Data System (ADS)

Drobnis, Ann W.

This study examined the impact of an all girls' classroom environment in a high school introductory computer science class on the student's attitudes towards computer science and their thoughts on future involvement with computer science. It was determined that an all girls' introductory class could impact the declining female enrollment and female students' efficacy towards computer science. This research was conducted in a summer school program through a regional magnet school for science and technology which these students attend during the school year. Three different groupings of students were examined for the research: female students in an all girls' class, female students in mixed-gender classes and male students in mixed-gender classes. A survey, Attitudes about Computers and Computer Science (ACCS), was designed to obtain an understanding of the students' thoughts, preconceptions, attitude, knowledge of computer science, and future intentions around computer science, both in education and career. Students in all three groups were administered the ACCS prior to taking the class and upon completion of the class. In addition, students in the all girls' class wrote in a journal throughout the course, and some of those students were also interviewed upon completion of the course. The data was analyzed using quantitative and qualitative techniques. While there were no major differences found in the quantitative data, it was determined that girls in the all girls' class were truly excited by what they had learned and were more open to the idea of computer science being a part of their future.

Bringing computational science to the public.

PubMed

McDonagh, James L; Barker, Daniel; Alderson, Rosanna G

2016-01-01

The increasing use of computers in science allows for the scientific analyses of large datasets at an increasing pace. We provided examples and interactive demonstrations at Dundee Science Centre as part of the 2015 Women in Science festival, to present aspects of computational science to the general public. We used low-cost Raspberry Pi computers to provide hands on experience in computer programming and demonstrated the application of computers to biology. Computer games were used as a means to introduce computers to younger visitors. The success of the event was evaluated by voluntary feedback forms completed by visitors, in conjunction with our own self-evaluation. This work builds on the original work of the 4273π bioinformatics education program of Barker et al. (2013, BMC Bioinform. 14:243). 4273π provides open source education materials in bioinformatics. This work looks at the potential to adapt similar materials for public engagement events. It appears, at least in our small sample of visitors (n = 13), that basic computational science can be conveyed to people of all ages by means of interactive demonstrations. Children as young as five were able to successfully edit simple computer programs with supervision. This was, in many cases, their first experience of computer programming. The feedback is predominantly positive, showing strong support for improving computational science education, but also included suggestions for improvement. Our conclusions are necessarily preliminary. However, feedback forms suggest methods were generally well received among the participants; "Easy to follow. Clear explanation" and "Very easy. Demonstrators were very informative." Our event, held at a local Science Centre in Dundee, demonstrates that computer games and programming activities suitable for young children can be performed alongside a more specialised and applied introduction to computational science for older visitors.

Computer Science Research in Europe.

DTIC Science & Technology

1984-08-29

most attention, multi- database and its structure, and (3) the dependencies between databases Distributed Systems and multi- databases . Having...completed a multi- database Newcastle University, UK system for distributed data management, At the University of Newcastle the INRIA is now working on a real...communications re- INRIA quirements of distributed database A project called SIRIUS was estab- systems, protocols for checking the lished in 1977 at the

A Grid and Group Explanation of Students' and Instructors' Preferences in Computer Assisted Instruction: A Case Study of University Classrooms in Thailand

ERIC Educational Resources Information Center

Limwudhikraijirath, Aree

2009-01-01

This study was a case study which had three overlapping purposes. The first purpose was to use Douglas's typology to explain the educational culture of the Faculty of Management Sciences (FMS) at Prince of Songkla University (PSU) Hatyai, Songkhla, Thailand. The second purpose was to describe the students' and instructor's preferences about…

Report of the Army Science Board Summer Study on Installations 2025

DTIC Science & Technology

2009-12-01

stresses , beha- vioral health problems, and injuries associated with war. Transform: IMCOM is modernizing installation management processes, policies...well. For example, "Prediction is very difficult, especially about the future" (Niels Bohr). Others stress that the future will be a lot like the...34homogenization" Endangered species Continuous and ubiquitous of society Islanding computing Telecommuting Wireless proliferation across appliances

Visual Knowledge in Tactical Planning: Preliminary Knowledge Acquisition Phase 1 Technical Report

DTIC Science & Technology

1990-04-05

MANAGEMENT INFORMATION , COMMUNICATIONS, AND COMPUTER SCIENCES Visual Knowledge in Tactical Planning: Preliminary Knowledge Acquisition Phase I Technical...perceived provides information in multiple modalities and, in fact, we may rely on a non-verbal mode for much of our understanding of the situation...some tasks, almost all the pertinent information is provided via diagrams, maps, znd other illustrations. Visual Knowledge Visual experience forms a

Sensing and Efficient Inference for Identity Management

DTIC Science & Technology

2015-12-20

further studies in science, mathematics, engineering or technology fields: Student Metrics This section only applies to graduating undergraduates...of identification errors. Because of this, we believe that further study is warranted to make the Lagrangian formulation computationally more...conducted on the ISSIA data set [40], which is a 3 minutes soccer scene comprising 25 targets (11 from each team and 3 referees), recorded by 6 cameras

Guidance and Control Software,

DTIC Science & Technology

1980-05-01

commitments of function, cost, and schedule . The phrase "software engineering" was intended to contrast with the phrase "computer science" the latter aims...the software problems of cost, delivery schedule , and quality were gradually being recognized at the highest management levels. Thus, in a project... schedule dates. Although the analysis of software problems indicated that the entire software development process (figure 1) needed new methods, only

Computer Science and Telecommunications Board summary of activities

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

Blumenthal, M.S.

1992-03-27

The Computer Science and Telecommunications Board (CSTB) considers technical and policy issues pertaining to computer science, telecommunications, and associated technologies. CSTB actively disseminates the results of its completed projects to those in a position to help implement their recommendations or otherwise use their insights. It provides a forum for the exchange of information on computer science, computing technology, and telecommunications. This report discusses the major accomplishments of CSTB.

Hispanic women overcoming deterrents to computer science: A phenomenological study

NASA Astrophysics Data System (ADS)

Herling, Lourdes

The products of computer science are important to all aspects of society and are tools in the solution of the world's problems. It is, therefore, troubling that the United States faces a shortage in qualified graduates in computer science. The number of women and minorities in computer science is significantly lower than the percentage of the U.S. population which they represent. The overall enrollment in computer science programs has continued to decline with the enrollment of women declining at a higher rate than that of men. This study addressed three aspects of underrepresentation about which there has been little previous research: addressing computing disciplines specifically rather than embedding them within the STEM disciplines, what attracts women and minorities to computer science, and addressing the issues of race/ethnicity and gender in conjunction rather than in isolation. Since women of underrepresented ethnicities are more severely underrepresented than women in general, it is important to consider whether race and ethnicity play a role in addition to gender as has been suggested by previous research. Therefore, this study examined what attracted Hispanic women to computer science specifically. The study determines whether being subjected to multiple marginalizations---female and Hispanic---played a role in the experiences of Hispanic women currently in computer science. The study found five emergent themes within the experiences of Hispanic women in computer science. Encouragement and role models strongly influenced not only the participants' choice to major in the field, but to persist as well. Most of the participants experienced a negative atmosphere and feelings of not fitting in while in college and industry. The interdisciplinary nature of computer science was the most common aspect that attracted the participants to computer science. The aptitudes participants commonly believed are needed for success in computer science are the Twenty-First Century skills problem solving, creativity, and critical thinking. While not all the participants had experience with computers or programming prior to attending college, experience played a role in the self-confidence of those who did.

Research in applied mathematics, numerical analysis, and computer science

NASA Technical Reports Server (NTRS)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Dawn: A Simulation Model for Evaluating Costs and Tradeoffs of Big Data Science Architectures

NASA Astrophysics Data System (ADS)

Cinquini, L.; Crichton, D. J.; Braverman, A. J.; Kyo, L.; Fuchs, T.; Turmon, M.

2014-12-01

In many scientific disciplines, scientists and data managers are bracing for an upcoming deluge of big data volumes, which will increase the size of current data archives by a factor of 10-100 times. For example, the next Climate Model Inter-comparison Project (CMIP6) will generate a global archive of model output of approximately 10-20 Peta-bytes, while the upcoming next generation of NASA decadal Earth Observing instruments are expected to collect tens of Giga-bytes/day. In radio-astronomy, the Square Kilometre Array (SKA) will collect data in the Exa-bytes/day range, of which (after reduction and processing) around 1.5 Exa-bytes/year will be stored. The effective and timely processing of these enormous data streams will require the design of new data reduction and processing algorithms, new system architectures, and new techniques for evaluating computation uncertainty. Yet at present no general software tool or framework exists that will allow system architects to model their expected data processing workflow, and determine the network, computational and storage resources needed to prepare their data for scientific analysis. In order to fill this gap, at NASA/JPL we have been developing a preliminary model named DAWN (Distributed Analytics, Workflows and Numerics) for simulating arbitrary complex workflows composed of any number of data processing and movement tasks. The model can be configured with a representation of the problem at hand (the data volumes, the processing algorithms, the available computing and network resources), and is able to evaluate tradeoffs between different possible workflows based on several estimators: overall elapsed time, separate computation and transfer times, resulting uncertainty, and others. So far, we have been applying DAWN to analyze architectural solutions for 4 different use cases from distinct science disciplines: climate science, astronomy, hydrology and a generic cloud computing use case. This talk will present preliminary results and discuss how DAWN can be evolved into a powerful tool for designing system architectures for data intensive science.

Science-Driven Computing: NERSC's Plan for 2006-2010

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

Simon, Horst D.; Kramer, William T.C.; Bailey, David H.

NERSC has developed a five-year strategic plan focusing on three components: Science-Driven Systems, Science-Driven Services, and Science-Driven Analytics. (1) Science-Driven Systems: Balanced introduction of the best new technologies for complete computational systems--computing, storage, networking, visualization and analysis--coupled with the activities necessary to engage vendors in addressing the DOE computational science requirements in their future roadmaps. (2) Science-Driven Services: The entire range of support activities, from high-quality operations and user services to direct scientific support, that enable a broad range of scientists to effectively use NERSC systems in their research. NERSC will concentrate on resources needed to realize the promise ofmore » the new highly scalable architectures for scientific discovery in multidisciplinary computational science projects. (3) Science-Driven Analytics: The architectural and systems enhancements and services required to integrate NERSC's powerful computational and storage resources to provide scientists with new tools to effectively manipulate, visualize, and analyze the huge data sets derived from simulations and experiments.« less

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)

Gender Differences in the Use of Computers, Programming, and Peer Interactions in Computer Science Classrooms

ERIC Educational Resources Information Center

Stoilescu, Dorian; Egodawatte, Gunawardena

2010-01-01

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…

An Innovative Infrastructure with a Universal Geo-spatiotemporal Data Representation Supporting Cost-effective Integration of Diverse Earth Science Data

NASA Astrophysics Data System (ADS)

Kuo, K. S.; Rilee, M. L.

2017-12-01

Existing pathways for bringing together massive, diverse Earth Science datasets for integrated analyses burden end users with data packaging and management details irrelevant to their domain goals. The major data repositories focus on archival, discovery, and dissemination of products (files) in a standardized manner. End-users must download and then adapt these files using local resources and custom methods before analysis can proceed. This reduces scientific or other domain productivity, as scarce resources and expertise must be diverted to data processing. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme encoding geospatial and temporal information for organizing data on scalable computing/storage resources, minimizing expensive data transfers. STARE provides a compact representation that turns set-logic functions, e.g. conditional subsetting, into integer operations, that takes into account representative spatiotemporal resolutions of the data in the datasets, which is needed for data placement alignment of geo-spatiotemporally diverse data on massive parallel resources. Automating important scientific functions (e.g. regridding) and computational functions (e.g. data placement) allows scientists to focus on domain specific questions instead of expending their expertise on data processing. While STARE is not tied to any particular computing technology, we have used STARE for visualization and the SciDB array database to analyze Earth Science data on a 28-node compute cluster. STARE's automatic data placement and coupling of geometric and array indexing allows complicated data comparisons to be realized as straightforward database operations like "join." With STARE-enabled automation, SciDB+STARE provides a database interface, reducing costly data preparation, increasing the volume and variety of integrable data, and easing result sharing. Using SciDB+STARE as part of an integrated analysis infrastructure, we demonstrate the dramatic ease of combining diametrically different datasets, i.e. gridded (NMQ radar) vs. spacecraft swath (TRMM). SciDB+STARE is an important step towards a computational infrastructure for integrating and sharing diverse, complex Earth Science data and science products derived from them.

Quantum rendering

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco O.; Gomez, Richard B.; Uhlmann, Jeffrey K.

2003-08-01

In recent years, computer graphics has emerged as a critical component of the scientific and engineering process, and it is recognized as an important computer science research area. Computer graphics are extensively used for a variety of aerospace and defense training systems and by Hollywood's special effects companies. All these applications require the computer graphics systems to produce high quality renderings of extremely large data sets in short periods of time. Much research has been done in "classical computing" toward the development of efficient methods and techniques to reduce the rendering time required for large datasets. Quantum Computing's unique algorithmic features offer the possibility of speeding up some of the known rendering algorithms currently used in computer graphics. In this paper we discuss possible implementations of quantum rendering algorithms. In particular, we concentrate on the implementation of Grover's quantum search algorithm for Z-buffering, ray-tracing, radiosity, and scene management techniques. We also compare the theoretical performance between the classical and quantum versions of the algorithms.