Sample records for scientific computing service

  1. 76 FR 41234 - Advanced Scientific Computing Advisory Committee Charter Renewal

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-13

    ... Secretariat, General Services Administration, notice is hereby given that the Advanced Scientific Computing... advice and recommendations concerning the Advanced Scientific Computing program in response only to... Advanced Scientific Computing Research program and recommendations based thereon; --Advice on the computing...

  2. 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...

  3. DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

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

    Hey, Tony; Agarwal, Deborah; Borgman, Christine

    The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

  4. High-End Scientific Computing

    EPA Pesticide Factsheets

    EPA uses high-end scientific computing, geospatial services and remote sensing/imagery analysis to support EPA's mission. The Center for Environmental Computing (CEC) assists the Agency's program offices and regions to meet staff needs in these areas.

  5. A Computing Environment to Support Repeatable Scientific Big Data Experimentation of World-Wide Scientific Literature

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

    Schlicher, Bob G; Kulesz, James J; Abercrombie, Robert K

    A principal tenant of the scientific method is that experiments must be repeatable and relies on ceteris paribus (i.e., all other things being equal). As a scientific community, involved in data sciences, we must investigate ways to establish an environment where experiments can be repeated. We can no longer allude to where the data comes from, we must add rigor to the data collection and management process from which our analysis is conducted. This paper describes a computing environment to support repeatable scientific big data experimentation of world-wide scientific literature, and recommends a system that is housed at the Oakmore » Ridge National Laboratory in order to provide value to investigators from government agencies, academic institutions, and industry entities. The described computing environment also adheres to the recently instituted digital data management plan mandated by multiple US government agencies, which involves all stages of the digital data life cycle including capture, analysis, sharing, and preservation. It particularly focuses on the sharing and preservation of digital research data. The details of this computing environment are explained within the context of cloud services by the three layer classification of Software as a Service , Platform as a Service , and Infrastructure as a Service .« less

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

    ERIC Educational Resources Information Center

    Donna, Joel D.; Miller, Brant G.

    2013-01-01

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

  7. Auspice: Automatic Service Planning in Cloud/Grid Environments

    NASA Astrophysics Data System (ADS)

    Chiu, David; Agrawal, Gagan

    Recent scientific advances have fostered a mounting number of services and data sets available for utilization. These resources, though scattered across disparate locations, are often loosely coupled both semantically and operationally. This loosely coupled relationship implies the possibility of linking together operations and data sets to answer queries. This task, generally known as automatic service composition, therefore abstracts the process of complex scientific workflow planning from the user. We have been exploring a metadata-driven approach toward automatic service workflow composition, among other enabling mechanisms, in our system, Auspice: Automatic Service Planning in Cloud/Grid Environments. In this paper, we present a complete overview of our system's unique features and outlooks for future deployment as the Cloud computing paradigm becomes increasingly eminent in enabling scientific computing.

  8. 37 CFR 6.1 - International schedule of classes of goods and services.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...; entertainment; sporting and cultural activities. 42. Scientific and technological services and research and design relating thereto; industrial analysis and research services; design and development of computer...-operated); cutlery; side arms; razors. 9. Scientific, nautical, surveying, photographic, cinematographic...

  9. 37 CFR 6.1 - International schedule of classes of goods and services.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...; entertainment; sporting and cultural activities. 42. Scientific and technological services and research and design relating thereto; industrial analysis and research services; design and development of computer...); cutlery; side arms; razors. 9. Scientific, nautical, surveying, photographic, cinematographic, optical...

  10. 37 CFR 6.1 - International schedule of classes of goods and services.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...; entertainment; sporting and cultural activities. 42. Scientific and technological services and research and design relating thereto; industrial analysis and research services; design and development of computer...); cutlery; side arms; razors. 9. Scientific, nautical, surveying, photographic, cinematographic, optical...

  11. Grids, virtualization, and clouds at Fermilab

    DOE PAGES

    Timm, S.; Chadwick, K.; Garzoglio, G.; ...

    2014-06-11

    Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture andmore » the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.« less

  12. Grids, virtualization, and clouds at Fermilab

    NASA Astrophysics Data System (ADS)

    Timm, S.; Chadwick, K.; Garzoglio, G.; Noh, S.

    2014-06-01

    Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). This work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

  13. The Versatile Terminal.

    ERIC Educational Resources Information Center

    Evans, C. D.

    This paper describes the experiences of the industrial research laboratory of Kodak Ltd. in finding and providing a computer terminal most suited to its very varied requirements. These requirements include bibliographic and scientific data searching and access to a number of worldwide computing services for scientific computing work. The provision…

  14. iSERVO: Implementing the International Solid Earth Research Virtual Observatory by Integrating Computational Grid and Geographical Information Web Services

    NASA Astrophysics Data System (ADS)

    Aktas, Mehmet; Aydin, Galip; Donnellan, Andrea; Fox, Geoffrey; Granat, Robert; Grant, Lisa; Lyzenga, Greg; McLeod, Dennis; Pallickara, Shrideep; Parker, Jay; Pierce, Marlon; Rundle, John; Sayar, Ahmet; Tullis, Terry

    2006-12-01

    We describe the goals and initial implementation of the International Solid Earth Virtual Observatory (iSERVO). This system is built using a Web Services approach to Grid computing infrastructure and is accessed via a component-based Web portal user interface. We describe our implementations of services used by this system, including Geographical Information System (GIS)-based data grid services for accessing remote data repositories and job management services for controlling multiple execution steps. iSERVO is an example of a larger trend to build globally scalable scientific computing infrastructures using the Service Oriented Architecture approach. Adoption of this approach raises a number of research challenges in millisecond-latency message systems suitable for internet-enabled scientific applications. We review our research in these areas.

  15. Enabling Data Intensive Science through Service Oriented Science: Virtual Laboratories and Science Gateways

    NASA Astrophysics Data System (ADS)

    Lescinsky, D. T.; Wyborn, L. A.; Evans, B. J. K.; Allen, C.; Fraser, R.; Rankine, T.

    2014-12-01

    We present collaborative work on a generic, modular infrastructure for virtual laboratories (VLs, similar to science gateways) that combine online access to data, scientific code, and computing resources as services that support multiple data intensive scientific computing needs across a wide range of science disciplines. We are leveraging access to 10+ PB of earth science data on Lustre filesystems at Australia's National Computational Infrastructure (NCI) Research Data Storage Infrastructure (RDSI) node, co-located with NCI's 1.2 PFlop Raijin supercomputer and a 3000 CPU core research cloud. The development, maintenance and sustainability of VLs is best accomplished through modularisation and standardisation of interfaces between components. Our approach has been to break up tightly-coupled, specialised application packages into modules, with identified best techniques and algorithms repackaged either as data services or scientific tools that are accessible across domains. The data services can be used to manipulate, visualise and transform multiple data types whilst the scientific tools can be used in concert with multiple scientific codes. We are currently designing a scalable generic infrastructure that will handle scientific code as modularised services and thereby enable the rapid/easy deployment of new codes or versions of codes. The goal is to build open source libraries/collections of scientific tools, scripts and modelling codes that can be combined in specially designed deployments. Additional services in development include: provenance, publication of results, monitoring, workflow tools, etc. The generic VL infrastructure will be hosted at NCI, but can access alternative computing infrastructures (i.e., public/private cloud, HPC).The Virtual Geophysics Laboratory (VGL) was developed as a pilot project to demonstrate the underlying technology. This base is now being redesigned and generalised to develop a Virtual Hazards Impact and Risk Laboratory (VHIRL); any enhancements and new capabilities will be incorporated into a generic VL infrastructure. At same time, we are scoping seven new VLs and in the process, identifying other common components to prioritise and focus development.

  16. Templet Web: the use of volunteer computing approach in PaaS-style cloud

    NASA Astrophysics Data System (ADS)

    Vostokin, Sergei; Artamonov, Yuriy; Tsarev, Daniil

    2018-03-01

    This article presents the Templet Web cloud service. The service is designed for high-performance scientific computing automation. The use of high-performance technology is specifically required by new fields of computational science such as data mining, artificial intelligence, machine learning, and others. Cloud technologies provide a significant cost reduction for high-performance scientific applications. The main objectives to achieve this cost reduction in the Templet Web service design are: (a) the implementation of "on-demand" access; (b) source code deployment management; (c) high-performance computing programs development automation. The distinctive feature of the service is the approach mainly used in the field of volunteer computing, when a person who has access to a computer system delegates his access rights to the requesting user. We developed an access procedure, algorithms, and software for utilization of free computational resources of the academic cluster system in line with the methods of volunteer computing. The Templet Web service has been in operation for five years. It has been successfully used for conducting laboratory workshops and solving research problems, some of which are considered in this article. The article also provides an overview of research directions related to service development.

  17. 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.

  18. EUROPLANET-RI modelling service for the planetary science community: European Modelling and Data Analysis Facility (EMDAF)

    NASA Astrophysics Data System (ADS)

    Khodachenko, Maxim; Miller, Steven; Stoeckler, Robert; Topf, Florian

    2010-05-01

    Computational modeling and observational data analysis are two major aspects of the modern scientific research. Both appear nowadays under extensive development and application. Many of the scientific goals of planetary space missions require robust models of planetary objects and environments as well as efficient data analysis algorithms, to predict conditions for mission planning and to interpret the experimental data. Europe has great strength in these areas, but it is insufficiently coordinated; individual groups, models, techniques and algorithms need to be coupled and integrated. Existing level of scientific cooperation and the technical capabilities for operative communication, allow considerable progress in the development of a distributed international Research Infrastructure (RI) which is based on the existing in Europe computational modelling and data analysis centers, providing the scientific community with dedicated services in the fields of their computational and data analysis expertise. These services will appear as a product of the collaborative communication and joint research efforts of the numerical and data analysis experts together with planetary scientists. The major goal of the EUROPLANET-RI / EMDAF is to make computational models and data analysis algorithms associated with particular national RIs and teams, as well as their outputs, more readily available to their potential user community and more tailored to scientific user requirements, without compromising front-line specialized research on model and data analysis algorithms development and software implementation. This objective will be met through four keys subdivisions/tasks of EMAF: 1) an Interactive Catalogue of Planetary Models; 2) a Distributed Planetary Modelling Laboratory; 3) a Distributed Data Analysis Laboratory, and 4) enabling Models and Routines for High Performance Computing Grids. Using the advantages of the coordinated operation and efficient communication between the involved computational modelling, research and data analysis expert teams and their related research infrastructures, EMDAF will provide a 1) flexible, 2) scientific user oriented, 3) continuously developing and fast upgrading computational and data analysis service to support and intensify the European planetary scientific research. At the beginning EMDAF will create a set of demonstrators and operational tests of this service in key areas of European planetary science. This work will aim at the following objectives: (a) Development and implementation of tools for distant interactive communication between the planetary scientists and computing experts (including related RIs); (b) Development of standard routine packages, and user-friendly interfaces for operation of the existing numerical codes and data analysis algorithms by the specialized planetary scientists; (c) Development of a prototype of numerical modelling services "on demand" for space missions and planetary researchers; (d) Development of a prototype of data analysis services "on demand" for space missions and planetary researchers; (e) Development of a prototype of coordinated interconnected simulations of planetary phenomena and objects (global multi-model simulators); (f) Providing the demonstrators of a coordinated use of high performance computing facilities (super-computer networks), done in cooperation with European HPC Grid DEISA.

  19. Web Services Provide Access to SCEC Scientific Research Application Software

    NASA Astrophysics Data System (ADS)

    Gupta, N.; Gupta, V.; Okaya, D.; Kamb, L.; Maechling, P.

    2003-12-01

    Web services offer scientific communities a new paradigm for sharing research codes and communicating results. While there are formal technical definitions of what constitutes a web service, for a user community such as the Southern California Earthquake Center (SCEC), we may conceptually consider a web service to be functionality provided on-demand by an application which is run on a remote computer located elsewhere on the Internet. The value of a web service is that it can (1) run a scientific code without the user needing to install and learn the intricacies of running the code; (2) provide the technical framework which allows a user's computer to talk to the remote computer which performs the service; (3) provide the computational resources to run the code; and (4) bundle several analysis steps and provide the end results in digital or (post-processed) graphical form. Within an NSF-sponsored ITR project coordinated by SCEC, we are constructing web services using architectural protocols and programming languages (e.g., Java). However, because the SCEC community has a rich pool of scientific research software (written in traditional languages such as C and FORTRAN), we also emphasize making existing scientific codes available by constructing web service frameworks which wrap around and directly run these codes. In doing so we attempt to broaden community usage of these codes. Web service wrapping of a scientific code can be done using a "web servlet" construction or by using a SOAP/WSDL-based framework. This latter approach is widely adopted in IT circles although it is subject to rapid evolution. Our wrapping framework attempts to "honor" the original codes with as little modification as is possible. For versatility we identify three methods of user access: (A) a web-based GUI (written in HTML and/or Java applets); (B) a Linux/OSX/UNIX command line "initiator" utility (shell-scriptable); and (C) direct access from within any Java application (and with the correct API interface from within C++ and/or C/Fortran). This poster presentation will provide descriptions of the following selected web services and their origin as scientific application codes: 3D community velocity models for Southern California, geocoordinate conversions (latitude/longitude to UTM), execution of GMT graphical scripts, data format conversions (Gocad to Matlab format), and implementation of Seismic Hazard Analysis application programs that calculate hazard curve and hazard map data sets.

  20. Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

    ERIC Educational Resources Information Center

    Younge, Andrew J.

    2016-01-01

    With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

  1. 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

  2. Key Lessons in Building "Data Commons": The Open Science Data Cloud Ecosystem

    NASA Astrophysics Data System (ADS)

    Patterson, M.; Grossman, R.; Heath, A.; Murphy, M.; Wells, W.

    2015-12-01

    Cloud computing technology has created a shift around data and data analysis by allowing researchers to push computation to data as opposed to having to pull data to an individual researcher's computer. Subsequently, cloud-based resources can provide unique opportunities to capture computing environments used both to access raw data in its original form and also to create analysis products which may be the source of data for tables and figures presented in research publications. Since 2008, the Open Cloud Consortium (OCC) has operated the Open Science Data Cloud (OSDC), which provides scientific researchers with computational resources for storing, sharing, and analyzing large (terabyte and petabyte-scale) scientific datasets. OSDC has provided compute and storage services to over 750 researchers in a wide variety of data intensive disciplines. Recently, internal users have logged about 2 million core hours each month. The OSDC also serves the research community by colocating these resources with access to nearly a petabyte of public scientific datasets in a variety of fields also accessible for download externally by the public. In our experience operating these resources, researchers are well served by "data commons," meaning cyberinfrastructure that colocates data archives, computing, and storage infrastructure and supports essential tools and services for working with scientific data. In addition to the OSDC public data commons, the OCC operates a data commons in collaboration with NASA and is developing a data commons for NOAA datasets. As cloud-based infrastructures for distributing and computing over data become more pervasive, we ask, "What does it mean to publish data in a data commons?" Here we present the OSDC perspective and discuss several services that are key in architecting data commons, including digital identifier services.

  3. An Introductory Course on Service-Oriented Computing for High Schools

    ERIC Educational Resources Information Center

    Tsai, W. T.; Chen, Yinong; Cheng, Calvin; Sun, Xin; Bitter, Gary; White, Mary

    2008-01-01

    Service-Oriented Computing (SOC) is a new computing paradigm that has been adopted by major computer companies as well as government agencies such as the Department of Defense for mission-critical applications. SOC is being used for developing Web and electronic business applications, as well as robotics, gaming, and scientific applications. Yet,…

  4. Data Mining as a Service (DMaaS)

    NASA Astrophysics Data System (ADS)

    Tejedor, E.; Piparo, D.; Mascetti, L.; Moscicki, J.; Lamanna, M.; Mato, P.

    2016-10-01

    Data Mining as a Service (DMaaS) is a software and computing infrastructure that allows interactive mining of scientific data in the cloud. It allows users to run advanced data analyses by leveraging the widely adopted Jupyter notebook interface. Furthermore, the system makes it easier to share results and scientific code, access scientific software, produce tutorials and demonstrations as well as preserve the analyses of scientists. This paper describes how a first pilot of the DMaaS service is being deployed at CERN, starting from the notebook interface that has been fully integrated with the ROOT analysis framework, in order to provide all the tools for scientists to run their analyses. Additionally, we characterise the service backend, which combines a set of IT services such as user authentication, virtual computing infrastructure, mass storage, file synchronisation, development portals or batch systems. The added value acquired by the combination of the aforementioned categories of services is discussed, focusing on the opportunities offered by the CERNBox synchronisation service and its massive storage backend, EOS.

  5. Scientific Services on the Cloud

    NASA Astrophysics Data System (ADS)

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

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

  6. 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.

  7. Introduction to the LaRC central scientific computing complex

    NASA Technical Reports Server (NTRS)

    Shoosmith, John N.

    1993-01-01

    The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

  8. Ontology-Driven Discovery of Scientific Computational Entities

    ERIC Educational Resources Information Center

    Brazier, Pearl W.

    2010-01-01

    Many geoscientists use modern computational resources, such as software applications, Web services, scientific workflows and datasets that are readily available on the Internet, to support their research and many common tasks. These resources are often shared via human contact and sometimes stored in data portals; however, they are not necessarily…

  9. Software Framework for Peer Data-Management Services

    NASA Technical Reports Server (NTRS)

    Hughes, John; Hardman, Sean; Crichton, Daniel; Hyon, Jason; Kelly, Sean; Tran, Thuy

    2007-01-01

    Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-to-peer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

  10. Applications and Methods Utilizing the Simple Semantic Web Architecture and Protocol (SSWAP) for Bioinformatics Resource Discovery and Disparate Data and Service Integration

    USDA-ARS?s Scientific Manuscript database

    Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of scientific data between information resources difficu...

  11. Enabling NVM for Data-Intensive Scientific Services

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

    Carns, Philip; Jenkins, John; Seo, Sangmin

    Specialized, transient data services are playing an increasingly prominent role in data-intensive scientific computing. These services offer flexible, on-demand pairing of applications with storage hardware using semantics that are optimized for the problem domain. Concurrent with this trend, upcoming scientific computing and big data systems will be deployed with emerging NVM technology to achieve the highest possible price/productivity ratio. Clearly, therefore, we must develop techniques to facilitate the confluence of specialized data services and NVM technology. In this work we explore how to enable the composition of NVM resources within transient distributed services while still retaining their essential performance characteristics.more » Our approach involves eschewing the conventional distributed file system model and instead projecting NVM devices as remote microservices that leverage user-level threads, RPC services, RMA-enabled network transports, and persistent memory libraries in order to maximize performance. We describe a prototype system that incorporates these concepts, evaluate its performance for key workloads on an exemplar system, and discuss how the system can be leveraged as a component of future data-intensive architectures.« less

  12. [Earth and Space Sciences Project Services for NASA HPCC

    NASA Technical Reports Server (NTRS)

    Merkey, Phillip

    2002-01-01

    This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

  13. Opal web services for biomedical applications.

    PubMed

    Ren, Jingyuan; Williams, Nadya; Clementi, Luca; Krishnan, Sriram; Li, Wilfred W

    2010-07-01

    Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal's programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239,814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

  14. Software Reuse Methods to Improve Technological Infrastructure for e-Science

    NASA Technical Reports Server (NTRS)

    Marshall, James J.; Downs, Robert R.; Mattmann, Chris A.

    2011-01-01

    Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.

  15. Network and computing infrastructure for scientific applications in Georgia

    NASA Astrophysics Data System (ADS)

    Kvatadze, R.; Modebadze, Z.

    2016-09-01

    Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

  16. Understanding the Performance and Potential of Cloud Computing for Scientific Applications

    DOE PAGES

    Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

    2015-02-19

    In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

  17. Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

    Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

    In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

  18. Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

    NASA Astrophysics Data System (ADS)

    Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

    Grid computing has widely evolved over the past years, and its capabilities have found their way even into business products and are no longer relegated to scientific applications. Today, grid computing technology is not restricted to a set of specific grid open source or industrial products, but rather it is comprised of a set of capabilities virtually within any kind of software to create shared and highly collaborative production environments. These environments are focused on computational (workload) capabilities and the integration of information (data) into those computational capabilities. An active grid computing application field is the fully virtualization of scientific instruments in order to increase their availability and decrease operational and maintaining costs. Computational and information grids allow to manage real-world objects in a service-oriented way using industrial world-spread standards.

  19. DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

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

    Gerber, Richard; Allcock, William; Beggio, Chris

    2014-10-17

    U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at themore » DOE national laboratories. The report contains findings from that review.« less

  20. Amplify scientific discovery with artificial intelligence

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

    Gil, Yolanda; Greaves, Mark T.; Hendler, James

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

  1. Data Intensive Scientific Workflows on a Federated Cloud: CRADA Final Report

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

    Garzoglio, Gabriele

    The Fermilab Scientific Computing Division and the KISTI Global Science Experimental Data Hub Center have built a prototypical large-scale infrastructure to handle scientific workflows of stakeholders to run on multiple cloud resources. The demonstrations have been in the areas of (a) Data-Intensive Scientific Workflows on Federated Clouds, (b) Interoperability and Federation of Cloud Resources, and (c) Virtual Infrastructure Automation to enable On-Demand Services.

  2. 5 CFR 551.210 - Computer employees.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Computer employees. 551.210 Section 551.210 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY... solve complex business, scientific or engineering problems of the organization or the organization's...

  3. Cloud Computing with iPlant Atmosphere.

    PubMed

    McKay, Sheldon J; Skidmore, Edwin J; LaRose, Christopher J; Mercer, Andre W; Noutsos, Christos

    2013-10-15

    Cloud Computing refers to distributed computing platforms that use virtualization software to provide easy access to physical computing infrastructure and data storage, typically administered through a Web interface. Cloud-based computing provides access to powerful servers, with specific software and virtual hardware configurations, while eliminating the initial capital cost of expensive computers and reducing the ongoing operating costs of system administration, maintenance contracts, power consumption, and cooling. This eliminates a significant barrier to entry into bioinformatics and high-performance computing for many researchers. This is especially true of free or modestly priced cloud computing services. The iPlant Collaborative offers a free cloud computing service, Atmosphere, which allows users to easily create and use instances on virtual servers preconfigured for their analytical needs. Atmosphere is a self-service, on-demand platform for scientific computing. This unit demonstrates how to set up, access and use cloud computing in Atmosphere. Copyright © 2013 John Wiley & Sons, Inc.

  4. RELIABILITY, AVAILABILITY, AND SERVICEABILITY FOR PETASCALE HIGH-END COMPUTING AND BEYOND

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

    Chokchai "Box" Leangsuksun

    2011-05-31

    Our project is a multi-institutional research effort that adopts interplay of RELIABILITY, AVAILABILITY, and SERVICEABILITY (RAS) aspects for solving resilience issues in highend scientific computing in the next generation of supercomputers. results lie in the following tracks: Failure prediction in a large scale HPC; Investigate reliability issues and mitigation techniques including in GPGPU-based HPC system; HPC resilience runtime & tools.

  5. Computational Science in Armenia (Invited Talk)

    NASA Astrophysics Data System (ADS)

    Marandjian, H.; Shoukourian, Yu.

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

  6. The virtual machine (VM) scaler: an infrastructure manager supporting environmental modeling on IaaS clouds

    USDA-ARS?s Scientific Manuscript database

    Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific m...

  7. Integrating Grid Services into the Cray XT4 Environment

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

    NERSC; Cholia, Shreyas; Lin, Hwa-Chun Wendy

    2009-05-01

    The 38640 core Cray XT4"Franklin" system at the National Energy Research Scientific Computing Center (NERSC) is a massively parallel resource available to Department of Energy researchers that also provides on-demand grid computing to the Open Science Grid. The integration of grid services on Franklin presented various challenges, including fundamental differences between the interactive and compute nodes, a stripped down compute-node operating system without dynamic library support, a shared-root environment and idiosyncratic application launching. Inour work, we describe how we resolved these challenges on a running, general-purpose production system to provide on-demand compute, storage, accounting and monitoring services through generic gridmore » interfaces that mask the underlying system-specific details for the end user.« less

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

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

    Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

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

  9. Environmental Models as a Service: Enabling Interoperability through RESTful Endpoints and API Documentation

    EPA Science Inventory

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantag...

  10. Environmental Models as a Service: Enabling Interoperability through RESTful Endpoints and API Documentation.

    EPA Science Inventory

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantag...

  11. A Rich Metadata Filesystem for Scientific Data

    ERIC Educational Resources Information Center

    Bui, Hoang

    2012-01-01

    As scientific research becomes more data intensive, there is an increasing need for scalable, reliable, and high performance storage systems. Such data repositories must provide both data archival services and rich metadata, and cleanly integrate with large scale computing resources. ROARS is a hybrid approach to distributed storage that provides…

  12. Critical Field Experiments on Uses of Scientific and Technical Information.

    ERIC Educational Resources Information Center

    Rubenstein, Albert H.; And Others

    Research in the field of "information-seeking behavior of scientists and engineers" has been done on the behavior and preferences of researchers with respect to technical literature, computer-based information systems, and other scientific and technical information (STI) systems and services. The objectives of this project are: (1) to…

  13. Environmental Models as a Service: Enabling Interoperability through RESTful Endpoints and API Documentation (presentation)

    EPA Science Inventory

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantag...

  14. Tracking-Data-Conversion Tool

    NASA Technical Reports Server (NTRS)

    Flora-Adams, Dana; Makihara, Jeanne; Benenyan, Zabel; Berner, Jeff; Kwok, Andrew

    2007-01-01

    Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-topeer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

  15. Automatic Publishing of Library Bulletins.

    ERIC Educational Resources Information Center

    Inbal, Moshe

    1980-01-01

    Describes the use of a computer to publish library bulletins that list recent accessions of technical reports according to the subject classification scheme of NTIS/SRIM (National Technical Information Service's Scientific Reports in Microfiche). The codes file, the four computer program functions, and costs/economy are discussed. (JD)

  16. The INDIGO-Datacloud Authentication and Authorization Infrastructure

    NASA Astrophysics Data System (ADS)

    Ceccanti, A.; Hardt, M.; Wegh, B.; Millar, AP; Caberletti, M.; Vianello, E.; Licehammer, S.

    2017-10-01

    Contemporary distributed computing infrastructures (DCIs) are not easily and securely accessible by scientists. These computing environments are typically hard to integrate due to interoperability problems resulting from the use of different authentication mechanisms, identity negotiation protocols and access control policies. Such limitations have a big impact on the user experience making it hard for user communities to port and run their scientific applications on resources aggregated from multiple providers. The INDIGO-DataCloud project wants to provide the services and tools needed to enable a secure composition of resources from multiple providers in support of scientific applications. In order to do so, a common AAI architecture has to be defined that supports multiple authentication mechanisms, support delegated authorization across services and can be easily integrated in off-the-shelf software. In this contribution we introduce the INDIGO Authentication and Authorization Infrastructure, describing its main components and their status and how authentication, delegation and authorization flows are implemented across services.

  17. The QuakeSim Project: Web Services for Managing Geophysical Data and Applications

    NASA Astrophysics Data System (ADS)

    Pierce, Marlon E.; Fox, Geoffrey C.; Aktas, Mehmet S.; Aydin, Galip; Gadgil, Harshawardhan; Qi, Zhigang; Sayar, Ahmet

    2008-04-01

    We describe our distributed systems research efforts to build the “cyberinfrastructure” components that constitute a geophysical Grid, or more accurately, a Grid of Grids. Service-oriented computing principles are used to build a distributed infrastructure of Web accessible components for accessing data and scientific applications. Our data services fall into two major categories: Archival, database-backed services based around Geographical Information System (GIS) standards from the Open Geospatial Consortium, and streaming services that can be used to filter and route real-time data sources such as Global Positioning System data streams. Execution support services include application execution management services and services for transferring remote files. These data and execution service families are bound together through metadata information and workflow services for service orchestration. Users may access the system through the QuakeSim scientific Web portal, which is built using a portlet component approach.

  18. Mechanisation and Automation of Information Library Procedures in the USSR.

    ERIC Educational Resources Information Center

    Batenko, A. I.

    Scientific and technical libraries represent a fundamental link in a complex information storage and retrieval system. The handling of a large volume of scientific and technical data and provision of information library services requires the utilization of computing facilities and automation equipment, and was started in the Soviet Union on a…

  19. Science in the cloud (SIC): A use case in MRI connectomics

    PubMed Central

    Gorgolewski, Krzysztof J.; Kleissas, Dean; Roncal, William Gray; Litt, Brian; Wandell, Brian; Poldrack, Russel A.; Wiener, Martin; Vogelstein, R. Jacob; Burns, Randal

    2017-01-01

    Abstract Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called ‘science in the cloud’ (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. PMID:28327935

  20. Science in the cloud (SIC): A use case in MRI connectomics.

    PubMed

    Kiar, Gregory; Gorgolewski, Krzysztof J; Kleissas, Dean; Roncal, William Gray; Litt, Brian; Wandell, Brian; Poldrack, Russel A; Wiener, Martin; Vogelstein, R Jacob; Burns, Randal; Vogelstein, Joshua T

    2017-05-01

    Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called 'science in the cloud' (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. © The Author 2017. Published by Oxford University Press.

  1. French Plans for Fifth Generation Computer Systems.

    DTIC Science & Technology

    1984-12-07

    centrally man- French industry In electronics, compu- aged project in France that covers all ters, software, and services and to make the facets of the...Centre National of Japan’s Fifth Generation Project , the de Recherche Scientifique (CNRS) Cooper- French scientific and industrial com- ative Research...systems, man-computer The National Projects interaction, novel computer structures, The French Ministry of Research and knowledge-based computer systems

  2. An automated and integrated framework for dust storm detection based on ogc web processing services

    NASA Astrophysics Data System (ADS)

    Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

    2014-11-01

    Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

  3. Format Guide for Scientific and Technical Reports.

    DTIC Science & Technology

    1984-01-01

    supported by the discussion. Graphkic Services The Graphic Services Section (Code 2632) provides a variety of layout and design services. Camera-ready artwork...complex typography , elaborate graphic elements, extensive computer printouts, and other unusual materials that explain the project. With few exceptions...2630 Publications Branch Office 222/253 72379 S Publications Control Center 222/253 73508 Editorial 222/253 72782 Graphic Services 222/234 72756 73989

  4. 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.

  5. Cyberinfrastructure at IRIS: Challenges and Solutions Providing Integrated Data Access to EarthScope and Other Earth Science Data

    NASA Astrophysics Data System (ADS)

    Ahern, T. K.; Barga, R.; Casey, R.; Kamb, L.; Parastatidis, S.; Stromme, S.; Weertman, B. T.

    2008-12-01

    While mature methods of accessing seismic data from the IRIS DMC have existed for decades, the demands for improved interdisciplinary data integration call for new approaches. Talented software teams at the IRIS DMC, UNAVCO and the ICDP in Germany, have been developing web services for all EarthScope data including data from USArray, PBO and SAFOD. These web services are based upon SOAP and WSDL. The EarthScope Data Portal was the first external system to access data holdings from the IRIS DMC using Web Services. EarthScope will also draw more heavily upon products to aid in cross-disciplinary data reuse. A Product Management System called SPADE allows archive of and access to heterogeneous data products, presented as XML documents, at the IRIS DMC. Searchable metadata are extracted from the XML and enable powerful searches for products from EarthScope and other data sources. IRIS is teaming with the External Research Group at Microsoft Research to leverage a powerful Scientific Workflow Engine (Trident) and interact with the web services developed at centers such as IRIS to enable access to data services as well as computational services. We believe that this approach will allow web- based control of workflows and the invocation of computational services that transform data. This capability will greatly improve access to data across scientific disciplines. This presentation will review some of the traditional access tools as well as many of the newer approaches that use web services, scientific workflow to improve interdisciplinary data access.

  6. 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.

  7. 78 FR 64968 - Center for Scientific Review; Amended Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-30

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review; Amended Notice of Meeting Notice is hereby given of a change in the meeting of the Genomics, Computational Biology and Technology Study Section, October 16, 2013, 8:30 a.m. to October 17, 2013, 1:00 p.m., Avenue...

  8. Security Risks of Cloud Computing and Its Emergence as 5th Utility Service

    NASA Astrophysics Data System (ADS)

    Ahmad, Mushtaq

    Cloud Computing is being projected by the major cloud services provider IT companies such as IBM, Google, Yahoo, Amazon and others as fifth utility where clients will have access for processing those applications and or software projects which need very high processing speed for compute intensive and huge data capacity for scientific, engineering research problems and also e- business and data content network applications. These services for different types of clients are provided under DASM-Direct Access Service Management based on virtualization of hardware, software and very high bandwidth Internet (Web 2.0) communication. The paper reviews these developments for Cloud Computing and Hardware/Software configuration of the cloud paradigm. The paper also examines the vital aspects of security risks projected by IT Industry experts, cloud clients. The paper also highlights the cloud provider's response to cloud security risks.

  9. SNS programming environment user's guide

    NASA Technical Reports Server (NTRS)

    Tennille, Geoffrey M.; Howser, Lona M.; Humes, D. Creig; Cronin, Catherine K.; Bowen, John T.; Drozdowski, Joseph M.; Utley, Judith A.; Flynn, Theresa M.; Austin, Brenda A.

    1992-01-01

    The computing environment is briefly described for the Supercomputing Network Subsystem (SNS) of the Central Scientific Computing Complex of NASA Langley. The major SNS computers are a CRAY-2, a CRAY Y-MP, a CONVEX C-210, and a CONVEX C-220. The software is described that is common to all of these computers, including: the UNIX operating system, computer graphics, networking utilities, mass storage, and mathematical libraries. Also described is file management, validation, SNS configuration, documentation, and customer services.

  10. The role of dedicated data computing centers in the age of cloud computing

    NASA Astrophysics Data System (ADS)

    Caramarcu, Costin; Hollowell, Christopher; Strecker-Kellogg, William; Wong, Antonio; Zaytsev, Alexandr

    2017-10-01

    Brookhaven National Laboratory (BNL) anticipates significant growth in scientific programs with large computing and data storage needs in the near future and has recently reorganized support for scientific computing to meet these needs. A key component is the enhanced role of the RHIC-ATLAS Computing Facility (RACF) in support of high-throughput and high-performance computing (HTC and HPC) at BNL. This presentation discusses the evolving role of the RACF at BNL, in light of its growing portfolio of responsibilities and its increasing integration with cloud (academic and for-profit) computing activities. We also discuss BNL’s plan to build a new computing center to support the new responsibilities of the RACF and present a summary of the cost benefit analysis done, including the types of computing activities that benefit most from a local data center vs. cloud computing. This analysis is partly based on an updated cost comparison of Amazon EC2 computing services and the RACF, which was originally conducted in 2012.

  11. Theory of Constraints for Services: Past, Present, and Future

    NASA Astrophysics Data System (ADS)

    Ricketts, John A.

    Theory of constraints (TOC) is a thinking process and a set of management applications based on principles that run counter to conventional wisdom. TOC is best known in the manufacturing and distribution sectors where it originated. Awareness is growing in some service sectors, such as Health Care. And it's been adopted in some high-tech industries, such as Computer Software. Until recently, however, TOC was barely known in the Professional, Scientific, and Technical Services (PSTS) sector. Professional services include law, accounting, and consulting. Scientific services include research and development. And Technical services include development, operation, and support of various technologies. The main reason TOC took longer to reach PSTS is it's much harder to apply TOC principles when services are highly customized. Nevertheless, with the management applications described in this chapter, TOC has been successfully adapted for PSTS. Those applications cover management of resources, projects, processes, and finances.

  12. Interactive Forecasting with the National Weather Service River Forecast System

    NASA Technical Reports Server (NTRS)

    Smith, George F.; Page, Donna

    1993-01-01

    The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

  13. 76 FR 14323 - Small Business Size Standards: Professional, Scientific and Technical Services

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-16

    ... SBA to establish a common size standard for the Computer Systems Design and Related Services....0 12.0 Testing Laboratories........ 10.0 5.0 $10.0 $10.0 541410 0.8 5.1 0.2 0.557 5.0 7.0 Interior Design Services.... 5.0 5.0 5.0 $5.0 541420 1.3 9.5 0.714 5.0 7.0 Industrial Design Services.. 5.0 5.0 $5...

  14. The Virtual Geophysics Laboratory (VGL): Scientific Workflows Operating Across Organizations and Across Infrastructures

    NASA Astrophysics Data System (ADS)

    Cox, S. J.; Wyborn, L. A.; Fraser, R.; Rankine, T.; Woodcock, R.; Vote, J.; Evans, B.

    2012-12-01

    The Virtual Geophysics Laboratory (VGL) is web portal that provides geoscientists with an integrated online environment that: seamlessly accesses geophysical and geoscience data services from the AuScope national geoscience information infrastructure; loosely couples these data to a variety of gesocience software tools; and provides large scale processing facilities via cloud computing. VGL is a collaboration between CSIRO, Geoscience Australia, National Computational Infrastructure, Monash University, Australian National University and the University of Queensland. The VGL provides a distributed system whereby a user can enter an online virtual laboratory to seamlessly connect to OGC web services for geoscience data. The data is supplied in open standards formats using international standards like GeoSciML. A VGL user uses a web mapping interface to discover and filter the data sources using spatial and attribute filters to define a subset. Once the data is selected the user is not required to download the data. VGL collates the service query information for later in the processing workflow where it will be staged directly to the computing facilities. The combination of deferring data download and access to Cloud computing enables VGL users to access their data at higher resolutions and to undertake larger scale inversions, more complex models and simulations than their own local computing facilities might allow. Inside the Virtual Geophysics Laboratory, the user has access to a library of existing models, complete with exemplar workflows for specific scientific problems based on those models. For example, the user can load a geological model published by Geoscience Australia, apply a basic deformation workflow provided by a CSIRO scientist, and have it run in a scientific code from Monash. Finally the user can publish these results to share with a colleague or cite in a paper. This opens new opportunities for access and collaboration as all the resources (models, code, data, processing) are shared in the one virtual laboratory. VGL provides end users with access to an intuitive, user-centered interface that leverages cloud storage and cloud and cluster processing from both the research communities and commercial suppliers (e.g. Amazon). As the underlying data and information services are agnostic of the scientific domain, they can support many other data types. This fundamental characteristic results in a highly reusable virtual laboratory infrastructure that could also be used for example natural hazards, satellite processing, soil geochemistry, climate modeling, agriculture crop modeling.

  15. Scientific Library Offers New Training Options | Poster

    Cancer.gov

    The Scientific Library is expanding its current training opportunities by offering webinars, allowing employees to take advantage of trainings from the comfort of their own offices. Due to the nature of their work, some employees find it inconvenient to attend in-person training classes; others simply prefer to use their own computers. The Scientific Library has been experimenting with webinar sessions since 2016 and expanded the service in 2017. Now, due to the popularity of webinars, it plans to offer even more webinar training sessions.

  16. Educational and Scientific Applications of Climate Model Diagnostic Analyzer

    NASA Astrophysics Data System (ADS)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

    2016-12-01

    Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of Two Variables, and the datasets used are NCAR CAM total cloud fraction and MODIS total cloud fraction. The scientific highlight of the use case is that the CAM5 model overall does a fairly decent job at simulating total cloud cover, though simulates too few clouds especially near and offshore of the eastern ocean basins where low clouds are dominant.

  17. 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

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

    Garzoglio, Gabriele

    The Fermilab Grid and Cloud Computing Department and the KISTI Global Science experimental Data hub Center are working on a multi-year Collaborative Research and Development Agreement.With the knowledge developed in the first year on how to provision and manage a federation of virtual machines through Cloud management systems. In this second year, we expanded the work on provisioning and federation, increasing both scale and diversity of solutions, and we started to build on-demand services on the established fabric, introducing the paradigm of Platform as a Service to assist with the execution of scientific workflows. We have enabled scientific workflows ofmore » stakeholders to run on multiple cloud resources at the scale of 1,000 concurrent machines. The demonstrations have been in the areas of (a) Virtual Infrastructure Automation and Provisioning, (b) Interoperability and Federation of Cloud Resources, and (c) On-demand Services for ScientificWorkflows.« less

  19. Integrating Mathematical Modeling for Undergraduate Pre-Service Science Education Learning and Instruction in Middle School Classrooms

    ERIC Educational Resources Information Center

    Carrejo, David; Robertson, William H.

    2011-01-01

    Computer-based mathematical modeling in physics is a process of constructing models of concepts and the relationships between them in the scientific characteristics of work. In this manner, computer-based modeling integrates the interactions of natural phenomenon through the use of models, which provide structure for theories and a base for…

  20. Generalized Method for the User Evaluation of Purchased Information Services. Report Number Three; Monthly Report (October 1 to November 30, 1975).

    ERIC Educational Resources Information Center

    Hall, Homer J.

    Four case histories were studied in an on-going project to develop a method for user selection of purchased scientific and technical information services. The issues involved were: (1) the value of computer search services to a small branch of a company technical library; (2) the special decision-making factors used for selecting items of very…

  1. Activities at the Lunar and Planetary Institute

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The activities of the Lunar and Planetary Institute for the period July to December 1984 are discussed. Functions of its departments and projects are summarized. These include: planetary image center; library information center; computer center; production services; scientific staff; visitors program; scientific projects; conferences; workshops; seminars; publications and communications; panels, teams, committees and working groups; NASA-AMES vertical gun range (AVGR); and lunar and planetary science council.

  2. ArcGIS Framework for Scientific Data Analysis and Serving

    NASA Astrophysics Data System (ADS)

    Xu, H.; Ju, W.; Zhang, J.

    2015-12-01

    ArcGIS is a platform for managing, visualizing, analyzing, and serving geospatial data. Scientific data as part of the geospatial data features multiple dimensions (X, Y, time, and depth) and large volume. Multidimensional mosaic dataset (MDMD), a newly enhanced data model in ArcGIS, models the multidimensional gridded data (e.g. raster or image) as a hypercube and enables ArcGIS's capabilities to handle the large volume and near-real time scientific data. Built on top of geodatabase, the MDMD stores the dimension values and the variables (2D arrays) in a geodatabase table which allows accessing a slice or slices of the hypercube through a simple query and supports animating changes along time or vertical dimension using ArcGIS desktop or web clients. Through raster types, MDMD can manage not only netCDF, GRIB, and HDF formats but also many other formats or satellite data. It is scalable and can handle large data volume. The parallel geo-processing engine makes the data ingestion fast and easily. Raster function, definition of a raster processing algorithm, is a very important component in ArcGIS platform for on-demand raster processing and analysis. The scientific data analytics is achieved through the MDMD and raster function templates which perform on-demand scientific computation with variables ingested in the MDMD. For example, aggregating monthly average from daily data; computing total rainfall of a year; calculating heat index for forecasting data, and identifying fishing habitat zones etc. Addtionally, MDMD with the associated raster function templates can be served through ArcGIS server as image services which provide a framework for on-demand server side computation and analysis, and the published services can be accessed by multiple clients such as ArcMap, ArcGIS Online, JavaScript, REST, WCS, and WMS. This presentation will focus on the MDMD model and raster processing templates. In addtion, MODIS land cover, NDFD weather service, and HYCOM ocean model will be used to illustrate how ArcGIS platform and MDMD model can facilitate scientific data visualization and analytics and how the analysis results can be shared to more audience through ArcGIS Online and Portal.

  3. Using Amazon's Elastic Compute Cloud to dynamically scale CMS computational resources

    NASA Astrophysics Data System (ADS)

    Evans, D.; Fisk, I.; Holzman, B.; Melo, A.; Metson, S.; Pordes, R.; Sheldon, P.; Tiradani, A.

    2011-12-01

    Large international scientific collaborations such as the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider have traditionally addressed their data reduction and analysis needs by building and maintaining dedicated computational infrastructure. Emerging cloud computing services such as Amazon's Elastic Compute Cloud (EC2) offer short-term CPU and storage resources with costs based on usage. These services allow experiments to purchase computing resources as needed, without significant prior planning and without long term investments in facilities and their management. We have demonstrated that services such as EC2 can successfully be integrated into the production-computing model of CMS, and find that they work very well as worker nodes. The cost-structure and transient nature of EC2 services makes them inappropriate for some CMS production services and functions. We also found that the resources are not truely "on-demand" as limits and caps on usage are imposed. Our trial workflows allow us to make a cost comparison between EC2 resources and dedicated CMS resources at a University, and conclude that it is most cost effective to purchase dedicated resources for the "base-line" needs of experiments such as CMS. However, if the ability to use cloud computing resources is built into an experiment's software framework before demand requires their use, cloud computing resources make sense for bursting during times when spikes in usage are required.

  4. Impact of configuration management system of computer center on support of scientific projects throughout their lifecycle

    NASA Astrophysics Data System (ADS)

    Bogdanov, A. V.; Iuzhanin, N. V.; Zolotarev, V. I.; Ezhakova, T. R.

    2017-12-01

    In this article the problem of scientific projects support throughout their lifecycle in the computer center is considered in every aspect of support. Configuration Management system plays a connecting role in processes related to the provision and support of services of a computer center. In view of strong integration of IT infrastructure components with the use of virtualization, control of infrastructure becomes even more critical to the support of research projects, which means higher requirements for the Configuration Management system. For every aspect of research projects support, the influence of the Configuration Management system is being reviewed and development of the corresponding elements of the system is being described in the present paper.

  5. ChemCalc: a building block for tomorrow's chemical infrastructure.

    PubMed

    Patiny, Luc; Borel, Alain

    2013-05-24

    Web services, as an aspect of cloud computing, are becoming an important part of the general IT infrastructure, and scientific computing is no exception to this trend. We propose a simple approach to develop chemical Web services, through which servers could expose the essential data manipulation functionality that students and researchers need for chemical calculations. These services return their results as JSON (JavaScript Object Notation) objects, which facilitates their use for Web applications. The ChemCalc project http://www.chemcalc.org demonstrates this approach: we present three Web services related with mass spectrometry, namely isotopic distribution simulation, peptide fragmentation simulation, and molecular formula determination. We also developed a complete Web application based on these three Web services, taking advantage of modern HTML5 and JavaScript libraries (ChemDoodle and jQuery).

  6. 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.

  7. Climate Analytics as a Service. Chapter 11

    NASA Technical Reports Server (NTRS)

    Schnase, John L.

    2016-01-01

    Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

  8. IEEE Computer Society/Software Engineering Institute Software Process Achievement (SPA) Award 2009

    DTIC Science & Technology

    2011-03-01

    capabilities to our GDM. We also introduced software as a service ( SaaS ) as part our technology solutions and have further enhanced our ability to...model PROSPER Infosys production support methodology Q&P quality and productivity R&D research and development SaaS software as a service ... Software Development Life Cycle (SDLC) 23 Table 10: Scientific Estimation Coverage by Service Line 27 CMU/SEI-2011-TR-008 | vi CMU/SEI-2011

  9. Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

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

    Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

    2008-07-30

    As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

  10. A scientific workflow framework for (13)C metabolic flux analysis.

    PubMed

    Dalman, Tolga; Wiechert, Wolfgang; Nöh, Katharina

    2016-08-20

    Metabolic flux analysis (MFA) with (13)C labeling data is a high-precision technique to quantify intracellular reaction rates (fluxes). One of the major challenges of (13)C MFA is the interactivity of the computational workflow according to which the fluxes are determined from the input data (metabolic network model, labeling data, and physiological rates). Here, the workflow assembly is inevitably determined by the scientist who has to consider interacting biological, experimental, and computational aspects. Decision-making is context dependent and requires expertise, rendering an automated evaluation process hardly possible. Here, we present a scientific workflow framework (SWF) for creating, executing, and controlling on demand (13)C MFA workflows. (13)C MFA-specific tools and libraries, such as the high-performance simulation toolbox 13CFLUX2, are wrapped as web services and thereby integrated into a service-oriented architecture. Besides workflow steering, the SWF features transparent provenance collection and enables full flexibility for ad hoc scripting solutions. To handle compute-intensive tasks, cloud computing is supported. We demonstrate how the challenges posed by (13)C MFA workflows can be solved with our approach on the basis of two proof-of-concept use cases. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. iRODS-Based Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation

    NASA Astrophysics Data System (ADS)

    Schnase, J. L.; Duffy, D. Q.; Tamkin, G. S.; Strong, S.; Ripley, D.; Gill, R.; Sinno, S. S.; Shen, Y.; Carriere, L. E.; Brieger, L.; Moore, R.; Rajasekar, A.; Schroeder, W.; Wan, M.

    2011-12-01

    Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of specialized virtual climate data servers, repetitive cloud provisioning, image-based deployment and distribution, and virtualization-as-a-service. A virtual climate data server is an OAIS-compliant, iRODS-based data server designed to support a particular type of scientific data collection. iRODS is data grid middleware that provides policy-based control over collection-building, managing, querying, accessing, and preserving large scientific data sets. We have developed prototype vCDSs to manage NetCDF, HDF, and GeoTIF data products. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA's Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into these virtualized resources, multiple vCDSs can use iRODS's federation and realized object capabilities to create an integrated ecosystem of data servers that can scale and adapt to changing requirements. This approach enables platform- or software-as-a-service deployment of the vCDSs and allows the NCCS to offer virtualization-as-a-service, a capacity to respond in an agile way to new customer requests for data services, and a path for migrating existing services into the cloud. We have registered MODIS Atmosphere data products in a vCDS that contains 54 million registered files, 630TB of data, and over 300 million metadata values. We are now assembling IPCC AR5 data into a production vCDS that will provide the platform upon which NCCS's Earth System Grid (ESG) node publishes to the extended science community. In this talk, we describe our approach, experiences, lessons learned, and plans for the future.

  12. Distributed geospatial model sharing based on open interoperability standards

    USGS Publications Warehouse

    Feng, Min; Liu, Shuguang; Euliss, Ned H.; Fang, Yin

    2009-01-01

    Numerous geospatial computational models have been developed based on sound principles and published in journals or presented in conferences. However modelers have made few advances in the development of computable modules that facilitate sharing during model development or utilization. Constraints hampering development of model sharing technology includes limitations on computing, storage, and connectivity; traditional stand-alone and closed network systems cannot fully support sharing and integrating geospatial models. To address this need, we have identified methods for sharing geospatial computational models using Service Oriented Architecture (SOA) techniques and open geospatial standards. The service-oriented model sharing service is accessible using any tools or systems compliant with open geospatial standards, making it possible to utilize vast scientific resources available from around the world to solve highly sophisticated application problems. The methods also allow model services to be empowered by diverse computational devices and technologies, such as portable devices and GRID computing infrastructures. Based on the generic and abstract operations and data structures required for Web Processing Service (WPS) standards, we developed an interactive interface for model sharing to help reduce interoperability problems for model use. Geospatial computational models are shared on model services, where the computational processes provided by models can be accessed through tools and systems compliant with WPS. We developed a platform to help modelers publish individual models in a simplified and efficient way. Finally, we illustrate our technique using wetland hydrological models we developed for the prairie pothole region of North America.

  13. NERSC Annual Report 2008-2009

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

    Hules, John; Bashor, Jon; Vu, Linda

    2010-05-28

    This report presents highlights of the research conducted on NERSC computers in a variety of scientific disciplines during the years 2008-2009. It also reports on changes and upgrades to NERSC's systems and services as well as activities of NERSC staff.

  14. End-to-end Cyberinfrastructure and Data Services for Earth System Science Education and Research: Unidata's Plans and Directions

    NASA Astrophysics Data System (ADS)

    Ramamurthy, M.

    2005-12-01

    A revolution is underway in the role played by cyberinfrastructure and data services in the conduct of research and education. We live in an era of an unprecedented data volume from diverse sources, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. For example, modern remote-sensing systems like hyperspectral satellite instruments generate terabytes of data each day. Environmental problems such as global change and water cycle transcend disciplinary as well as geographic boundaries, and their solution requires integrated earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing new pedagogical techniques such as enquiry-based learning and hands-on activities. Needless to add, today's education and research enterprise depends heavily on robust, flexible and scalable cyberinfrastructure, especially on the ready availability of quality data and appropriate tools to manipulate and integrate those data. Fortuitously, rapid advances in computing and communication technologies have also revolutionized how data, tools and services are being incorporated into the teaching and scientific enterprise. The exponential growth in the use of the Internet in education and research, largely due to the advent of the World Wide Web, is by now well documented. On the other hand, how some of the other technological and community trends that have shaped the use of cyberinfrastructure, especially data services, is less well understood. For example, the computing industry is converging on an approach called Web services that enables a standard and yet revolutionary way of building applications and methods to connect and exchange information over the Web. This new approach, based on XML - a widely accepted format for exchanging data and corresponding semantics over the Internet - enables applications, computer systems, and information processes to work together in a fundamentally different way. Likewise, the advent of digital libraries, grid computing platforms, interoperable frameworks, standards and protocols, open-source software, and community atmospheric models have been important drivers in shaping the use of a new generation of end-to-end cyberinfrastructure for solving some of the most challenging scientific and educational problems. In this talk, I will present an overview of the scientific, technological, and educational drivers and discuss recent developments in cyberinfrastructure and Unidata's role and directions in providing robust, end-to-end data services for solving geoscientific problems and advancing student learning.

  15. 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.

  16. The role of a clinically based computer department of instruction in a school of medicine.

    PubMed

    Yamamoto, W S

    1991-10-01

    The evolution of activities and educational directions of a department of instruction in medical computer technology in a school of medicine are reviewed. During the 18 years covered, the society at large has undergone marked change in availability and use of computation in every aspect of medical care. It is argued that a department of instruction should be clinical and develop revenue sources based on patient care, perform technical services for the institution with a decentralized structure, and perform both health services and scientific research. Distinction should be drawn between utilization of computing in medical specialties, library function, and instruction in computer science. The last is the proper arena for the academic content of instruction and is best labelled as the philosophical basis of medical knowledge, in particular, its epistemology. Contemporary pressures for teaching introductory computer skills are probably temporary.

  17. Building Research Cyberinfrastructure at Small/Medium Research Institutions

    ERIC Educational Resources Information Center

    Agee, Anne; Rowe, Theresa; Woo, Melissa; Woods, David

    2010-01-01

    A 2006 ECAR study defined cyberinfrastructure as the coordinated aggregate of "hardware, software, communications, services, facilities, and personnel that enable researchers to conduct advanced computational, collaborative, and data-intensive research." While cyberinfrastructure was initially seen as support for scientific and…

  18. iSPHERE - A New Approach to Collaborative Research and Cloud Computing

    NASA Astrophysics Data System (ADS)

    Al-Ubaidi, T.; Khodachenko, M. L.; Kallio, E. J.; Harry, A.; Alexeev, I. I.; Vázquez-Poletti, J. L.; Enke, H.; Magin, T.; Mair, M.; Scherf, M.; Poedts, S.; De Causmaecker, P.; Heynderickx, D.; Congedo, P.; Manolescu, I.; Esser, B.; Webb, S.; Ruja, C.

    2015-10-01

    The project iSPHERE (integrated Scientific Platform for HEterogeneous Research and Engineering) that has been proposed for Horizon 2020 (EINFRA-9- 2015, [1]) aims at creating a next generation Virtual Research Environment (VRE) that embraces existing and emerging technologies and standards in order to provide a versatile platform for scientific investigations and collaboration. The presentation will introduce the large project consortium, provide a comprehensive overview of iSPHERE's basic concepts and approaches and outline general user requirements that the VRE will strive to satisfy. An overview of the envisioned architecture will be given, focusing on the adapted Service Bus concept, i.e. the "Scientific Service Bus" as it is called in iSPHERE. The bus will act as a central hub for all communication and user access, and will be implemented in the course of the project. The agile approach [2] that has been chosen for detailed elaboration and documentation of user requirements, as well as for the actual implementation of the system, will be outlined and its motivation and basic structure will be discussed. The presentation will show which user communities will benefit and which concrete problems, scientific investigations are facing today, will be tackled by the system. Another focus of the presentation is iSPHERE's seamless integration of cloud computing resources and how these will benefit scientific modeling teams by providing a reliable and web based environment for cloud based model execution, storage of results, and comparison with measurements, including fully web based tools for data mining, analysis and visualization. Also the envisioned creation of a dedicated data model for experimental plasma physics will be discussed. It will be shown why the Scientific Service Bus provides an ideal basis to integrate a number of data models and communication protocols and to provide mechanisms for data exchange across multiple and even multidisciplinary platforms.

  19. 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.

  20. 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

  1. OOI CyberInfrastructure - Next Generation Oceanographic Research

    NASA Astrophysics Data System (ADS)

    Farcas, C.; Fox, P.; Arrott, M.; Farcas, E.; Klacansky, I.; Krueger, I.; Meisinger, M.; Orcutt, J.

    2008-12-01

    Software has become a key enabling technology for scientific discovery, observation, modeling, and exploitation of natural phenomena. New value emerges from the integration of individual subsystems into networked federations of capabilities exposed to the scientific community. Such data-intensive interoperability networks are crucial for future scientific collaborative research, as they open up new ways of fusing data from different sources and across various domains, and analysis on wide geographic areas. The recently established NSF OOI program, through its CyberInfrastructure component addresses this challenge by providing broad access from sensor networks for data acquisition up to computational grids for massive computations and binding infrastructure facilitating policy management and governance of the emerging system-of-scientific-systems. We provide insight into the integration core of this effort, namely, a hierarchic service-oriented architecture for a robust, performant, and maintainable implementation. We first discuss the relationship between data management and CI crosscutting concerns such as identity management, policy and governance, which define the organizational contexts for data access and usage. Next, we detail critical services including data ingestion, transformation, preservation, inventory, and presentation. To address interoperability issues between data represented in various formats we employ a semantic framework derived from the Earth System Grid technology, a canonical representation for scientific data based on DAP/OPeNDAP, and related data publishers such as ERDDAP. Finally, we briefly present the underlying transport based on a messaging infrastructure over the AMQP protocol, and the preservation based on a distributed file system through SDSC iRODS.

  2. Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

    Wu, Chase Qishi; Zhu, Michelle Mengxia

    The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

  3. Enabling a Scientific Cloud Marketplace: VGL (Invited)

    NASA Astrophysics Data System (ADS)

    Fraser, R.; Woodcock, R.; Wyborn, L. A.; Vote, J.; Rankine, T.; Cox, S. J.

    2013-12-01

    The Virtual Geophysics Laboratory (VGL) provides a flexible, web based environment where researchers can browse data and use a variety of scientific software packaged into tool kits that run in the Cloud. Both data and tool kits are published by multiple researchers and registered with the VGL infrastructure forming a data and application marketplace. The VGL provides the basic work flow of Discovery and Access to the disparate data sources and a Library for tool kits and scripting to drive the scientific codes. Computation is then performed on the Research or Commercial Clouds. Provenance information is collected throughout the work flow and can be published alongside the results allowing for experiment comparison and sharing with other researchers. VGL's "mix and match" approach to data, computational resources and scientific codes, enables a dynamic approach to scientific collaboration. VGL allows scientists to publish their specific contribution, be it data, code, compute or work flow, knowing the VGL framework will provide other components needed for a complete application. Other scientists can choose the pieces that suit them best to assemble an experiment. The coarse grain workflow of the VGL framework combined with the flexibility of the scripting library and computational toolkits allows for significant customisation and sharing amongst the community. The VGL utilises the cloud computational and storage resources from the Australian academic research cloud provided by the NeCTAR initiative and a large variety of data accessible from national and state agencies via the Spatial Information Services Stack (SISS - http://siss.auscope.org). VGL v1.2 screenshot - http://vgl.auscope.org

  4. National Laboratory for Advanced Scientific Visualization at UNAM - Mexico

    NASA Astrophysics Data System (ADS)

    Manea, Marina; Constantin Manea, Vlad; Varela, Alfredo

    2016-04-01

    In 2015, the National Autonomous University of Mexico (UNAM) joined the family of Universities and Research Centers where advanced visualization and computing plays a key role to promote and advance missions in research, education, community outreach, as well as business-oriented consulting. This initiative provides access to a great variety of advanced hardware and software resources and offers a range of consulting services that spans a variety of areas related to scientific visualization, among which are: neuroanatomy, embryonic development, genome related studies, geosciences, geography, physics and mathematics related disciplines. The National Laboratory for Advanced Scientific Visualization delivers services through three main infrastructure environments: the 3D fully immersive display system Cave, the high resolution parallel visualization system Powerwall, the high resolution spherical displays Earth Simulator. The entire visualization infrastructure is interconnected to a high-performance-computing-cluster (HPCC) called ADA in honor to Ada Lovelace, considered to be the first computer programmer. The Cave is an extra large 3.6m wide room with projected images on the front, left and right, as well as floor walls. Specialized crystal eyes LCD-shutter glasses provide a strong stereo depth perception, and a variety of tracking devices allow software to track the position of a user's hand, head and wand. The Powerwall is designed to bring large amounts of complex data together through parallel computing for team interaction and collaboration. This system is composed by 24 (6x4) high-resolution ultra-thin (2 mm) bezel monitors connected to a high-performance GPU cluster. The Earth Simulator is a large (60") high-resolution spherical display used for global-scale data visualization like geophysical, meteorological, climate and ecology data. The HPCC-ADA, is a 1000+ computing core system, which offers parallel computing resources to applications that requires large quantity of memory as well as large and fast parallel storage systems. The entire system temperature is controlled by an energy and space efficient cooling solution, based on large rear door liquid cooled heat exchangers. This state-of-the-art infrastructure will boost research activities in the region, offer a powerful scientific tool for teaching at undergraduate and graduate levels, and enhance association and cooperation with business-oriented organizations.

  5. Stackable middleware services for advanced multimedia applications. Final report for period July 14, 1999 - July 14, 2001

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

    Feng, Wu-chi; Crawfis, Roger, Weide, Bruce

    2002-02-01

    In this project, the authors propose the research, development, and distribution of a stackable component-based multimedia streaming protocol middleware service. The goals of this stackable middleware interface include: (1) The middleware service will provide application writers and scientists easy to use interfaces that support their visualization needs. (2) The middleware service will support a variety of image compression modes. Currently, many of the network adaptation protocols for video have been developed with DCT-based compression algorithms like H.261, MPEG-1, or MPEG-2 in mind. It is expected that with advanced scientific computing applications that the lossy compression of the image data willmore » be unacceptable in certain instances. The middleware service will support several in-line lossless compression modes for error-sensitive scientific visualization data. (3) The middleware service will support two different types of streaming video modes: one for interactive collaboration of scientists and a stored video streaming mode for viewing prerecorded animations. The use of two different streaming types will allow the quality of the video delivered to the user to be maximized. Most importantly, this service will happen transparently to the user (with some basic controls exported to the user for domain specific tweaking). In the spirit of layered network protocols (like ISO and TCP/IP), application writers should not have to know a large amount about lower level network details. Currently, many example video streaming players have their congestion management techniques tightly integrated into the video player itself and are, for the most part, ''one-off'' applications. As more networked multimedia and video applications are written in the future, a larger percentage of these programmers and scientist will most likely know little about the underlying networking layer. By providing a simple, powerful, and semi-transparent middleware layer, the successful completion of this project will help serve as a catalyst to support future video-based applications, particularly those of advanced scientific computing applications.« less

  6. National Fusion Collaboratory: Grid Computing for Simulations and Experiments

    NASA Astrophysics Data System (ADS)

    Greenwald, Martin

    2004-05-01

    The National Fusion Collaboratory Project is creating a computational grid designed to advance scientific understanding and innovation in magnetic fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling and allowing more efficient use of experimental facilities. The philosophy of FusionGrid is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as network available services, easily used by the fusion scientist. In such an environment, access to services is stressed rather than portability. By building on a foundation of established computer science toolkits, deployment time can be minimized. These services all share the same basic infrastructure that allows for secure authentication and resource authorization which allows stakeholders to control their own resources such as computers, data and experiments. Code developers can control intellectual property, and fair use of shared resources can be demonstrated and controlled. A key goal is to shield scientific users from the implementation details such that transparency and ease-of-use are maximized. The first FusionGrid service deployed was the TRANSP code, a widely used tool for transport analysis. Tools for run preparation, submission, monitoring and management have been developed and shared among a wide user base. This approach saves user sites from the laborious effort of maintaining such a large and complex code while at the same time reducing the burden on the development team by avoiding the need to support a large number of heterogeneous installations. Shared visualization and A/V tools are being developed and deployed to enhance long-distance collaborations. These include desktop versions of the Access Grid, a highly capable multi-point remote conferencing tool and capabilities for sharing displays and analysis tools over local and wide-area networks.

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

    PubMed

    Schmitt, Marco; Jäschke, Robert

    2017-01-01

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

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

    PubMed Central

    Schmitt, Marco

    2017-01-01

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

  9. HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

    DOE PAGES

    Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian; ...

    2017-09-29

    Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

  10. HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

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

    Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian

    Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

  11. Sustainable access to data, products, services and software from the European seismological Research Infrastructures: the EPOS TCS Seismology

    NASA Astrophysics Data System (ADS)

    Haslinger, Florian; Dupont, Aurelien; Michelini, Alberto; Rietbrock, Andreas; Sleeman, Reinoud; Wiemer, Stefan; Basili, Roberto; Bossu, Rémy; Cakti, Eser; Cotton, Fabrice; Crawford, Wayne; Diaz, Jordi; Garth, Tom; Locati, Mario; Luzi, Lucia; Pinho, Rui; Pitilakis, Kyriazis; Strollo, Angelo

    2016-04-01

    Easy, efficient and comprehensive access to data, data products, scientific services and scientific software is a key ingredient in enabling research at the frontiers of science. Organizing this access across the European Research Infrastructures in the field of seismology, so that it best serves user needs, takes advantage of state-of-the-art ICT solutions, provides cross-domain interoperability, and is organizationally and financially sustainable in the long term, is the core challenge of the implementation phase of the Thematic Core Service (TCS) Seismology within the EPOS-IP project. Building upon the existing European-level infrastructures ORFEUS for seismological waveforms, EMSC for seismological products, and EFEHR for seismological hazard and risk information, and implementing a pilot Computational Earth Science service starting from the results of the VERCE project, the work within the EPOS-IP project focuses on improving and extending the existing services, aligning them with global developments, to at the end produce a well coordinated framework that is technically, organizationally, and financially integrated with the EPOS architecture. This framework needs to respect the roles and responsibilities of the underlying national research infrastructures that are the data owners and main providers of data and products, and allow for active input and feedback from the (scientific) user community. At the same time, it needs to remain flexible enough to cope with unavoidable challenges in the availability of resources and dynamics of contributors. The technical work during the next years is organized in four areas: - constructing the next generation software architecture for the European Integrated (waveform) Data Archive EIDA, developing advanced metadata and station information services, fully integrate strong motion waveforms and derived parametric engineering-domain data, and advancing the integration of mobile (temporary) networks and OBS deployments in EIDA; - further development and expansion of services to access seismological products of scientific interest as provided by the community by implementing a common collection and development (IT) platform, improvements in the earthquake information services e.g. by introducing more robust quality indicators and diversifying collection and dissemination mechanisms, as well as improving historical earthquake data services; - development of a comprehensive suite of earthquake hazard products, tools, and services harmonized on the European level and available through a common access platform, encompassing information on seismic sources, seismogenic faults, ground-motion prediction equations, geotechnical information, and strong-motion recordings in buildings, together with an interface to earthquake risk; - a portal implementation of computational seismology tools and services, specifically for seismic waveform propagation in complex 3D media following the results of the VERCE project, and initiating the inclusion of further suitable codes on that portal in discussion with the community, forming the basis of EPOS computational earth science infrastructure. This will be accompanied by development and implementation of integrated and interoperable metadata structures, adequate and referencable persistent identifiers, and appropriate user access and authorization mechanisms. Here we present further detail on the work plan with the attempt to foster interaction with the target user community on the spectrum of services as well as on feedback mechanisms and governance.

  12. Science Gateways, Scientific Workflows and Open Community Software

    NASA Astrophysics Data System (ADS)

    Pierce, M. E.; Marru, S.

    2014-12-01

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

  13. Open Science in the Cloud: Towards a Universal Platform for Scientific and Statistical Computing

    NASA Astrophysics Data System (ADS)

    Chine, Karim

    The UK, through the e-Science program, the US through the NSF-funded cyber infrastructure and the European Union through the ICT Calls aimed to provide "the technological solution to the problem of efficiently connecting data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge".1 The Grid (Foster, 2002; Foster; Kesselman, Nick, & Tuecke, 2002), foreseen as a major accelerator of discovery, didn't meet the expectations it had excited at its beginnings and was not adopted by the broad population of research professionals. The Grid is a good tool for particle physicists and it has allowed them to tackle the tremendous computational challenges inherent to their field. However, as a technology and paradigm for delivering computing on demand, it doesn't work and it can't be fixed. On one hand, "the abstractions that Grids expose - to the end-user, to the deployers and to application developers - are inappropriate and they need to be higher level" (Jha, Merzky, & Fox), and on the other hand, academic Grids are inherently economically unsustainable. They can't compete with a service outsourced to the Industry whose quality and price would be driven by market forces. The virtualization technologies and their corollary, the Infrastructure-as-a-Service (IaaS) style cloud, hold the promise to enable what the Grid failed to deliver: a sustainable environment for computational sciences that would lower the barriers for accessing federated computational resources, software tools and data; enable collaboration and resources sharing and provide the building blocks of a ubiquitous platform for traceable and reproducible computational research.

  14. Development of a SaaS application probe to the physical properties of the Earth's interior: An attempt at moving HPC to the cloud

    NASA Astrophysics Data System (ADS)

    Huang, Qian

    2014-09-01

    Scientific computing often requires the availability of a massive number of computers for performing large-scale simulations, and computing in mineral physics is no exception. In order to investigate physical properties of minerals at extreme conditions in computational mineral physics, parallel computing technology is used to speed up the performance by utilizing multiple computer resources to process a computational task simultaneously thereby greatly reducing computation time. Traditionally, parallel computing has been addressed by using High Performance Computing (HPC) solutions and installed facilities such as clusters and super computers. Today, it has been seen that there is a tremendous growth in cloud computing. Infrastructure as a Service (IaaS), the on-demand and pay-as-you-go model, creates a flexible and cost-effective mean to access computing resources. In this paper, a feasibility report of HPC on a cloud infrastructure is presented. It is found that current cloud services in IaaS layer still need to improve performance to be useful to research projects. On the other hand, Software as a Service (SaaS), another type of cloud computing, is introduced into an HPC system for computing in mineral physics, and an application of which is developed. In this paper, an overall description of this SaaS application is presented. This contribution can promote cloud application development in computational mineral physics, and cross-disciplinary studies.

  15. Evolving the Land Information System into a Cloud Computing Service

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

    Houser, Paul R.

    The Land Information System (LIS) was developed to use advanced flexible land surface modeling and data assimilation frameworks to integrate extremely large satellite- and ground-based observations with advanced land surface models to produce continuous high-resolution fields of land surface states and fluxes. The resulting fields are extremely useful for drought and flood assessment, agricultural planning, disaster management, weather and climate forecasting, water resources assessment, and the like. We envisioned transforming the LIS modeling system into a scientific cloud computing-aware web and data service that would allow clients to easily setup and configure for use in addressing large water management issues.more » The focus of this Phase 1 project was to determine the scientific, technical, commercial merit and feasibility of the proposed LIS-cloud innovations that are currently barriers to broad LIS applicability. We (a) quantified the barriers to broad LIS utility and commercialization (high performance computing, big data, user interface, and licensing issues); (b) designed the proposed LIS-cloud web service, model-data interface, database services, and user interfaces; (c) constructed a prototype LIS user interface including abstractions for simulation control, visualization, and data interaction, (d) used the prototype to conduct a market analysis and survey to determine potential market size and competition, (e) identified LIS software licensing and copyright limitations and developed solutions, and (f) developed a business plan for development and marketing of the LIS-cloud innovation. While some significant feasibility issues were found in the LIS licensing, overall a high degree of LIS-cloud technical feasibility was found.« less

  16. Supporting Weather Data

    NASA Technical Reports Server (NTRS)

    2004-01-01

    Since its founding in 1992, Global Science & Technology, Inc. (GST), of Greenbelt, Maryland, has been developing technologies and providing services in support of NASA scientific research. GST specialties include scientific analysis, science data and information systems, data visualization, communications, networking and Web technologies, computer science, and software system engineering. As a longtime contractor to Goddard Space Flight Center s Earth Science Directorate, GST scientific, engineering, and information technology staff have extensive qualifications with the synthesis of satellite, in situ, and Earth science data for weather- and climate-related projects. GST s experience in this arena is end-to-end, from building satellite ground receiving systems and science data systems, to product generation and research and analysis.

  17. A Generic Archive Protocol and an Implementation

    NASA Astrophysics Data System (ADS)

    Jordan, J. M.; Jennings, D. G.; McGlynn, T. A.; Ruggiero, N. G.; Serlemitsos, T. A.

    1993-01-01

    Archiving vast amounts of data has become a major part of every scientific space mission today. GRASP, the Generic Retrieval/Ar\\-chive Services Protocol, addresses the question of how to archive the data collected in an environment where the underlying hardware archives and computer hosts may be rapidly changing.

  18. Generic Divide and Conquer Internet-Based Computing

    NASA Technical Reports Server (NTRS)

    Follen, Gregory J. (Technical Monitor); Radenski, Atanas

    2003-01-01

    The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.

  19. Evaluation of Service Level Agreement Approaches for Portfolio Management in the Financial Industry

    NASA Astrophysics Data System (ADS)

    Pontz, Tobias; Grauer, Manfred; Kuebert, Roland; Tenschert, Axel; Koller, Bastian

    The idea of service-oriented Grid computing seems to have the potential for fundamental paradigm change and a new architectural alignment concerning the design of IT infrastructures. There is a wide range of technical approaches from scientific communities which describe basic infrastructures and middlewares for integrating Grid resources in order that by now Grid applications are technically realizable. Hence, Grid computing needs viable business models and enhanced infrastructures to move from academic application right up to commercial application. For a commercial usage of these evolutions service level agreements are needed. The developed approaches are primary of academic interest and mostly have not been put into practice. Based on a business use case of the financial industry, five service level agreement approaches have been evaluated in this paper. Based on the evaluation, a management architecture has been designed and implemented as a prototype.

  20. Symmetrical compression distance for arrhythmia discrimination in cloud-based big-data services.

    PubMed

    Lillo-Castellano, J M; Mora-Jiménez, I; Santiago-Mozos, R; Chavarría-Asso, F; Cano-González, A; García-Alberola, A; Rojo-Álvarez, J L

    2015-07-01

    The current development of cloud computing is completely changing the paradigm of data knowledge extraction in huge databases. An example of this technology in the cardiac arrhythmia field is the SCOOP platform, a national-level scientific cloud-based big data service for implantable cardioverter defibrillators. In this scenario, we here propose a new methodology for automatic classification of intracardiac electrograms (EGMs) in a cloud computing system, designed for minimal signal preprocessing. A new compression-based similarity measure (CSM) is created for low computational burden, so-called weighted fast compression distance, which provides better performance when compared with other CSMs in the literature. Using simple machine learning techniques, a set of 6848 EGMs extracted from SCOOP platform were classified into seven cardiac arrhythmia classes and one noise class, reaching near to 90% accuracy when previous patient arrhythmia information was available and 63% otherwise, hence overcoming in all cases the classification provided by the majority class. Results show that this methodology can be used as a high-quality service of cloud computing, providing support to physicians for improving the knowledge on patient diagnosis.

  1. Institute for scientific computing research;fiscal year 1999 annual report

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

    Keyes, D

    2000-03-28

    Large-scale scientific computation, and all of the disciplines that support it and help to validate it, have been placed at the focus of Lawrence Livermore National Laboratory by the Accelerated Strategic Computing Initiative (ASCI). The Laboratory operates the computer with the highest peak performance in the world and has undertaken some of the largest and most compute-intensive simulations ever performed. Computers at the architectural extremes, however, are notoriously difficult to use efficiently. Even such successes as the Laboratory's two Bell Prizes awarded in November 1999 only emphasize the need for much better ways of interacting with the results of large-scalemore » simulations. Advances in scientific computing research have, therefore, never been more vital to the core missions of the Laboratory than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, the Laboratory must engage researchers at many academic centers of excellence. In FY 1999, the Institute for Scientific Computing Research (ISCR) has expanded the Laboratory's bridge to the academic community in the form of collaborative subcontracts, visiting faculty, student internships, a workshop, and a very active seminar series. ISCR research participants are integrated almost seamlessly with the Laboratory's Center for Applied Scientific Computing (CASC), which, in turn, addresses computational challenges arising throughout the Laboratory. Administratively, the ISCR flourishes under the Laboratory's University Relations Program (URP). Together with the other four Institutes of the URP, it must navigate a course that allows the Laboratory to benefit from academic exchanges while preserving national security. Although FY 1999 brought more than its share of challenges to the operation of an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and well worth the continued effort. A change of administration for the ISCR occurred during FY 1999. Acting Director John Fitzgerald retired from LLNL in August after 35 years of service, including the last two at helm of the ISCR. David Keyes, who has been a regular visitor in conjunction with ASCI scalable algorithms research since October 1997, overlapped with John for three months and serves half-time as the new Acting Director.« less

  2. Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

    NASA Astrophysics Data System (ADS)

    Chen, A.; Pham, L.; Kempler, S.; Theobald, M.; Esfandiari, A.; Campino, J.; Vollmer, B.; Lynnes, C.

    2011-12-01

    Cloud Computing technology has been used to offer high-performance and low-cost computing and storage resources for both scientific problems and business services. Several cloud computing services have been implemented in the commercial arena, e.g. Amazon's EC2 & S3, Microsoft's Azure, and Google App Engine. There are also some research and application programs being launched in academia and governments to utilize Cloud Computing. NASA launched the Nebula Cloud Computing platform in 2008, which is an Infrastructure as a Service (IaaS) to deliver on-demand distributed virtual computers. Nebula users can receive required computing resources as a fully outsourced service. NASA Goddard Earth Science Data and Information Service Center (GES DISC) migrated several GES DISC's applications to the Nebula as a proof of concept, including: a) The Simple, Scalable, Script-based Science Processor for Measurements (S4PM) for processing scientific data; b) the Atmospheric Infrared Sounder (AIRS) data process workflow for processing AIRS raw data; and c) the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (GIOVANNI) for online access to, analysis, and visualization of Earth science data. This work aims to evaluate the practicability and adaptability of the Nebula. The initial work focused on the AIRS data process workflow to evaluate the Nebula. The AIRS data process workflow consists of a series of algorithms being used to process raw AIRS level 0 data and output AIRS level 2 geophysical retrievals. Migrating the entire workflow to the Nebula platform is challenging, but practicable. After installing several supporting libraries and the processing code itself, the workflow is able to process AIRS data in a similar fashion to its current (non-cloud) configuration. We compared the performance of processing 2 days of AIRS level 0 data through level 2 using a Nebula virtual computer and a local Linux computer. The result shows that Nebula has significantly better performance than the local machine. Much of the difference was due to newer equipment in the Nebula than the legacy computer, which is suggestive of a potential economic advantage beyond elastic power, i.e., access to up-to-date hardware vs. legacy hardware that must be maintained past its prime to amortize the cost. In addition to a trade study of advantages and challenges of porting complex processing to the cloud, a tutorial was developed to enable further progress in utilizing the Nebula for Earth Science applications and understanding better the potential for Cloud Computing in further data- and computing-intensive Earth Science research. In particular, highly bursty computing such as that experienced in the user-demand-driven Giovanni system may become more tractable in a Cloud environment. Our future work will continue to focus on migrating more GES DISC's applications/instances, e.g. Giovanni instances, to the Nebula platform and making matured migrated applications to be in operation on the Nebula.

  3. Customizable scientific web-portal for DIII-D nuclear fusion experiment

    NASA Astrophysics Data System (ADS)

    Abla, G.; Kim, E. N.; Schissel, D. P.

    2010-04-01

    Increasing utilization of the Internet and convenient web technologies has made the web-portal a major application interface for remote participation and control of scientific instruments. While web-portals have provided a centralized gateway for multiple computational services, the amount of visual output often is overwhelming due to the high volume of data generated by complex scientific instruments and experiments. Since each scientist may have different priorities and areas of interest in the experiment, filtering and organizing information based on the individual user's need can increase the usability and efficiency of a web-portal. DIII-D is the largest magnetic nuclear fusion device in the US. A web-portal has been designed to support the experimental activities of DIII-D researchers worldwide. It offers a customizable interface with personalized page layouts and list of services for users to select. Each individual user can create a unique working environment to fit his own needs and interests. Customizable services are: real-time experiment status monitoring, diagnostic data access, interactive data analysis and visualization. The web-portal also supports interactive collaborations by providing collaborative logbook, and online instant announcement services. The DIII-D web-portal development utilizes multi-tier software architecture, and Web 2.0 technologies and tools, such as AJAX and Django, to develop a highly-interactive and customizable user interface.

  4. 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.

  5. 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.

  6. GABBs: Cyberinfrastructure for Self-Service Geospatial Data Exploration, Computation, and Sharing

    NASA Astrophysics Data System (ADS)

    Song, C. X.; Zhao, L.; Biehl, L. L.; Merwade, V.; Villoria, N.

    2016-12-01

    Geospatial data are present everywhere today with the proliferation of location-aware computing devices. This is especially true in the scientific community where large amounts of data are driving research and education activities in many domains. Collaboration over geospatial data, for example, in modeling, data analysis and visualization, must still overcome the barriers of specialized software and expertise among other challenges. In addressing these needs, the Geospatial data Analysis Building Blocks (GABBs) project aims at building geospatial modeling, data analysis and visualization capabilities in an open source web platform, HUBzero. Funded by NSF's Data Infrastructure Building Blocks initiative, GABBs is creating a geospatial data architecture that integrates spatial data management, mapping and visualization, and interfaces in the HUBzero platform for scientific collaborations. The geo-rendering enabled Rappture toolkit, a generic Python mapping library, geospatial data exploration and publication tools, and an integrated online geospatial data management solution are among the software building blocks from the project. The GABBS software will be available through Amazon's AWS Marketplace VM images and open source. Hosting services are also available to the user community. The outcome of the project will enable researchers and educators to self-manage their scientific data, rapidly create GIS-enable tools, share geospatial data and tools on the web, and build dynamic workflows connecting data and tools, all without requiring significant software development skills, GIS expertise or IT administrative privileges. This presentation will describe the GABBs architecture, toolkits and libraries, and showcase the scientific use cases that utilize GABBs capabilities, as well as the challenges and solutions for GABBs to interoperate with other cyberinfrastructure platforms.

  7. The Virtual Climate Data Server (vCDS): An iRODS-Based Data Management Software Appliance Supporting Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation

    NASA Technical Reports Server (NTRS)

    Schnase, John L.; Tamkin, Glenn S.; Ripley, W. David III; Stong, Savannah; Gill, Roger; Duffy, Daniel Q.

    2012-01-01

    Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of a Virtual Climate Data Server (vCDS), repetitive provisioning, image-based deployment and distribution, and virtualization-as-a-service. The vCDS is an iRODS-based data server specialized to the needs of a particular data-centric application. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA s Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into one or more of these virtualized resource classes, vCDSs can use iRODS s federation capabilities to create an integrated ecosystem of managed collections that is scalable and adaptable to changing resource requirements. This approach enables platform- or software-asa- service deployment of vCDS and allows the NCCS to offer virtualization-as-a-service: a capacity to respond in an agile way to new customer requests for data services.

  8. Four-Year Summary, Educational and Commercial Utilization of a Chemical Information Center, Part II.

    ERIC Educational Resources Information Center

    Schipma, Peter B., Ed.

    The major objective of the Illinois Institute of Technology Retrieval Institute (IITRI) Computer Search Center (CSC) is to educate and link industry, academia, and government institutions to chemical and other scientific information systems and sources. The CSC is in full operation providing services to users from a variety of machine-readable…

  9. Educational and Commercial Utilization of a Chemical Information Center, Four Year Summary.

    ERIC Educational Resources Information Center

    Williams, Martha E.; And Others

    The major objective of the IITRI Computer Search Center is to educate and link industry, academia, and government institutions to chemical and other scientific information systems and sources. The Center was developed to meet this objective and is in full operation providing services to users from a variety of machine-readable data bases with…

  10. A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

    Treesearch

    Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin

    2017-01-01

    Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...

  11. Four-Year Summary, Educational and Commercial Utilization of a Chemical Information Center. Part I.

    ERIC Educational Resources Information Center

    Schipma, Peter B., Ed.

    The major objective of the Illinois Institute of Technology (IIT) Computer Search Center (CSC) is to educate and link industry, academia, and government institutions to chemical and other scientific information systems and sources. The CSC is in full operation providing services to users from a variety of machine-readable data bases with minimal…

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

    NASA Technical Reports Server (NTRS)

    Gallagher, D. L. (Editor)

    1993-01-01

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

  13. Physicists Get INSPIREd: INSPIRE Project and Grid Applications

    NASA Astrophysics Data System (ADS)

    Klem, Jukka; Iwaszkiewicz, Jan

    2011-12-01

    INSPIRE is the new high-energy physics scientific information system developed by CERN, DESY, Fermilab and SLAC. INSPIRE combines the curated and trusted contents of SPIRES database with Invenio digital library technology. INSPIRE contains the entire HEP literature with about one million records and in addition to becoming the reference HEP scientific information platform, it aims to provide new kinds of data mining services and metrics to assess the impact of articles and authors. Grid and cloud computing provide new opportunities to offer better services in areas that require large CPU and storage resources including document Optical Character Recognition (OCR) processing, full-text indexing of articles and improved metrics. D4Science-II is a European project that develops and operates an e-Infrastructure supporting Virtual Research Environments (VREs). It develops an enabling technology (gCube) which implements a mechanism for facilitating the interoperation of its e-Infrastructure with other autonomously running data e-Infrastructures. As a result, this creates the core of an e-Infrastructure ecosystem. INSPIRE is one of the e-Infrastructures participating in D4Science-II project. In the context of the D4Science-II project, the INSPIRE e-Infrastructure makes available some of its resources and services to other members of the resulting ecosystem. Moreover, it benefits from the ecosystem via a dedicated Virtual Organization giving access to an array of resources ranging from computing and storage resources of grid infrastructures to data and services.

  14. Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models

    PubMed Central

    Walker, Mark A.; Madduri, Ravi; Rodriguez, Alex; Greenstein, Joseph L.; Winslow, Raimond L.

    2016-01-01

    We describe the ways in which Galaxy, a web-based reproducible research platform, can be used for web-based sharing of complex computational models. Galaxy allows users to seamlessly customize and run simulations on cloud computing resources, a concept we refer to as Models and Simulations as a Service (MaSS). To illustrate this application of Galaxy, we have developed a tool suite for simulating a high spatial-resolution model of the cardiac Ca2+ spark that requires supercomputing resources for execution. We also present tools for simulating models encoded in the SBML and CellML model description languages, thus demonstrating how Galaxy’s reproducible research features can be leveraged by existing technologies. Finally, we demonstrate how the Galaxy workflow editor can be used to compose integrative models from constituent submodules. This work represents an important novel approach, to our knowledge, to making computational simulations more accessible to the broader scientific community. PMID:26958881

  15. The service telemetry and control device for space experiment “GRIS”

    NASA Astrophysics Data System (ADS)

    Glyanenko, A. S.

    2016-02-01

    Problems of scientific devices control (for example, fine control of measuring paths), collecting auxiliary (service information about working capacity, conditions of experiment carrying out, etc.) and preliminary data processing are actual for any space device. Modern devices for space research it is impossible to imagine without devices that didn't use digital data processing methods and specialized or standard interfaces and computing facilities. For realization of these functions in “GRIS” experiment onboard ISS for purposes minimization of dimensions, power consumption, the concept “system-on-chip” was chosen and realized. In the programmable logical integrated scheme by Microsemi from ProASIC3 family with maximum capacity up to 3M system gates, the computing kernel and all necessary peripherals are created. In this paper we discuss structure, possibilities and resources the service telemetry and control device for “GRIS” space experiment.

  16. [Automation of medical literature--and information services].

    PubMed

    Bakker, S

    1997-01-04

    It is important for clinical practice to be able to find (or retrieve) relevant literature and to keep informed of the state of medical science. The fact that the contents of articles in journals are now accessible via computers is the result of integration of bibliographic techniques, medical knowledge and computer technology. Articles published in some 5000 medical journals can nowadays be retrieved electronically via Medline and Embase together (but medical literature in Dutch is underrepresented). Computerised insertion of publications into Internet dose not make information traceable or accessible, let alone reliable and readable. It cannot be predicted if electronic versions of scientific periodicals will replace the printed editions completely. However, valuable, reliable information will always have its price, even on Internet. It is unlikely that electronic information published privately (internet) will replace scientific publishers soon, for readers will still want selection and monitoring of contents and language. Good layout, professional typography and suitable illustrations to enhance reading comfort and cognitive processes, will even become more important. The problems arising from the immensity of scientific knowledge are not (any longer) of a technological nature-what is needed is a cultural about-turn of the information infrastructure in medical-scientific associations, organizations and institutions.

  17. Enabling Earth Science Through Cloud Computing

    NASA Technical Reports Server (NTRS)

    Hardman, Sean; Riofrio, Andres; Shams, Khawaja; Freeborn, Dana; Springer, Paul; Chafin, Brian

    2012-01-01

    Cloud Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in cloud computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on cloud systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne Cloud Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate cloud computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating cloud computing solutions with the system and porting their science algorithms for execution in a cloud environment.

  18. INSA Scientific Activities in the Space Astronomy Area

    NASA Astrophysics Data System (ADS)

    Pérez Martínez, Ricardo; Sánchez Portal, Miguel

    Support to astronomy operations is an important and long-lived activity within INSA. Probably the best known (and traditional) INSA activities are those related with real-time spacecraft operations: ground station maintenance and operation (ground station engineers and operators); spacecraft and payload real-time operation (spacecraft and instruments controllers); computing infrastructure maintenance (operators, analysts), and general site services. In this paper, we’ll show a different perspective, probably not so well-known, presenting some INSA recent activities at the European Space Astronomy Centre (ESAC) and NASA Madrid Deep Space Communication Complex (MDSCC) directly related to scientific operations. Basic lines of activity involved include: operations support for science operations; system and software support for real time systems; technical administration and IT support; R&D activities, radioastronomy (at MDSCC and ESAC), and scientific research projects. This paper is structured as follows: first, INSA activities in two ESA cornerstone astrophysics missions, XMM-Newton and Herschel, will be outlined. Then, our activities related to scientific infrastructure services, represented by the Virtual Observatory (VO) framework and the Science Archives development facilities, are briefly shown. Radio astronomy activities will be described afterwards, and, finally, a few research topics in which INSA scientists are involved will also be described.

  19. Towards Monitoring-as-a-service for Scientific Computing Cloud applications using the ElasticSearch ecosystem

    NASA Astrophysics Data System (ADS)

    Bagnasco, S.; Berzano, D.; Guarise, A.; Lusso, S.; Masera, M.; Vallero, S.

    2015-12-01

    The INFN computing centre in Torino hosts a private Cloud, which is managed with the OpenNebula cloud controller. The infrastructure offers Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) services to different scientific computing applications. The main stakeholders of the facility are a grid Tier-2 site for the ALICE collaboration at LHC, an interactive analysis facility for the same experiment and a grid Tier-2 site for the BESIII collaboration, plus an increasing number of other small tenants. The dynamic allocation of resources to tenants is partially automated. This feature requires detailed monitoring and accounting of the resource usage. We set up a monitoring framework to inspect the site activities both in terms of IaaS and applications running on the hosted virtual instances. For this purpose we used the ElasticSearch, Logstash and Kibana (ELK) stack. The infrastructure relies on a MySQL database back-end for data preservation and to ensure flexibility to choose a different monitoring solution if needed. The heterogeneous accounting information is transferred from the database to the ElasticSearch engine via a custom Logstash plugin. Each use-case is indexed separately in ElasticSearch and we setup a set of Kibana dashboards with pre-defined queries in order to monitor the relevant information in each case. For the IaaS metering, we developed sensors for the OpenNebula API. The IaaS level information gathered through the API is sent to the MySQL database through an ad-hoc developed RESTful web service. Moreover, we have developed a billing system for our private Cloud, which relies on the RabbitMQ message queue for asynchronous communication to the database and on the ELK stack for its graphical interface. The Italian Grid accounting framework is also migrating to a similar set-up. Concerning the application level, we used the Root plugin TProofMonSenderSQL to collect accounting data from the interactive analysis facility. The BESIII virtual instances used to be monitored with Zabbix, as a proof of concept we also retrieve the information contained in the Zabbix database. In this way we have achieved a uniform monitoring interface for both the IaaS and the scientific applications, mostly leveraging off-the-shelf tools. At present, we are working to define a model for monitoring-as-a-service, based on the tools described above, which the Cloud tenants can easily configure to suit their specific needs.

  20. Integrating multiple scientific computing needs via a Private Cloud infrastructure

    NASA Astrophysics Data System (ADS)

    Bagnasco, S.; Berzano, D.; Brunetti, R.; Lusso, S.; Vallero, S.

    2014-06-01

    In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.

  1. Exploiting opportunistic resources for ATLAS with ARC CE and the Event Service

    NASA Astrophysics Data System (ADS)

    Cameron, D.; Filipčič, A.; Guan, W.; Tsulaia, V.; Walker, R.; Wenaus, T.; ATLAS Collaboration

    2017-10-01

    With ever-greater computing needs and fixed budgets, big scientific experiments are turning to opportunistic resources as a means to add much-needed extra computing power. These resources can be very different in design from those that comprise the Grid computing of most experiments, therefore exploiting them requires a change in strategy for the experiment. They may be highly restrictive in what can be run or in connections to the outside world, or tolerate opportunistic usage only on condition that tasks may be terminated without warning. The Advanced Resource Connector Computing Element (ARC CE) with its nonintrusive architecture is designed to integrate resources such as High Performance Computing (HPC) systems into a computing Grid. The ATLAS experiment developed the ATLAS Event Service (AES) primarily to address the issue of jobs that can be terminated at any point when opportunistic computing capacity is needed by someone else. This paper describes the integration of these two systems in order to exploit opportunistic resources for ATLAS in a restrictive environment. In addition to the technical details, results from deployment of this solution in the SuperMUC HPC centre in Munich are shown.

  2. Hera - The HEASARC's New Data Analysis Service

    NASA Technical Reports Server (NTRS)

    Pence, William

    2006-01-01

    Hera is the new computer service provided by the HEASARC at the NASA Goddard Space Flight Center that enables qualified student and professional astronomical researchers to immediately begin analyzing scientific data from high-energy astrophysics missions. All the necessary resources needed to do the data analysis are freely provided by Hera, including: * the latest version of the hundreds of scientific analysis programs in the HEASARC's HEASOFT package, as well as most of the programs in the Chandra CIAO package and the XMM-Newton SAS package. * high speed access to the terabytes of data in the HEASARC's high energy astrophysics Browse data archive. * a cluster of fast Linw workstations to run the software * ample local disk space to temporarily store the data and results. Some of the many features and different modes of using Hera are illustrated in this poster presentation.

  3. 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.

  4. 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

  5. Mexican Space Weather Service (SCIESMEX)

    NASA Astrophysics Data System (ADS)

    Gonzalez-Esparza, A.; De la Luz, V.; Mejia-Ambriz, J. C.; Aguilar-Rodriguez, E.; Corona-Romero, P.; Gonzalez, L. X.

    2015-12-01

    Recent modifications of the Civil Protection Law in Mexico include now specific mentions to space hazards and space weather phenomena. During the last few years, the UN has promoted international cooperation on Space Weather awareness, studies and monitoring. Internal and external conditions motivated the creation of a Space Weather Service in Mexico (SCIESMEX). The SCIESMEX (www.sciesmex.unam.mx) is operated by the Geophysics Institute at the National Autonomous University of Mexico (UNAM). The UNAM has the experience of operating several critical national services, including the National Seismological Service (SSN); besides that has a well established scientific group with expertise in space physics and solar- terrestrial phenomena. The SCIESMEX is also related with the recent creation of the Mexican Space Agency (AEM). The project combines a network of different ground instruments covering solar, interplanetary, geomagnetic, and ionospheric observations. The SCIESMEX has already in operation computing infrastructure running the web application, a virtual observatory and a high performance computing server to run numerical models. SCIESMEX participates in the International Space Environment Services (ISES) and in the Inter-progamme Coordination Team on Space Weather (ICTSW) of the Word Meteorological Organization (WMO).

  6. 76 FR 31945 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-02

    ... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy... teleconference meeting of the Advanced Scientific Computing Advisory Committee (ASCAC). The Federal [email protected] . FOR FURTHER INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing...

  7. Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

    PubMed Central

    Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

    2015-01-01

    Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

  8. Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

    PubMed

    Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

    2015-01-01

    Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

  9. Open Access: From Myth to Paradox

    ScienceCinema

    Ginsparg, Paul [Cornell University, Ithaca, New York, United States

    2018-04-19

    True open access to scientific publications not only gives readers the possibility to read articles without paying subscription, but also makes the material available for automated ingestion and harvesting by 3rd parties. Once articles and associated data become universally treatable as computable objects, openly available to 3rd party aggregators and value-added services, what new services can we expect, and how will they change the way that researchers interact with their scholarly communications infrastructure? I will discuss straightforward applications of existing ideas and services, including citation analysis, collaborative filtering, external database linkages, interoperability, and other forms of automated markup, and speculate on the sociology of the next generation of users.

  10. 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

  11. 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

  12. The role of NASA for aerospace information

    NASA Technical Reports Server (NTRS)

    Chandler, G. P., Jr.

    1980-01-01

    The NASA Scientific and Technical Information Program operations are performed by two contractor operated facilities. The NASA STI Facility, located near Baltimore, Maryland, employs about 210 people who process report literature, operate the computer complex, and provide support for software maintenance and developments. A second contractor, the Technical Information Services of the American Institute of Aeronautics and Astronautics, employs approximately 80 people in New York City and processes the open literature such as journals, magazines, and books. Features of these programs include online access via RECON, announcement services, and international document exchange.

  13. Prototyping an online wetland ecosystem services model using open model sharing standards

    USGS Publications Warehouse

    Feng, M.; Liu, S.; Euliss, N.H.; Young, Caitlin; Mushet, D.M.

    2011-01-01

    Great interest currently exists for developing ecosystem models to forecast how ecosystem services may change under alternative land use and climate futures. Ecosystem services are diverse and include supporting services or functions (e.g., primary production, nutrient cycling), provisioning services (e.g., wildlife, groundwater), regulating services (e.g., water purification, floodwater retention), and even cultural services (e.g., ecotourism, cultural heritage). Hence, the knowledge base necessary to quantify ecosystem services is broad and derived from many diverse scientific disciplines. Building the required interdisciplinary models is especially challenging as modelers from different locations and times may develop the disciplinary models needed for ecosystem simulations, and these models must be identified and made accessible to the interdisciplinary simulation. Additional difficulties include inconsistent data structures, formats, and metadata required by geospatial models as well as limitations on computing, storage, and connectivity. Traditional standalone and closed network systems cannot fully support sharing and integrating interdisciplinary geospatial models from variant sources. To address this need, we developed an approach to openly share and access geospatial computational models using distributed Geographic Information System (GIS) techniques and open geospatial standards. We included a means to share computational models compliant with Open Geospatial Consortium (OGC) Web Processing Services (WPS) standard to ensure modelers have an efficient and simplified means to publish new models. To demonstrate our approach, we developed five disciplinary models that can be integrated and shared to simulate a few of the ecosystem services (e.g., water storage, waterfowl breeding) that are provided by wetlands in the Prairie Pothole Region (PPR) of North America.

  14. 75 FR 9887 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-04

    ... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy... Advanced Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L. 92-463... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building...

  15. 76 FR 9765 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-22

    ... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee AGENCY: Office of Science... Advanced Scientific Computing Advisory Committee (ASCAC). The Federal Advisory Committee Act (Pub. L. 92... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research, SC-21/Germantown Building...

  16. 77 FR 45345 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-31

    ... Recompetition results for Scientific Discovery through Advanced Computing (SciDAC) applications Co-design Public... DEPARTMENT OF ENERGY DOE/Advanced Scientific Computing Advisory Committee AGENCY: Office of... the Advanced Scientific Computing Advisory Committee (ASCAC). The Federal Advisory Committee Act (Pub...

  17. 75 FR 64720 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-20

    ... DEPARTMENT OF ENERGY DOE/Advanced Scientific Computing Advisory Committee AGENCY: Department of... the Advanced Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L.... FOR FURTHER INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21...

  18. Computing through Scientific Abstractions in SysBioPS

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

    Chin, George; Stephan, Eric G.; Gracio, Deborah K.

    2004-10-13

    Today, biologists and bioinformaticists have a tremendous amount of computational power at their disposal. With the availability of supercomputers, burgeoning scientific databases and digital libraries such as GenBank and PubMed, and pervasive computational environments such as the Grid, biologists have access to a wealth of computational capabilities and scientific data at hand. Yet, the rapid development of computational technologies has far exceeded the typical biologist’s ability to effectively apply the technology in their research. Computational sciences research and development efforts such as the Biology Workbench, BioSPICE (Biological Simulation Program for Intra-Cellular Evaluation), and BioCoRE (Biological Collaborative Research Environment) are importantmore » in connecting biologists and their scientific problems to computational infrastructures. On the Computational Cell Environment and Heuristic Entity-Relationship Building Environment projects at the Pacific Northwest National Laboratory, we are jointly developing a new breed of scientific problem solving environment called SysBioPSE that will allow biologists to access and apply computational resources in the scientific research context. In contrast to other computational science environments, SysBioPSE operates as an abstraction layer above a computational infrastructure. The goal of SysBioPSE is to allow biologists to apply computational resources in the context of the scientific problems they are addressing and the scientific perspectives from which they conduct their research. More specifically, SysBioPSE allows biologists to capture and represent scientific concepts and theories and experimental processes, and to link these views to scientific applications, data repositories, and computer systems.« less

  19. 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.

  20. Adding Data Management Services to Parallel File Systems

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

    Brandt, Scott

    2015-03-04

    The objective of this project, called DAMASC for “Data Management in Scientific Computing”, is to coalesce data management with parallel file system management to present a declarative interface to scientists for managing, querying, and analyzing extremely large data sets efficiently and predictably. Managing extremely large data sets is a key challenge of exascale computing. The overhead, energy, and cost of moving massive volumes of data demand designs where computation is close to storage. In current architectures, compute/analysis clusters access data in a physically separate parallel file system and largely leave it scientist to reduce data movement. Over the past decadesmore » the high-end computing community has adopted middleware with multiple layers of abstractions and specialized file formats such as NetCDF-4 and HDF5. These abstractions provide a limited set of high-level data processing functions, but have inherent functionality and performance limitations: middleware that provides access to the highly structured contents of scientific data files stored in the (unstructured) file systems can only optimize to the extent that file system interfaces permit; the highly structured formats of these files often impedes native file system performance optimizations. We are developing Damasc, an enhanced high-performance file system with native rich data management services. Damasc will enable efficient queries and updates over files stored in their native byte-stream format while retaining the inherent performance of file system data storage via declarative queries and updates over views of underlying files. Damasc has four key benefits for the development of data-intensive scientific code: (1) applications can use important data-management services, such as declarative queries, views, and provenance tracking, that are currently available only within database systems; (2) the use of these services becomes easier, as they are provided within a familiar file-based ecosystem; (3) common optimizations, e.g., indexing and caching, are readily supported across several file formats, avoiding effort duplication; and (4) performance improves significantly, as data processing is integrated more tightly with data storage. Our key contributions are: SciHadoop which explores changes to MapReduce assumption by taking advantage of semantics of structured data while preserving MapReduce’s failure and resource management; DataMods which extends common abstractions of parallel file systems so they become programmable such that they can be extended to natively support a variety of data models and can be hooked into emerging distributed runtimes such as Stanford’s Legion; and Miso which combines Hadoop and relational data warehousing to minimize time to insight, taking into account the overhead of ingesting data into data warehousing.« less

  1. 75 FR 43518 - Advanced Scientific Computing Advisory Committee; Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-26

    ... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee; Meeting AGENCY: Office of... Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L. 92-463, 86 Stat. 770...: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U. S...

  2. End-to-end Cyberinfrastructure and Data Services for Earth System Science Education and Research: A vision for the future

    NASA Astrophysics Data System (ADS)

    Ramamurthy, M. K.

    2006-05-01

    We live in an era of an unprecedented data volumes, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. For instance, a new generation of satellite instruments is being designed for GOES-R and NPOESS programs to deliver terabytes of data each day. Similarly, high-resolution, coupled models run over a wide range of temporal scales are generating data at unprecedented rates. Complex environmental problems such as El Nino/Southern Oscillation, climate change, and water cycle transcend not only disciplinary but also geographic boundaries, with their impacts and implications touching every region and community of the world. The understanding and solution to these inherently global scientific and social problems requires integrated observations that cover all areas of the globe, international sharing and flow of data, and earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing new pedagogical techniques such as enquiry-based learning and hands-on activities. Needless to add, today's education and research enterprise depends heavily on easy to use, robust, flexible and scalable cyberinfrastructure, especially on the ready availability of quality data and appropriate tools to manipulate and integrate those data. Fortunately, rapid advances in computing, communication and information technologies have provided solutions that can are being applied to advance teaching, research, and service. The exponential growth in the use of the Internet in education and research, largely due to the advent of the World Wide Web, is well documented. On the other hand, how other technological and community trends have shaped the development and application of cyberinfrastructure, especially in the data services area, is less well understood. For example, the computing industry is converging on an approach called Web services that enables a standard and yet revolutionary way of building applications and methods to connect and exchange information over the Web. This new approach, based on XML - a widely accepted format for exchanging data and corresponding semantics over the Internet - enables applications, computer systems, and information processes to work together in fundamentally different ways. Likewise, the advent of digital libraries, grid computing platforms, interoperable frameworks, standards and protocols, open-source software, and community atmospheric models have been important drivers in shaping the use of a new generation of end-to-end cyberinfrastructure for solving some of the most challenging scientific and educational problems. In this talk, I will present an overview of the scientific, technological, and educational landscape, discuss recent developments in cyberinfrastructure, and Unidata's role in and vision for providing easy-to use, robust, end-to-end data services for solving geoscientific problems and advancing student learning.

  3. The SBAS Sentinel-1 Surveillance service for automatic and systematic generation of Earth surface displacement within the GEP platform.

    NASA Astrophysics Data System (ADS)

    Casu, Francesco; De Luca, Claudio; Lanari, Riccardo; Manunta, Michele; Zinno, Ivana

    2017-04-01

    The Geohazards Exploitation Platform (GEP) is an ESA activity of the Earth Observation (EO) ground segment to demonstrate the benefit of new technologies for large scale processing of EO data. GEP aims at providing both on-demand processing services for scientific users of the geohazards community and an integration platform for new EO data analysis processors dedicated to scientists and other expert users. In the Remote Sensing scenario, a crucial role is played by the recently launched Sentinel-1 (S1) constellation that, with its global acquisition policy, has literally flooded the scientific community with a huge amount of data acquired over large part of the Earth on a regular basis (down to 6-days with both Sentinel-1A and 1B passes). Moreover, the S1 data, as part of the European Copernicus program, are openly and freely accessible, thus fostering their use for the development of tools for Earth surface monitoring. In particular, due to their specific SAR Interferometry (InSAR) design, Sentinel-1 satellites can be exploited to build up operational services for the generation of advanced interferometric products that can be very useful within risk management and natural hazard monitoring scenarios. Accordingly, in this work we present the activities carried out for the development, integration, and deployment of the SBAS Sentinel-1 Surveillance service of CNR-IREA within the GEP platform. This service is based on a parallel implementation of the SBAS approach, referred to as P-SBAS, able to effectively run in large distributed computing infrastructures (grid and cloud) and to allow for an efficient computation of large SAR data sequences with advanced DInSAR approaches. In particular, the Surveillance service developed on GEP platform consists on the systematic and automatic processing of Sentinel-1 data on selected Areas of Interest (AoI) to generate updated surface displacement time series via the SBAS-InSAR algorithm. We built up a system that is automatically triggered by every new S1 acquisition over the AoI, once it is available on the S1 catalogue. Then, tacking benefit from the SBAS results generated by previous runs of the service, the system processes the new acquisitions only, thus saving storage space and computing time and finally generating an updated SBAS time series. The same P-SBAS processor underlying the Surveillance service is also available through the GEP as a standard on-demand DInSAR service, thus allowing the scientific community to generate S1 SBAS time series on areas not covered by the Surveillance service itself. It is worth noting that the SBAS Sentinel-1 Surveillance service on GEP represents the core of the EPOSAR service, which will deliver S1 displacement time series of Earth surface on a regular basis for the European Plate Observing System (EPOS) Research Infrastructure community. In particular, the main goal of EPOSAR is to contribute with advanced technique and methods, which have already well demonstrated their effectiveness and relevance, in investigating the physical processes controlling earthquakes, volcanic eruptions and unrest episodes as well as those driving tectonics and Earth surface dynamics.

  4. Investigation of Storage Options for Scientific Computing on Grid and Cloud Facilities

    NASA Astrophysics Data System (ADS)

    Garzoglio, Gabriele

    2012-12-01

    In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storage server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on “bare metal” nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.

  5. Investigation of storage options for scientific computing on Grid and Cloud facilities

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

    Garzoglio, Gabriele

    In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storagemore » server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on bare metal nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.« less

  6. Grids: The Top Ten Questions

    DOE PAGES

    Schopf, Jennifer M.; Nitzberg, Bill

    2002-01-01

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

  7. 78 FR 6854 - Health Services Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-31

    ... DEPARTMENT OF VETERANS AFFAIRS Health Services Research and Development Service Scientific Merit... Research and Development Service Scientific Merit Review Board will meet on February 13-14, 2013, at the... research. Applications are reviewed for scientific and technical merit. Recommendations regarding funding...

  8. The Globus Galaxies Platform. Delivering Science Gateways as a Service

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

    Madduri, Ravi; Chard, Kyle; Chard, Ryan

    We use public cloud computers to host sophisticated scientific data; software is then used to transform scientific practice by enabling broad access to capabilities previously available only to the few. The primary obstacle to more widespread use of public clouds to host scientific software (‘cloud-based science gateways’) has thus far been the considerable gap between the specialized needs of science applications and the capabilities provided by cloud infrastructures. We describe here a domain-independent, cloud-based science gateway platform, the Globus Galaxies platform, which overcomes this gap by providing a set of hosted services that directly address the needs of science gatewaymore » developers. The design and implementation of this platform leverages our several years of experience with Globus Genomics, a cloud-based science gateway that has served more than 200 genomics researchers across 30 institutions. Building on that foundation, we have also implemented a platform that leverages the popular Galaxy system for application hosting and workflow execution; Globus services for data transfer, user and group management, and authentication; and a cost-aware elastic provisioning model specialized for public cloud resources. We describe here the capabilities and architecture of this platform, present six scientific domains in which we have successfully applied it, report on user experiences, and analyze the economics of our deployments. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.« less

  9. Computational knowledge integration in biopharmaceutical research.

    PubMed

    Ficenec, David; Osborne, Mark; Pradines, Joel; Richards, Dan; Felciano, Ramon; Cho, Raymond J; Chen, Richard O; Liefeld, Ted; Owen, James; Ruttenberg, Alan; Reich, Christian; Horvath, Joseph; Clark, Tim

    2003-09-01

    An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action.

  10. Design of the smart scenic spot service platform

    NASA Astrophysics Data System (ADS)

    Yin, Min; Wang, Shi-tai

    2015-12-01

    With the deepening of the smart city construction, the model "smart+" is rapidly developing. Guilin, the international tourism metropolis fast constructing need smart tourism technology support. This paper studied the smart scenic spot service object and its requirements. And then constructed the smart service platform of the scenic spot application of 3S technology (Geographic Information System (GIS), Remote Sensing (RS) and Global Navigation Satellite System (GNSS)) and the Internet of things, cloud computing. Based on Guilin Seven-star Park scenic area as an object, this paper designed the Seven-star smart scenic spot service platform framework. The application of this platform will improve the tourists' visiting experience, make the tourism management more scientifically and standardly, increase tourism enterprises operating earnings.

  11. Globus: Service and Platform for Research Data Lifecycle Management

    NASA Astrophysics Data System (ADS)

    Ananthakrishnan, R.; Foster, I.

    2017-12-01

    Globus offers a range of data management capabilities to the community as hosted services, encompassing data transfer and sharing, user identity and authorization, and data publication. Globus capabilities are accessible via both a web browser and REST APIs. Web access allows researchers to use Globus capabilities through a software-as-a-service model; and the REST APIs address the needs of developers of research services, who can now use Globus as a platform, outsourcing complex user and data management tasks to Globus services. In this presentation, we review Globus capabilities and outline how it is being applied as a platform for scientific services, and highlight work done to link computational analysis flows to the underlying data through an interactive Jupyter notebook environment to promote immediate data usability, reusability of these flows by other researchers, and future analysis extensibility.

  12. Water-resources investigations in Pennsylvania; programs and activities of the U.S. Geological Survey, 1990-91

    USGS Publications Warehouse

    McLanahan, L.O.

    1991-01-01

    The U.S. Geological Survey (USGS) was established by an act of Congress on March 3, 1879, to provide a permanent Federal agency to conduct the systematic and scientific 'classification of the public lands, and examination of the geological structure, mineral resources, and products of national domain'. Since 1879, the research and fact-finding role of the USGS has grown and has been modified to meet the changing needs of the Nation it serves. Moneys for program operation of the USGS in Pennsylvania come from joint-funding agreements with State and local agencies , transfer of funds from other Federal agencies, and direct Federal allotments to the USGS. Funding is distributed among the following programs: National Water Quality Assessment; water quality programs; surface water programs; groundwater programs; logging and geophysical services; computer services; scientific publication and information; hydrologic investigations; and hydrologic surveillance. (Lantz-PTT)

  13. Use of cloud computing in biomedicine.

    PubMed

    Sobeslav, Vladimir; Maresova, Petra; Krejcar, Ondrej; Franca, Tanos C C; Kuca, Kamil

    2016-12-01

    Nowadays, biomedicine is characterised by a growing need for processing of large amounts of data in real time. This leads to new requirements for information and communication technologies (ICT). Cloud computing offers a solution to these requirements and provides many advantages, such as cost savings, elasticity and scalability of using ICT. The aim of this paper is to explore the concept of cloud computing and the related use of this concept in the area of biomedicine. Authors offer a comprehensive analysis of the implementation of the cloud computing approach in biomedical research, decomposed into infrastructure, platform and service layer, and a recommendation for processing large amounts of data in biomedicine. Firstly, the paper describes the appropriate forms and technological solutions of cloud computing. Secondly, the high-end computing paradigm of cloud computing aspects is analysed. Finally, the potential and current use of applications in scientific research of this technology in biomedicine is discussed.

  14. Visions of the Future - the Changing Role of Actors in Data-Intensive Science

    NASA Astrophysics Data System (ADS)

    Schäfer, L.; Klump, J. F.

    2013-12-01

    Around the world scientific disciplines are increasingly facing the challenge of a burgeoning volume of research data. This data avalanche consists of a stream of information generated from sensors and scientific instruments, digital recordings, social-science surveys or drawn from the World Wide Web. All areas of the scientific economy are affected by this rapid growth in data, from the logging of digs in Archaeology, telescope data with observations of distant galaxies in Astrophysics or data from polls and surveys in the Social Sciences. The challenge for science is not only to process the data through analysis, reduction and visualization, but also to set up infrastructures for provisioning and storing the data. The rise of new technologies and developments also poses new challenges for the actors in the area of research data infrastructures. Libraries, as one of the actors, enable access to digital media and support the publication of research data and its long-term archiving. Digital media and research data, however, introduce new aspects into the libraries' range of activities. How are we to imagine the library of the future? The library as an interface to the computer centers? Will library and computer center fuse into a new service unit? What role will scientific publishers play in future? Currently the traditional form of publication still carry greater weight - articles for conferences and journals. But will this still be the case in future? New forms of publication are already making their presence felt. The tasks of the computer centers may also change. Yesterday their remit was provisioning of rapid hardware, whereas now everything revolves around the topic of data and services. Finally, how about the researchers themselves? Not such a long time ago, Geoscience was not necessarily seen as linked to Computer Science. Nowadays, modern Geoscience relies heavily on IT and its techniques. Thus, in how far will the profile of the modern geoscientist change? This gives rise to the question of what tools are required to locate and pursue the correct course in a networked world. One tool from the area of innovation management is the scenario technique. This poster will outline visions of the future as possible developments of the scientific world in 2020 (or later). The scenarios presented will show possible developments - both positive and negative. It is up then to the actors themselves to define their own position in this context, to rethink it and consider steps that can achieve a positive development for the future.

  15. A Responsive Client for Distributed Visualization

    NASA Astrophysics Data System (ADS)

    Bollig, E. F.; Jensen, P. A.; Erlebacher, G.; Yuen, D. A.; Momsen, A. R.

    2006-12-01

    As grids, web services and distributed computing continue to gain popularity in the scientific community, demand for virtual laboratories likewise increases. Today organizations such as the Virtual Laboratory for Earth and Planetary Sciences (VLab) are dedicated to developing web-based portals to perform various simulations remotely while abstracting away details of the underlying computation. Two of the biggest challenges in portal- based computing are fast visualization and smooth interrogation without over taxing clients resources. In response to this challenge, we have expanded on our previous data storage strategy and thick client visualization scheme [1] to develop a client-centric distributed application that utilizes remote visualization of large datasets and makes use of the local graphics processor for improved interactivity. Rather than waste precious client resources for visualization, a combination of 3D graphics and 2D server bitmaps are used to simulate the look and feel of local rendering. Java Web Start and Java Bindings for OpenGL enable install-on- demand functionality as well as low level access to client graphics for all platforms. Powerful visualization services based on VTK and auto-generated by the WATT compiler [2] are accessible through a standard web API. Data is permanently stored on compute nodes while separate visualization nodes fetch data requested by clients, caching it locally to prevent unnecessary transfers. We will demonstrate application capabilities in the context of simulated charge density visualization within the VLab portal. In addition, we will address generalizations of our application to interact with a wider number of WATT services and performance bottlenecks. [1] Ananthuni, R., Karki, B.B., Bollig, E.F., da Silva, C.R.S., Erlebacher, G., "A Web-Based Visualization and Reposition Scheme for Scientific Data," In Press, Proceedings of the 2006 International Conference on Modeling Simulation and Visualization Methods (MSV'06) (2006). [2] Jensen, P.A., Yuen, D.A., Erlebacher, G., Bollig, E.F., Kigelman, D.G., Shukh, E.A., Automated Generation of Web Services for Visualization Toolkits, Eos Trans. AGU, 86(52), Fall Meet. Suppl., Abstract IN42A-06, 2005.

  16. Geospatial-enabled Data Exploration and Computation through Data Infrastructure Building Blocks

    NASA Astrophysics Data System (ADS)

    Song, C. X.; Biehl, L. L.; Merwade, V.; Villoria, N.

    2015-12-01

    Geospatial data are present everywhere today with the proliferation of location-aware computing devices and sensors. This is especially true in the scientific community where large amounts of data are driving research and education activities in many domains. Collaboration over geospatial data, for example, in modeling, data analysis and visualization, must still overcome the barriers of specialized software and expertise among other challenges. The GABBs project aims at enabling broader access to geospatial data exploration and computation by developing spatial data infrastructure building blocks that leverage capabilities of end-to-end application service and virtualized computing framework in HUBzero. Funded by NSF Data Infrastructure Building Blocks (DIBBS) initiative, GABBs provides a geospatial data architecture that integrates spatial data management, mapping and visualization and will make it available as open source. The outcome of the project will enable users to rapidly create tools and share geospatial data and tools on the web for interactive exploration of data without requiring significant software development skills, GIS expertise or IT administrative privileges. This presentation will describe the development of geospatial data infrastructure building blocks and the scientific use cases that help drive the software development, as well as seek feedback from the user communities.

  17. Investigation of the Public Library as a Linking Agent to Major Scientific, Educational, Social and Environmental Data Bases. Two-Year Interim Report.

    ERIC Educational Resources Information Center

    Summit, Roger K.; Firschein, Oscar

    Eight public libraries participated in a two-year experiment to investigate the potential of the public library as a "linking agent" between the public and the many machine-readable data bases currently accessible using on line computer terminals. The investigation covered users of the service, impact on the library, conditions for…

  18. !CHAOS: A cloud of controls

    NASA Astrophysics Data System (ADS)

    Angius, S.; Bisegni, C.; Ciuffetti, P.; Di Pirro, G.; Foggetta, L. G.; Galletti, F.; Gargana, R.; Gioscio, E.; Maselli, D.; Mazzitelli, G.; Michelotti, A.; Orrù, R.; Pistoni, M.; Spagnoli, F.; Spigone, D.; Stecchi, A.; Tonto, T.; Tota, M. A.; Catani, L.; Di Giulio, C.; Salina, G.; Buzzi, P.; Checcucci, B.; Lubrano, P.; Piccini, M.; Fattibene, E.; Michelotto, M.; Cavallaro, S. R.; Diana, B. F.; Enrico, F.; Pulvirenti, S.

    2016-01-01

    The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of aaabstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack.

  19. Controlador para un Reloj GPS de Referencia en el Protocolo NTP

    NASA Astrophysics Data System (ADS)

    Hauscarriaga, F.; Bareilles, F. A.

    The synchronization between computers in a local network plays a very important role on enviroments similar to IAR. Calculations for exact time are needed before, during and after an observation. For this purpose the IAR's GNU/Linux Software Development Team implemented a driver inside NTP protocol (an internet standard for time synchronization of computers) for a GPS receiver acquired a few years ago by IAR, which did not have support in such protocol. Today our Institute has a stable and reliable time base synchronized to atomic clocks on board GPS Satellites according to computers's synchronization standard, offering precise time services to all scientific community and particularly to the University of La Plata. FULL TEXT IN SPANISH

  20. Geographically distributed Batch System as a Service: the INDIGO-DataCloud approach exploiting HTCondor

    NASA Astrophysics Data System (ADS)

    Aiftimiei, D. C.; Antonacci, M.; Bagnasco, S.; Boccali, T.; Bucchi, R.; Caballer, M.; Costantini, A.; Donvito, G.; Gaido, L.; Italiano, A.; Michelotto, D.; Panella, M.; Salomoni, D.; Vallero, S.

    2017-10-01

    One of the challenges a scientific computing center has to face is to keep delivering well consolidated computational frameworks (i.e. the batch computing farm), while conforming to modern computing paradigms. The aim is to ease system administration at all levels (from hardware to applications) and to provide a smooth end-user experience. Within the INDIGO- DataCloud project, we adopt two different approaches to implement a PaaS-level, on-demand Batch Farm Service based on HTCondor and Mesos. In the first approach, described in this paper, the various HTCondor daemons are packaged inside pre-configured Docker images and deployed as Long Running Services through Marathon, profiting from its health checks and failover capabilities. In the second approach, we are going to implement an ad-hoc HTCondor framework for Mesos. Container-to-container communication and isolation have been addressed exploring a solution based on overlay networks (based on the Calico Project). Finally, we have studied the possibility to deploy an HTCondor cluster that spans over different sites, exploiting the Condor Connection Broker component, that allows communication across a private network boundary or firewall as in case of multi-site deployments. In this paper, we are going to describe and motivate our implementation choices and to show the results of the first tests performed.

  1. Are Cloud Environments Ready for Scientific Applications?

    NASA Astrophysics Data System (ADS)

    Mehrotra, P.; Shackleford, K.

    2011-12-01

    Cloud computing environments are becoming widely available both in the commercial and government sectors. They provide flexibility to rapidly provision resources in order to meet dynamic and changing computational needs without the customers incurring capital expenses and/or requiring technical expertise. Clouds also provide reliable access to resources even though the end-user may not have in-house expertise for acquiring or operating such resources. Consolidation and pooling in a cloud environment allow organizations to achieve economies of scale in provisioning or procuring computing resources and services. Because of these and other benefits, many businesses and organizations are migrating their business applications (e.g., websites, social media, and business processes) to cloud environments-evidenced by the commercial success of offerings such as the Amazon EC2. In this paper, we focus on the feasibility of utilizing cloud environments for scientific workloads and workflows particularly of interest to NASA scientists and engineers. There is a wide spectrum of such technical computations. These applications range from small workstation-level computations to mid-range computing requiring small clusters to high-performance simulations requiring supercomputing systems with high bandwidth/low latency interconnects. Data-centric applications manage and manipulate large data sets such as satellite observational data and/or data previously produced by high-fidelity modeling and simulation computations. Most of the applications are run in batch mode with static resource requirements. However, there do exist situations that have dynamic demands, particularly ones with public-facing interfaces providing information to the general public, collaborators and partners, as well as to internal NASA users. In the last few months we have been studying the suitability of cloud environments for NASA's technical and scientific workloads. We have ported several applications to multiple cloud environments including NASA's Nebula environment, Amazon's EC2, Magellan at NERSC, and SGI's Cyclone system. We critically examined the performance of the applications on these systems. We also collected information on the usability of these cloud environments. In this talk we will present the results of our study focusing on the efficacy of using clouds for NASA's scientific applications.

  2. Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of data files concurrently. Our experience shows the viability and flexibility of this approach to workflow management for scientific data processing. - Finally, cloud computing is a promising platform for distributed volunteer ('interstitial') computing, via mechanisms such as the Berkeley Open Infrastructure for Network Computing (BOINC) popularized with the SETI@Home project and others such as ClimatePrediction.net and NASA's Climate@Home. Interstitial computing faces significant challenges as commodity computing shifts from (always on) desktop computers towards smartphones and tablets (untethered and running on scarce battery power); but cloud computing offers significant slack capacity. This capacity includes virtual machines with unused RAM or underused CPUs; virtual storage volumes allocated (& paid for) but not full; and virtual machines that are paid up for the current hour but whose work is complete. We are devising ways to facilitate the reuse of these resources (i.e., cloud-based interstitial computing) for satellite data processing and related analyses. We will present our findings and research directions on these and related topics.

  3. Open Access: From Myth to Paradox

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

    Ginsparg, Paul

    2009-05-06

    True open access to scientific publications not only gives readers the possibility to read articles without paying subscription, but also makes the material available for automated ingestion and harvesting by 3rd parties. Once articles and associated data become universally treatable as computable objects, openly available to 3rd party aggregators and value-added services, what new services can we expect, and how will they change the way that researchers interact with their scholarly communications infrastructure? I will discuss straightforward applications of existing ideas and services, including citation analysis, collaborative filtering, external database linkages, interoperability, and other forms of automated markup, and speculatemore » on the sociology of the next generation of users.« less

  4. CASAS: A tool for composing automatically and semantically astrophysical services

    NASA Astrophysics Data System (ADS)

    Louge, T.; Karray, M. H.; Archimède, B.; Knödlseder, J.

    2017-07-01

    Multiple astronomical datasets are available through internet and the astrophysical Distributed Computing Infrastructure (DCI) called Virtual Observatory (VO). Some scientific workflow technologies exist for retrieving and combining data from those sources. However selection of relevant services, automation of the workflows composition and the lack of user-friendly platforms remain a concern. This paper presents CASAS, a tool for semantic web services composition in astrophysics. This tool proposes automatic composition of astrophysical web services and brings a semantics-based, automatic composition of workflows. It widens the services choice and eases the use of heterogeneous services. Semantic web services composition relies on ontologies for elaborating the services composition; this work is based on Astrophysical Services ONtology (ASON). ASON had its structure mostly inherited from the VO services capacities. Nevertheless, our approach is not limited to the VO and brings VO plus non-VO services together without the need for premade recipes. CASAS is available for use through a simple web interface.

  5. Retrospective indexing (RI) - A computer-aided indexing technique

    NASA Technical Reports Server (NTRS)

    Buchan, Ronald L.

    1990-01-01

    An account is given of a method for data base-updating designated 'computer-aided indexing' (CAI) which has been very efficiently implemented at NASA's Scientific and Technical Information Facility by means of retrospective indexing. Novel terms added to the NASA Thesaurus will therefore proceed directly into both the NASA-RECON aerospace information system and its portion of the ESA-Information Retrieval Service, giving users full access to material thus indexed. If a given term appears in the title of a record, it is given special weight. An illustrative graphic representation of the CAI search strategy is presented.

  6. Grid Computing and Collaboration Technology in Support of Fusion Energy Sciences

    NASA Astrophysics Data System (ADS)

    Schissel, D. P.

    2004-11-01

    The SciDAC Initiative is creating a computational grid designed to advance scientific understanding in fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling, and allowing more efficient use of experimental facilities. The philosophy is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as easy to use network available services. Access to services is stressed rather than portability. Services share the same basic security infrastructure so that stakeholders can control their own resources and helps ensure fair use of resources. The collaborative control room is being developed using the open-source Access Grid software that enables secure group-to-group collaboration with capabilities beyond teleconferencing including application sharing and control. The ability to effectively integrate off-site scientists into a dynamic control room will be critical to the success of future international projects like ITER. Grid computing, the secure integration of computer systems over high-speed networks to provide on-demand access to data analysis capabilities and related functions, is being deployed as an alternative to traditional resource sharing among institutions. The first grid computational service deployed was the transport code TRANSP and included tools for run preparation, submission, monitoring and management. This approach saves user sites from the laborious effort of maintaining a complex code while at the same time reducing the burden on developers by avoiding the support of a large number of heterogeneous installations. This tutorial will present the philosophy behind an advanced collaborative environment, give specific examples, and discuss its usage beyond FES.

  7. A web portal for hydrodynamical, cosmological simulations

    NASA Astrophysics Data System (ADS)

    Ragagnin, A.; Dolag, K.; Biffi, V.; Cadolle Bel, M.; Hammer, N. J.; Krukau, A.; Petkova, M.; Steinborn, D.

    2017-07-01

    This article describes a data centre hosting a web portal for accessing and sharing the output of large, cosmological, hydro-dynamical simulations with a broad scientific community. It also allows users to receive related scientific data products by directly processing the raw simulation data on a remote computing cluster. The data centre has a multi-layer structure: a web portal, a job control layer, a computing cluster and a HPC storage system. The outer layer enables users to choose an object from the simulations. Objects can be selected by visually inspecting 2D maps of the simulation data, by performing highly compounded and elaborated queries or graphically by plotting arbitrary combinations of properties. The user can run analysis tools on a chosen object. These services allow users to run analysis tools on the raw simulation data. The job control layer is responsible for handling and performing the analysis jobs, which are executed on a computing cluster. The innermost layer is formed by a HPC storage system which hosts the large, raw simulation data. The following services are available for the users: (I) CLUSTERINSPECT visualizes properties of member galaxies of a selected galaxy cluster; (II) SIMCUT returns the raw data of a sub-volume around a selected object from a simulation, containing all the original, hydro-dynamical quantities; (III) SMAC creates idealized 2D maps of various, physical quantities and observables of a selected object; (IV) PHOX generates virtual X-ray observations with specifications of various current and upcoming instruments.

  8. A framework for integration of scientific applications into the OpenTopography workflow

    NASA Astrophysics Data System (ADS)

    Nandigam, V.; Crosby, C.; Baru, C.

    2012-12-01

    The NSF-funded OpenTopography facility provides online access to Earth science-oriented high-resolution LIDAR topography data, online processing tools, and derivative products. The underlying cyberinfrastructure employs a multi-tier service oriented architecture that is comprised of an infrastructure tier, a processing services tier, and an application tier. The infrastructure tier consists of storage, compute resources as well as supporting databases. The services tier consists of the set of processing routines each deployed as a Web service. The applications tier provides client interfaces to the system. (e.g. Portal). We propose a "pluggable" infrastructure design that will allow new scientific algorithms and processing routines developed and maintained by the community to be integrated into the OpenTopography system so that the wider earth science community can benefit from its availability. All core components in OpenTopography are available as Web services using a customized open-source Opal toolkit. The Opal toolkit provides mechanisms to manage and track job submissions, with the help of a back-end database. It allows monitoring of job and system status by providing charting tools. All core components in OpenTopography have been developed, maintained and wrapped as Web services using Opal by OpenTopography developers. However, as the scientific community develops new processing and analysis approaches this integration approach is not scalable efficiently. Most of the new scientific applications will have their own active development teams performing regular updates, maintenance and other improvements. It would be optimal to have the application co-located where its developers can continue to actively work on it while still making it accessible within the OpenTopography workflow for processing capabilities. We will utilize a software framework for remote integration of these scientific applications into the OpenTopography system. This will be accomplished by virtually extending the OpenTopography service over the various infrastructures running these scientific applications and processing routines. This involves packaging and distributing a customized instance of the Opal toolkit that will wrap the software application as an OPAL-based web service and integrate it into the OpenTopography framework. We plan to make this as automated as possible. A structured specification of service inputs and outputs along with metadata annotations encoded in XML can be utilized to automate the generation of user interfaces, with appropriate tools tips and user help features, and generation of other internal software. The OpenTopography Opal toolkit will also include the customizations that will enable security authentication, authorization and the ability to write application usage and job statistics back to the OpenTopography databases. This usage information could then be reported to the original service providers and used for auditing and performance improvements. This pluggable framework will enable the application developers to continue to work on enhancing their application while making the latest iteration available in a timely manner to the earth sciences community. This will also help us establish an overall framework that other scientific application providers will also be able to use going forward.

  9. BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology.

    PubMed

    Hardisty, Alex R; Bacall, Finn; Beard, Niall; Balcázar-Vargas, Maria-Paula; Balech, Bachir; Barcza, Zoltán; Bourlat, Sarah J; De Giovanni, Renato; de Jong, Yde; De Leo, Francesca; Dobor, Laura; Donvito, Giacinto; Fellows, Donal; Guerra, Antonio Fernandez; Ferreira, Nuno; Fetyukova, Yuliya; Fosso, Bruno; Giddy, Jonathan; Goble, Carole; Güntsch, Anton; Haines, Robert; Ernst, Vera Hernández; Hettling, Hannes; Hidy, Dóra; Horváth, Ferenc; Ittzés, Dóra; Ittzés, Péter; Jones, Andrew; Kottmann, Renzo; Kulawik, Robert; Leidenberger, Sonja; Lyytikäinen-Saarenmaa, Päivi; Mathew, Cherian; Morrison, Norman; Nenadic, Aleksandra; de la Hidalga, Abraham Nieva; Obst, Matthias; Oostermeijer, Gerard; Paymal, Elisabeth; Pesole, Graziano; Pinto, Salvatore; Poigné, Axel; Fernandez, Francisco Quevedo; Santamaria, Monica; Saarenmaa, Hannu; Sipos, Gergely; Sylla, Karl-Heinz; Tähtinen, Marko; Vicario, Saverio; Vos, Rutger Aldo; Williams, Alan R; Yilmaz, Pelin

    2016-10-20

    Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.

  10. Ontology-aided Data Fusion (Invited)

    NASA Astrophysics Data System (ADS)

    Raskin, R.

    2009-12-01

    An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

  11. Supporting the scientific lifecycle through cloud services

    NASA Astrophysics Data System (ADS)

    Gensch, S.; Klump, J. F.; Bertelmann, R.; Braune, C.

    2014-12-01

    Cloud computing has made resources and applications available for numerous use cases ranging from business processes in the private sector to scientific applications. Developers have created tools for data management, collaborative writing, social networking, data access and visualization, project management and many more; either for free or as paid premium services with additional or extended features. Scientists have begun to incorporate tools that fit their needs into their daily work. To satisfy specialized needs, some cloud applications specifically address the needs of scientists for sharing research data, literature search, laboratory documentation, or data visualization. Cloud services may vary in extent, user coverage, and inter-service integration and are also at risk of being abandonend or changed by the service providers making changes to their business model, or leaving the field entirely.Within the project Academic Enterprise Cloud we examine cloud based services that support the research lifecycle, using feature models to describe key properties in the areas of infrastructure and service provision, compliance to legal regulations, and data curation. Emphasis is put on the term Enterprise as to establish an academic cloud service provider infrastructure that satisfies demands of the research community through continious provision across the whole cloud stack. This could enable the research community to be independent from service providers regarding changes to terms of service and ensuring full control of its extent and usage. This shift towards a self-empowered scientific cloud provider infrastructure and its community raises implications about feasability of provision and overall costs. Legal aspects and licensing issues have to be considered, when moving data into cloud services, especially when personal data is involved.Educating researchers about cloud based tools is important to help in the transition towards effective and safe use. Scientists can benefit from the provision of standard services, like weblog and website creation, virtual machine deployments, and groupware provision using cloud based app store-like portals. And, other than in an industrial environment, researchers will want to keep their existing user profile when moving from one institution to another.

  12. The Centre of High-Performance Scientific Computing, Geoverbund, ABC/J - Geosciences enabled by HPSC

    NASA Astrophysics Data System (ADS)

    Kollet, Stefan; Görgen, Klaus; Vereecken, Harry; Gasper, Fabian; Hendricks-Franssen, Harrie-Jan; Keune, Jessica; Kulkarni, Ketan; Kurtz, Wolfgang; Sharples, Wendy; Shrestha, Prabhakar; Simmer, Clemens; Sulis, Mauro; Vanderborght, Jan

    2016-04-01

    The Centre of High-Performance Scientific Computing (HPSC TerrSys) was founded 2011 to establish a centre of competence in high-performance scientific computing in terrestrial systems and the geosciences enabling fundamental and applied geoscientific research in the Geoverbund ABC/J (geoscientfic research alliance of the Universities of Aachen, Cologne, Bonn and the Research Centre Jülich, Germany). The specific goals of HPSC TerrSys are to achieve relevance at the national and international level in (i) the development and application of HPSC technologies in the geoscientific community; (ii) student education; (iii) HPSC services and support also to the wider geoscientific community; and in (iv) the industry and public sectors via e.g., useful applications and data products. A key feature of HPSC TerrSys is the Simulation Laboratory Terrestrial Systems, which is located at the Jülich Supercomputing Centre (JSC) and provides extensive capabilities with respect to porting, profiling, tuning and performance monitoring of geoscientific software in JSC's supercomputing environment. We will present a summary of success stories of HPSC applications including integrated terrestrial model development, parallel profiling and its application from watersheds to the continent; massively parallel data assimilation using physics-based models and ensemble methods; quasi-operational terrestrial water and energy monitoring; and convection permitting climate simulations over Europe. The success stories stress the need for a formalized education of students in the application of HPSC technologies in future.

  13. Provenance-Powered Automatic Workflow Generation and Composition

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Lee, S.; Pan, L.; Lee, T. J.

    2015-12-01

    In recent years, scientists have learned how to codify tools into reusable software modules that can be chained into multi-step executable workflows. Existing scientific workflow tools, created by computer scientists, require domain scientists to meticulously design their multi-step experiments before analyzing data. However, this is oftentimes contradictory to a domain scientist's daily routine of conducting research and exploration. We hope to resolve this dispute. Imagine this: An Earth scientist starts her day applying NASA Jet Propulsion Laboratory (JPL) published climate data processing algorithms over ARGO deep ocean temperature and AMSRE sea surface temperature datasets. Throughout the day, she tunes the algorithm parameters to study various aspects of the data. Suddenly, she notices some interesting results. She then turns to a computer scientist and asks, "can you reproduce my results?" By tracking and reverse engineering her activities, the computer scientist creates a workflow. The Earth scientist can now rerun the workflow to validate her findings, modify the workflow to discover further variations, or publish the workflow to share the knowledge. In this way, we aim to revolutionize computer-supported Earth science. We have developed a prototyping system to realize the aforementioned vision, in the context of service-oriented science. We have studied how Earth scientists conduct service-oriented data analytics research in their daily work, developed a provenance model to record their activities, and developed a technology to automatically generate workflow starting from user behavior and adaptability and reuse of these workflows for replicating/improving scientific studies. A data-centric repository infrastructure is established to catch richer provenance to further facilitate collaboration in the science community. We have also established a Petri nets-based verification instrument for provenance-based automatic workflow generation and recommendation.

  14. Evolving the Technical Infrastructure of the Planetary Data System for the 21st Century

    NASA Technical Reports Server (NTRS)

    Beebe, Reta F.; Crichton, D.; Hughes, S.; Grayzeck, E.

    2010-01-01

    The Planetary Data System (PDS) was established in 1989 as a distributed system to assure scientific oversight. Initially the PDS followed guidelines recommended by the National Academies Committee on Data Management and Computation (CODMAC, 1982) and placed emphasis on archiving validated datasets. But overtime user demands, supported by increased computing capabilities and communication methods, have placed increasing demands on the PDS. The PDS must add additional services to better enable scientific analysis within distributed environments and to ensure that those services integrate with existing systems and data. To face these challenges the Planetary Data System (PDS) must modernize its architecture and technical implementation. The PDS 2010 project addresses these challenges. As part of this project, the PDS has three fundamental project goals that include: (1) Providing more efficient client delivery of data by data providers to the PDS (2) Enabling a stable, long-term usable planetary science data archive (3) Enabling services for the data consumer to find, access and use the data they require in contemporary data formats. In order to achieve these goals, the PDS 2010 project is upgrading both the technical infrastructure and the data standards to support increased efficiency in data delivery as well as usability of the PDS. Efforts are underway to interface with missions as early as possible and to streamline the preparation and delivery of data to the PDS. Likewise, the PDS is working to define and plan for data services that will help researchers to perform analysis in cost-constrained environments. This presentation will cover the PDS 2010 project including the goals, data standards and technical implementation plans that are underway within the Planetary Data System. It will discuss the plans for moving from the current system, version PDS 3, to version PDS 4.

  15. The GENIUS Grid Portal and robot certificates: a new tool for e-Science

    PubMed Central

    Barbera, Roberto; Donvito, Giacinto; Falzone, Alberto; La Rocca, Giuseppe; Milanesi, Luciano; Maggi, Giorgio Pietro; Vicario, Saverio

    2009-01-01

    Background Grid technology is the computing model which allows users to share a wide pletora of distributed computational resources regardless of their geographical location. Up to now, the high security policy requested in order to access distributed computing resources has been a rather big limiting factor when trying to broaden the usage of Grids into a wide community of users. Grid security is indeed based on the Public Key Infrastructure (PKI) of X.509 certificates and the procedure to get and manage those certificates is unfortunately not straightforward. A first step to make Grids more appealing for new users has recently been achieved with the adoption of robot certificates. Methods Robot certificates have recently been introduced to perform automated tasks on Grids on behalf of users. They are extremely useful for instance to automate grid service monitoring, data processing production, distributed data collection systems. Basically these certificates can be used to identify a person responsible for an unattended service or process acting as client and/or server. Robot certificates can be installed on a smart card and used behind a portal by everyone interested in running the related applications in a Grid environment using a user-friendly graphic interface. In this work, the GENIUS Grid Portal, powered by EnginFrame, has been extended in order to support the new authentication based on the adoption of these robot certificates. Results The work carried out and reported in this manuscript is particularly relevant for all users who are not familiar with personal digital certificates and the technical aspects of the Grid Security Infrastructure (GSI). The valuable benefits introduced by robot certificates in e-Science can so be extended to users belonging to several scientific domains, providing an asset in raising Grid awareness to a wide number of potential users. Conclusion The adoption of Grid portals extended with robot certificates, can really contribute to creating transparent access to computational resources of Grid Infrastructures, enhancing the spread of this new paradigm in researchers' working life to address new global scientific challenges. The evaluated solution can of course be extended to other portals, applications and scientific communities. PMID:19534747

  16. The GENIUS Grid Portal and robot certificates: a new tool for e-Science.

    PubMed

    Barbera, Roberto; Donvito, Giacinto; Falzone, Alberto; La Rocca, Giuseppe; Milanesi, Luciano; Maggi, Giorgio Pietro; Vicario, Saverio

    2009-06-16

    Grid technology is the computing model which allows users to share a wide pletora of distributed computational resources regardless of their geographical location. Up to now, the high security policy requested in order to access distributed computing resources has been a rather big limiting factor when trying to broaden the usage of Grids into a wide community of users. Grid security is indeed based on the Public Key Infrastructure (PKI) of X.509 certificates and the procedure to get and manage those certificates is unfortunately not straightforward. A first step to make Grids more appealing for new users has recently been achieved with the adoption of robot certificates. Robot certificates have recently been introduced to perform automated tasks on Grids on behalf of users. They are extremely useful for instance to automate grid service monitoring, data processing production, distributed data collection systems. Basically these certificates can be used to identify a person responsible for an unattended service or process acting as client and/or server. Robot certificates can be installed on a smart card and used behind a portal by everyone interested in running the related applications in a Grid environment using a user-friendly graphic interface. In this work, the GENIUS Grid Portal, powered by EnginFrame, has been extended in order to support the new authentication based on the adoption of these robot certificates. The work carried out and reported in this manuscript is particularly relevant for all users who are not familiar with personal digital certificates and the technical aspects of the Grid Security Infrastructure (GSI). The valuable benefits introduced by robot certificates in e-Science can so be extended to users belonging to several scientific domains, providing an asset in raising Grid awareness to a wide number of potential users. The adoption of Grid portals extended with robot certificates, can really contribute to creating transparent access to computational resources of Grid Infrastructures, enhancing the spread of this new paradigm in researchers' working life to address new global scientific challenges. The evaluated solution can of course be extended to other portals, applications and scientific communities.

  17. 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.

  18. [HyperPsych--resources for medicine and psychology on the World Wide Web].

    PubMed

    Laszig, P

    1997-07-01

    Progress in the research of interactive communication technology and the acceleration of processing and transmitting information have promoted the development of computer networks allowing global access to scientific information and services. The recently most well-known net is the internet. Based on its integrative structure as a communication-directed as well as an information-directed medium, the internet helps researchers design scientific research. Especially medicine and psychology as information-dependent scientific disciplines may profit by using this technological offer. As a method to coordinate to the vast amount of medical and psychological data around the globe and to communicate with researchers world-wide, it enhances innovative possibilities for research, diagnosis and therapy. Currently, the World Wide Web is regarded as the most user-friendly and practical of all the internet resources. Based on a systematic introduction to the applications of the WWW, this article discusses relevant resources, points out possibilities and limits of network-supported scientific research and proposes many uses of this new medium.

  19. XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

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

    Moreland, Kenneth D.; Pugmire, David; Rogers, David

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

  20. XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

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

    Moreland, Kenneth D.; Pugmire, David; Rogers, David

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

  1. XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

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

    Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

  2. XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

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

    Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  4. 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.

  5. A Simple XML Producer-Consumer Protocol

    NASA Technical Reports Server (NTRS)

    Smith, Warren; Gunter, Dan; Quesnel, Darcy; Biegel, Bryan (Technical Monitor)

    2001-01-01

    There are many different projects from government, academia, and industry that provide services for delivering events in distributed environments. The problem with these event services is that they are not general enough to support all uses and they speak different protocols so that they cannot interoperate. We require such interoperability when we, for example, wish to analyze the performance of an application in a distributed environment. Such an analysis might require performance information from the application, computer systems, networks, and scientific instruments. In this work we propose and evaluate a standard XML-based protocol for the transmission of events in distributed systems. One recent trend in government and academic research is the development and deployment of computational grids. Computational grids are large-scale distributed systems that typically consist of high-performance compute, storage, and networking resources. Examples of such computational grids are the DOE Science Grid, the NASA Information Power Grid (IPG), and the NSF Partnerships for Advanced Computing Infrastructure (PACIs). The major effort to deploy these grids is in the area of developing the software services to allow users to execute applications on these large and diverse sets of resources. These services include security, execution of remote applications, managing remote data, access to information about resources and services, and so on. There are several toolkits for providing these services such as Globus, Legion, and Condor. As part of these efforts to develop computational grids, the Global Grid Forum is working to standardize the protocols and APIs used by various grid services. This standardization will allow interoperability between the client and server software of the toolkits that are providing the grid services. The goal of the Performance Working Group of the Grid Forum is to standardize protocols and representations related to the storage and distribution of performance data. These standard protocols and representations must support tasks such as profiling parallel applications, monitoring the status of computers and networks, and monitoring the performance of services provided by a computational grid. This paper describes a proposed protocol and data representation for the exchange of events in a distributed system. The protocol exchanges messages formatted in XML and it can be layered atop any low-level communication protocol such as TCP or UDP Further, we describe Java and C++ implementations of this protocol and discuss their performance. The next section will provide some further background information. Section 3 describes the main communication patterns of our protocol. Section 4 describes how we represent events and related information using XML. Section 5 describes our protocol and Section 6 discusses the performance of two implementations of the protocol. Finally, an appendix provides the XML Schema definition of our protocol and event information.

  6. ATLAS computing on Swiss Cloud SWITCHengines

    NASA Astrophysics Data System (ADS)

    Haug, S.; Sciacca, F. G.; ATLAS Collaboration

    2017-10-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  7. Molecular structure input on the web.

    PubMed

    Ertl, Peter

    2010-02-02

    A molecule editor, that is program for input and editing of molecules, is an indispensable part of every cheminformatics or molecular processing system. This review focuses on a special type of molecule editors, namely those that are used for molecule structure input on the web. Scientific computing is now moving more and more in the direction of web services and cloud computing, with servers scattered all around the Internet. Thus a web browser has become the universal scientific user interface, and a tool to edit molecules directly within the web browser is essential.The review covers a history of web-based structure input, starting with simple text entry boxes and early molecule editors based on clickable maps, before moving to the current situation dominated by Java applets. One typical example - the popular JME Molecule Editor - will be described in more detail. Modern Ajax server-side molecule editors are also presented. And finally, the possible future direction of web-based molecule editing, based on technologies like JavaScript and Flash, is discussed.

  8. Challenges in integrating multidisciplinary data into a single e-infrastructure

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Hubble Space Telescope servicing mission scientific instrument protective enclosure design requirements and contamination controls

    NASA Technical Reports Server (NTRS)

    Hansen, Patricia A.; Hughes, David W.; Hedgeland, Randy J.; Chivatero, Craig J.; Studer, Robert J.; Kostos, Peter J.

    1994-01-01

    The Scientific Instrument Protective Enclosures were designed for the Hubble Space Telescope Servicing Missions to provide a beginning environment to a Scientific Instrument during ground and on orbit activities. The Scientific Instruments required very stringent surface cleanliness and molecular outgassing levels to maintain ultraviolet performance. Data from the First Servicing Mission verified that both the Scientific Instruments and Scientific Instrument Protective Enclosures met surface cleanliness level requirements during ground and on-orbit activities.

  10. Open Marketplace for Simulation Software on the Basis of a Web Platform

    NASA Astrophysics Data System (ADS)

    Kryukov, A. P.; Demichev, A. P.

    2016-02-01

    The focus in development of a new generation of middleware shifts from the global grid systems to building convenient and efficient web platforms for remote access to individual computing resources. Further line of their development, suggested in this work, is related not only with the quantitative increase in their number and with the expansion of scientific, engineering, and manufacturing areas in which they are used, but also with improved technology for remote deployment of application software on the resources interacting with the web platforms. Currently, the services for providers of application software in the context of scientific-oriented web platforms is not developed enough. The proposed in this work new web platforms of application software market should have all the features of the existing web platforms for submissions of jobs to remote resources plus the provision of specific web services for interaction on market principles between the providers and consumers of application packages. The suggested approach will be approved on the example of simulation applications in the field of nonlinear optics.

  11. Large Spatial Scale Ground Displacement Mapping through the P-SBAS Processing of Sentinel-1 Data on a Cloud Computing Environment

    NASA Astrophysics Data System (ADS)

    Casu, F.; Bonano, M.; de Luca, C.; Lanari, R.; Manunta, M.; Manzo, M.; Zinno, I.

    2017-12-01

    Since its launch in 2014, the Sentinel-1 (S1) constellation has played a key role on SAR data availability and dissemination all over the World. Indeed, the free and open access data policy adopted by the European Copernicus program together with the global coverage acquisition strategy, make the Sentinel constellation as a game changer in the Earth Observation scenario. Being the SAR data become ubiquitous, the technological and scientific challenge is focused on maximizing the exploitation of such huge data flow. In this direction, the use of innovative processing algorithms and distributed computing infrastructures, such as the Cloud Computing platforms, can play a crucial role. In this work we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing S1 Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation time series in efficient, automatic and systematic way. Such a DInSAR chain ingests Sentinel 1 SLC images and carries out several processing steps, to finally compute deformation time series and mean deformation velocity maps. Different parallel strategies have been designed ad hoc for each processing step of the P-SBAS S1 chain, encompassing both multi-core and multi-node programming techniques, in order to maximize the computational efficiency achieved within a Cloud Computing environment and cut down the relevant processing times. The presented P-SBAS S1 processing chain has been implemented on the Amazon Web Services platform and a thorough analysis of the attained parallel performances has been performed to identify and overcome the major bottlenecks to the scalability. The presented approach is used to perform national-scale DInSAR analyses over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Such an experiment confirms the big advantage of exploiting large computational and storage resources of Cloud Computing platforms for large scale DInSAR analysis. The presented Cloud Computing P-SBAS processing chain can be a precious tool in the perspective of developing operational services disposable for the EO scientific community related to hazard monitoring and risk prevention and mitigation.

  12. 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.

  13. Publication of science data on CD-ROM: A guide and example

    NASA Technical Reports Server (NTRS)

    Angelici, Gary; Skiles, J. W.

    1993-01-01

    CD-ROM (Compact Disk-Read Only Memory) is becoming the standard media not only in audio recording, but also in the publication of data and information accessible on many computer platforms. Little has been written about the complicated process involved in creating easy-to-use, high quality, and useful CD-ROM's containing scientific data. This document is a manual designed to aid those who are responsible for the publication of scientific data on CD-ROM. All aspects and steps of the procedure are covered, from feasibility assessment through disk design, data preparation, disc mastering, and CD-ROM distribution. General advice and actual examples are based on lessons learned from the publication of scientific data for an interdisciplinary field experiment. Appendices include actual files from a CD-ROM, a purchase request for CD-ROM mastering services, and the disk art for the first disk published for the project.

  14. ASI's space automation and robotics programs: The second step

    NASA Technical Reports Server (NTRS)

    Dipippo, Simonetta

    1994-01-01

    The strategic decisions taken by ASI in the last few years in building up the overall A&R program, represent the technological drivers for other applications (i.e., internal automation of the Columbus Orbital Facility in the ESA Manned Space program, applications to mobile robots both in space and non-space environments, etc...). In this context, the main area of application now emerging is the scientific missions domain. Due to the broad range of applications of the developed technologies, both in the in-orbit servicing and maintenance of space structures and scientific missions, ASI foresaw the need to have a common technological development path, mainly focusing on: (1) control; (2) manipulation; (3) on-board computing; (4) sensors; and (5) teleoperation. Before entering into new applications in the scientific missions field, a brief overview of the status of the SPIDER related projects is given, underlining also the possible new applications for the LEO/GEO space structures.

  15. 75 FR 65404 - Rehabilitation Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-22

    ... DEPARTMENT OF VETERANS AFFAIRS Rehabilitation Research and Development Service Scientific Merit... & Regenerative Medicine Subcommittee of the Rehabilitation Research and Development Service Scientific Merit..., examination, reference to, [[Page 65405

  16. A European Federated Cloud: Innovative distributed computing solutions by EGI

    NASA Astrophysics Data System (ADS)

    Sipos, Gergely; Turilli, Matteo; Newhouse, Steven; Kacsuk, Peter

    2013-04-01

    The European Grid Infrastructure (EGI) is the result of pioneering work that has, over the last decade, built a collaborative production infrastructure of uniform services through the federation of national resource providers that supports multi-disciplinary science across Europe and around the world. This presentation will provide an overview of the recently established 'federated cloud computing services' that the National Grid Initiatives (NGIs), operators of EGI, offer to scientific communities. The presentation will explain the technical capabilities of the 'EGI Federated Cloud' and the processes whereby earth and space science researchers can engage with it. EGI's resource centres have been providing services for collaborative, compute- and data-intensive applications for over a decade. Besides the well-established 'grid services', several NGIs already offer privately run cloud services to their national researchers. Many of these researchers recently expressed the need to share these cloud capabilities within their international research collaborations - a model similar to the way the grid emerged through the federation of institutional batch computing and file storage servers. To facilitate the setup of a pan-European cloud service from the NGIs' resources, the EGI-InSPIRE project established a Federated Cloud Task Force in September 2011. The Task Force has a mandate to identify and test technologies for a multinational federated cloud that could be provisioned within EGI by the NGIs. A guiding principle for the EGI Federated Cloud is to remain technology neutral and flexible for both resource providers and users: • Resource providers are allowed to use any cloud hypervisor and management technology to join virtualised resources into the EGI Federated Cloud as long as the site is subscribed to the user-facing interfaces selected by the EGI community. • Users can integrate high level services - such as brokers, portals and customised Virtual Research Environments - with the EGI Federated Cloud as long as these services access cloud resources through the user-facing interfaces selected by the EGI community. The Task Force will be closed in May 2013. It already • Identified key enabling technologies by which a multinational, federated 'Infrastructure as a Service' (IaaS) type cloud can be built from the NGIs' resources; • Deployed a test bed to evaluate the integration of virtualised resources within EGI and to engage with early adopter use cases from different scientific domains; • Integrated cloud resources into the EGI production infrastructure through cloud specific bindings of the EGI information system, monitoring system, authentication system, etc.; • Collected and catalogued requirements concerning the federated cloud services from the feedback of early adopter use cases; • Provided feedback and requirements to relevant technology providers on their implementations and worked with these providers to address those requirements; • Identified issues that need to be addressed by other areas of EGI (such as portal solutions, resource allocation policies, marketing and user support) to reach a production system. The Task Force will publish a blueprint in April 2013. The blueprint will drive the establishment of a production level EGI Federated Cloud service after May 2013.

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

    USGS Publications Warehouse

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

    2016-01-01

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

  18. 78 FR 12422 - Health Services Research and Development Service Scientific Merit Review Board, Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-22

    ... DEPARTMENT OF VETERANS AFFAIRS Health Services Research and Development Service Scientific Merit... nursing research. Applications are reviewed for scientific and technical merit, mission relevance, and the... recommendations will include qualifications of the personnel conducting the studies as well as research...

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

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

    Kostadin, Damevski

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

  20. Computational Science: A Research Methodology for the 21st Century

    NASA Astrophysics Data System (ADS)

    Orbach, Raymond L.

    2004-03-01

    Computational simulation - a means of scientific discovery that employs computer systems to simulate a physical system according to laws derived from theory and experiment - has attained peer status with theory and experiment. Important advances in basic science are accomplished by a new "sociology" for ultrascale scientific computing capability (USSCC), a fusion of sustained advances in scientific models, mathematical algorithms, computer architecture, and scientific software engineering. Expansion of current capabilities by factors of 100 - 1000 open up new vistas for scientific discovery: long term climatic variability and change, macroscopic material design from correlated behavior at the nanoscale, design and optimization of magnetic confinement fusion reactors, strong interactions on a computational lattice through quantum chromodynamics, and stellar explosions and element production. The "virtual prototype," made possible by this expansion, can markedly reduce time-to-market for industrial applications such as jet engines and safer, more fuel efficient cleaner cars. In order to develop USSCC, the National Energy Research Scientific Computing Center (NERSC) announced the competition "Innovative and Novel Computational Impact on Theory and Experiment" (INCITE), with no requirement for current DOE sponsorship. Fifty nine proposals for grand challenge scientific problems were submitted for a small number of awards. The successful grants, and their preliminary progress, will be described.

  1. The EGI-Engage EPOS Competence Center - Interoperating heterogeneous AAI mechanisms and Orchestrating distributed computational resources

    NASA Astrophysics Data System (ADS)

    Bailo, Daniele; Scardaci, Diego; Spinuso, Alessandro; Sterzel, Mariusz; Schwichtenberg, Horst; Gemuend, Andre

    2016-04-01

    The mission of EGI-Engage project [1] is to accelerate the implementation of the Open Science Commons vision, where researchers from all disciplines have easy and open access to the innovative digital services, data, knowledge and expertise they need for collaborative and excellent research. The Open Science Commons is grounded on three pillars: the e-Infrastructure Commons, an ecosystem of services that constitute the foundation layer of distributed infrastructures; the Open Data Commons, where observations, results and applications are increasingly available for scientific research and for anyone to use and reuse; and the Knowledge Commons, in which communities have shared ownership of knowledge, participate in the co-development of software and are technically supported to exploit state-of-the-art digital services. To develop the Knowledge Commons, EGI-Engage is supporting the work of a set of community-specific Competence Centres, with participants from user communities (scientific institutes), National Grid Initiatives (NGIs), technology and service providers. Competence Centres collect and analyse requirements, integrate community-specific applications into state-of-the-art services, foster interoperability across e-Infrastructures, and evolve services through a user-centric development model. One of these Competence Centres is focussed on the European Plate Observing System (EPOS) [2] as representative of the solid earth science communities. EPOS is a pan-European long-term plan to integrate data, software and services from the distributed (and already existing) Research Infrastructures all over Europe, in the domain of the solid earth science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. EPOS will improve our ability to better manage the use of the subsurface of the Earth. EPOS started its Implementation Phase in October 2015 and is now actively working in order to integrate multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) - European wide organizations and e-Infrastructure providing community specific data and data products - and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. TCS data, data products and services will be integrated into the Integrated Core Services (ICS) system, that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. The EPOS competence center (EPOS CC) goal is to tackle two of the main challenges that the ICS are going to face in the near future, by taking advantage of the technical solutions provided by EGI. In order to do this, we will present the two pilot use cases the EGI-EPOS CC is developing: 1) The AAI pilot, dealing with the provision of transparent and homogeneous access to the ICS infrastructure to users owning different kind of credentials (e.g. eduGain, OpenID Connect, X509 certificates etc.). Here the focus is on the mechanisms which allow the credential delegation. 2) The computational pilot, Improve the back-end services of an existing application in the field of Computational Seismology, developed in the context of the EC funded project VERCE. The application allows the processing and the comparison of data resulting from the simulation of seismic wave propagation following a real earthquake and real measurements recorded by seismographs. While the simulation data is produced directly by the users and stored in a Data Management System, the observations need to be pre-staged from institutional data-services, which are maintained by the community itself. This use case aims at exploiting the EGI FedCloud e-infrastructure for Data Intensive analysis and also explores possible interaction with other Common Data Infrastructure initiatives as EUDAT. In the presentation, the state of the art of the two use cases, together with the open challenges and the future application will be discussed. Also, possible integration of EGI solutions with EPOS and other e-infrastructure providers will be considered. [1] EGI-ENGAGE https://www.egi.eu/about/egi-engage/ [2] EPOS http://www.epos-eu.org/

  2. High-throughput neuroimaging-genetics computational infrastructure

    PubMed Central

    Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

    2014-01-01

    Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure1. PMID:24795619

  3. XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

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

    Geveci, Berk; Maynard, Robert

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respectivemore » features into a new visualization toolkit called VTK-m.« less

  4. Developing science gateways for drug discovery in a grid environment.

    PubMed

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

    2016-01-01

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

  5. Joint the Center for Applied Scientific Computing

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

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

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

  6. Enhancing UCSF Chimera through web services

    PubMed Central

    Huang, Conrad C.; Meng, Elaine C.; Morris, John H.; Pettersen, Eric F.; Ferrin, Thomas E.

    2014-01-01

    Integrating access to web services with desktop applications allows for an expanded set of application features, including performing computationally intensive tasks and convenient searches of databases. We describe how we have enhanced UCSF Chimera (http://www.rbvi.ucsf.edu/chimera/), a program for the interactive visualization and analysis of molecular structures and related data, through the addition of several web services (http://www.rbvi.ucsf.edu/chimera/docs/webservices.html). By streamlining access to web services, including the entire job submission, monitoring and retrieval process, Chimera makes it simpler for users to focus on their science projects rather than data manipulation. Chimera uses Opal, a toolkit for wrapping scientific applications as web services, to provide scalable and transparent access to several popular software packages. We illustrate Chimera's use of web services with an example workflow that interleaves use of these services with interactive manipulation of molecular sequences and structures, and we provide an example Python program to demonstrate how easily Opal-based web services can be accessed from within an application. Web server availability: http://webservices.rbvi.ucsf.edu/opal2/dashboard?command=serviceList. PMID:24861624

  7. 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.

  8. SCEAPI: A unified Restful Web API for High-Performance Computing

    NASA Astrophysics Data System (ADS)

    Rongqiang, Cao; Haili, Xiao; Shasha, Lu; Yining, Zhao; Xiaoning, Wang; Xuebin, Chi

    2017-10-01

    The development of scientific computing is increasingly moving to collaborative web and mobile applications. All these applications need high-quality programming interface for accessing heterogeneous computing resources consisting of clusters, grid computing or cloud computing. In this paper, we introduce our high-performance computing environment that integrates computing resources from 16 HPC centers across China. Then we present a bundle of web services called SCEAPI and describe how it can be used to access HPC resources with HTTP or HTTPs protocols. We discuss SCEAPI from several aspects including architecture, implementation and security, and address specific challenges in designing compatible interfaces and protecting sensitive data. We describe the functions of SCEAPI including authentication, file transfer and job management for creating, submitting and monitoring, and how to use SCEAPI in an easy-to-use way. Finally, we discuss how to exploit more HPC resources quickly for the ATLAS experiment by implementing the custom ARC compute element based on SCEAPI, and our work shows that SCEAPI is an easy-to-use and effective solution to extend opportunistic HPC resources.

  9. Pre-Service Science Teachers in Xinjiang "Scientific Inquiry" - Pedagogical Content Knowledge Research

    ERIC Educational Resources Information Center

    Li, Yufeng; Xiong, Jianwen

    2012-01-01

    Scientific inquiry is one of the science curriculum content, "Scientific inquiry" - Pedagogical Content Knowledge is the face of scientific inquiry and teachers - of course pedagogical content knowledge and scientific inquiry a teaching practice with more direct expertise. Pre-service teacher training phase of acquisition of knowledge is…

  10. Whole earth modeling: developing and disseminating scientific software for computational geophysics.

    NASA Astrophysics Data System (ADS)

    Kellogg, L. H.

    2016-12-01

    Historically, a great deal of specialized scientific software for modeling and data analysis has been developed by individual researchers or small groups of scientists working on their own specific research problems. As the magnitude of available data and computer power has increased, so has the complexity of scientific problems addressed by computational methods, creating both a need to sustain existing scientific software, and expand its development to take advantage of new algorithms, new software approaches, and new computational hardware. To that end, communities like the Computational Infrastructure for Geodynamics (CIG) have been established to support the use of best practices in scientific computing for solid earth geophysics research and teaching. Working as a scientific community enables computational geophysicists to take advantage of technological developments, improve the accuracy and performance of software, build on prior software development, and collaborate more readily. The CIG community, and others, have adopted an open-source development model, in which code is developed and disseminated by the community in an open fashion, using version control and software repositories like Git. One emerging issue is how to adequately identify and credit the intellectual contributions involved in creating open source scientific software. The traditional method of disseminating scientific ideas, peer reviewed publication, was not designed for review or crediting scientific software, although emerging publication strategies such software journals are attempting to address the need. We are piloting an integrated approach in which authors are identified and credited as scientific software is developed and run. Successful software citation requires integration with the scholarly publication and indexing mechanisms as well, to assign credit, ensure discoverability, and provide provenance for software.

  11. Integrating Research and Education at the National Center for Atmospheric Research at the Interface of Formal and Informal Education

    NASA Astrophysics Data System (ADS)

    Johnson, R.; Foster, S.

    2005-12-01

    The National Center for Atmospheric Research (NCAR) in Boulder, Colorado, is a leading institution in scientific research, education and service associated with exploring and understanding our atmosphere and its interactions with the Sun, the oceans, the biosphere, and human society. NCAR draws thousands of public and scientific visitors from around the world to its Mesa Laboratory facility annually for educational as well as research purposes. Public visitors include adult visitors, clubs, and families on an informal visit to NCAR and its exhibits, as well as classroom and summer camp groups. Additionally, NCAR provides extensive computational and visualization services, which can be used not only for scientific, but also public informational purposes. As such, NCAR's audience provides an opportunity to address both formal and informal education through the programs that we offer. The University Corporation for Atmospheric Research (UCAR) Office of Education and Outreach works with NCAR to develop and implement a highly-integrated strategy for reaching both formal and informal audiences through programs that range from events and exhibits to professional development (for scientists and educators) and bilingual distance learning. The hallmarks of our program include close collaboration with scientists, multi-purposing resources where appropriate for maximum efficiency, and a commitment to engage populations historically underrepresented in science in the geosciences.

  12. 75 FR 3542 - Rehabilitation Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-21

    ... unwarranted invasion of personal privacy. Disclosure would also reveal research proposals and research... DEPARTMENT OF VETERANS AFFAIRS Rehabilitation Research and Development Service Scientific Merit... (Federal Advisory Committee Act) that the Rehabilitation Research and Development Service Scientific Merit...

  13. BioModels.net Web Services, a free and integrated toolkit for computational modelling software.

    PubMed

    Li, Chen; Courtot, Mélanie; Le Novère, Nicolas; Laibe, Camille

    2010-05-01

    Exchanging and sharing scientific results are essential for researchers in the field of computational modelling. BioModels.net defines agreed-upon standards for model curation. A fundamental one, MIRIAM (Minimum Information Requested in the Annotation of Models), standardises the annotation and curation process of quantitative models in biology. To support this standard, MIRIAM Resources maintains a set of standard data types for annotating models, and provides services for manipulating these annotations. Furthermore, BioModels.net creates controlled vocabularies, such as SBO (Systems Biology Ontology) which strictly indexes, defines and links terms used in Systems Biology. Finally, BioModels Database provides a free, centralised, publicly accessible database for storing, searching and retrieving curated and annotated computational models. Each resource provides a web interface to submit, search, retrieve and display its data. In addition, the BioModels.net team provides a set of Web Services which allows the community to programmatically access the resources. A user is then able to perform remote queries, such as retrieving a model and resolving all its MIRIAM Annotations, as well as getting the details about the associated SBO terms. These web services use established standards. Communications rely on SOAP (Simple Object Access Protocol) messages and the available queries are described in a WSDL (Web Services Description Language) file. Several libraries are provided in order to simplify the development of client software. BioModels.net Web Services make one step further for the researchers to simulate and understand the entirety of a biological system, by allowing them to retrieve biological models in their own tool, combine queries in workflows and efficiently analyse models.

  14. Water resources scientific information center

    USGS Publications Warehouse

    Cardin, C. William; Campbell, J.T.

    1986-01-01

    The Water Resources Scientific Information Center (WRSIC) acquires, abstracts and indexes the major water resources related literature of the world, and makes information available to the water resources community and the public. A component of the Water Resources Division of the US Geological Survey, the Center maintains a searchable computerized bibliographic data base, and publishers a monthly journal of abstracts. Through its services, the Center is able to provide reliable scientific and technical information about the most recent water resources developments, as well as long-term trends and changes. WRSIC was established in 1966 by the Secretary of the Interior to further the objectives of the Water Resources Research Act of 1964--legislation that encouraged research in water resources and the prevention of needless duplication of research efforts. It was determined the WRSIC should be the national center for information on water resources, covering research reports, scientific journals, and other water resources literature of the world. WRSIC would evaluate all water resources literature, catalog selected articles, and make the information available in publications or by computer access. In this way WRSIC would increase the availability and awareness of water related scientific and technical information. (Lantz-PTT)

  15. Integrating Data Base into the Elementary School Science Program.

    ERIC Educational Resources Information Center

    Schlenker, Richard M.

    This document describes seven science activities that combine scientific principles and computers. The objectives for the activities are to show students how the computer can be used as a tool to store and arrange scientific data, provide students with experience using the computer as a tool to manage scientific data, and provide students with…

  16. A high performance scientific cloud computing environment for materials simulations

    NASA Astrophysics Data System (ADS)

    Jorissen, K.; Vila, F. D.; Rehr, J. J.

    2012-09-01

    We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

  17. Cloud Computing for Geosciences--GeoCloud for standardized geospatial service platforms (Invited)

    NASA Astrophysics Data System (ADS)

    Nebert, D. D.; Huang, Q.; Yang, C.

    2013-12-01

    The 21st century geoscience faces challenges of Big Data, spike computing requirements (e.g., when natural disaster happens), and sharing resources through cyberinfrastructure across different organizations (Yang et al., 2011). With flexibility and cost-efficiency of computing resources a primary concern, cloud computing emerges as a promising solution to provide core capabilities to address these challenges. Many governmental and federal agencies are adopting cloud technologies to cut costs and to make federal IT operations more efficient (Huang et al., 2010). However, it is still difficult for geoscientists to take advantage of the benefits of cloud computing to facilitate the scientific research and discoveries. This presentation reports using GeoCloud to illustrate the process and strategies used in building a common platform for geoscience communities to enable the sharing, integration of geospatial data, information and knowledge across different domains. GeoCloud is an annual incubator project coordinated by the Federal Geographic Data Committee (FGDC) in collaboration with the U.S. General Services Administration (GSA) and the Department of Health and Human Services. It is designed as a staging environment to test and document the deployment of a common GeoCloud community platform that can be implemented by multiple agencies. With these standardized virtual geospatial servers, a variety of government geospatial applications can be quickly migrated to the cloud. In order to achieve this objective, multiple projects are nominated each year by federal agencies as existing public-facing geospatial data services. From the initial candidate projects, a set of common operating system and software requirements was identified as the baseline for platform as a service (PaaS) packages. Based on these developed common platform packages, each project deploys and monitors its web application, develops best practices, and documents cost and performance information. This paper presents the background, architectural design, and activities of GeoCloud in support of the Geospatial Platform Initiative. System security strategies and approval processes for migrating federal geospatial data, information, and applications into cloud, and cost estimation for cloud operations are covered. Finally, some lessons learned from the GeoCloud project are discussed as reference for geoscientists to consider in the adoption of cloud computing.

  18. Expanding the use of Scientific Data through Maps and Apps

    NASA Astrophysics Data System (ADS)

    Shrestha, S. R.; Zimble, D. A.; Herring, D.; Halpert, M.

    2014-12-01

    The importance of making scientific data more available can't be overstated. There is a wealth of useful scientific data available and demand for this data is only increasing; however, applying scientific data towards practical uses poses several technical challenges. These challenges can arise from difficulty in handling the data due largely to 1) the complexity, variety and volume of scientific data and 2) applying and operating the techniques and tools needed to visualize and analyze the data. As a result, the combined knowledge required to take advantage of these data requires highly specialized skill sets that in total, limit the ability of scientific data from being used in more practical day-to-day decision making activities. While these challenges are daunting, information technologies do exist that can help mitigate some of these issues. Many organizations for years have already been enjoying the benefits of modern service oriented architectures (SOAs) for everyday enterprise tasks. We can use this approach to modernize how we share and access our scientific data where much of the specialized tools and techniques needed to handle and present scientific data can be automated and executed by servers and done so in an appropriate way. We will discuss and show an approach for preparing file based scientific data (e.g. GRIB, netCDF) for use in standard based scientific web services. These scientific web services are able to encapsulate the logic needed to handle and describe scientific data through a variety of service types including, image, map, feature, geoprocessing, and their respective service methods. By combining these types of services and leveraging well-documented and modern web development APIs, we can afford to focus our attention on the design and development of user-friendly maps and apps. Our scenario will include developing online maps through these services by integrating various forecast data from the Climate Forecast System (CFSv2). This presentation showcases a collaboration between the National Oceanic and Atmospheric Administration's (NOAA) Climate.gov portal, Climate Prediction Center and Esri, Inc. on the implementation of the ArcGIS platform, which is aimed at helping modernize scientific data access through a service oriented architecture.

  19. The Relations between Scientific Epistemological Beliefs and Goal Orientations of Pre-Service Teachers

    ERIC Educational Resources Information Center

    Kaya, Gamze Inan

    2017-01-01

    The purpose of this study was to investigate the relations between pre-service teachers' scientific epistemological beliefs and goal orientations in 2X2 framework. Scientific epistemological beliefs are domain-specific views of people about nature and acquisition of scientific knowledge, how scientific knowledge is produced, how reliable and valid…

  20. 75 FR 72872 - Rehabilitation Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-26

    ... DEPARTMENT OF VETERANS AFFAIRS Rehabilitation Research and Development Service Scientific Merit...-463 (Federal Advisory Committee Act) that a meeting of the Rehabilitation Research and Development Service Scientific Merit Review Board will be held on December 13-14, 2010, at the Hilton Alexandria Old...

  1. 75 FR 40036 - Rehabilitation Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-13

    .... Disclosure would also reveal research proposals and research underway which could lead to the loss of these... DEPARTMENT OF VETERANS AFFAIRS Rehabilitation Research and Development Service Scientific Merit... (Federal Advisory Committee Act) that the Rehabilitation Research and Development Service Scientific Merit...

  2. Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

    ERIC Educational Resources Information Center

    Pallant, Amy; Lee, Hee-Sun

    2015-01-01

    Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation…

  3. Can Clouds replace Grids? Will Clouds replace Grids?

    NASA Astrophysics Data System (ADS)

    Shiers, J. D.

    2010-04-01

    The world's largest scientific machine - comprising dual 27km circular proton accelerators cooled to 1.9oK and located some 100m underground - currently relies on major production Grid infrastructures for the offline computing needs of the 4 main experiments that will take data at this facility. After many years of sometimes difficult preparation the computing service has been declared "open" and ready to meet the challenges that will come shortly when the machine restarts in 2009. But the service is not without its problems: reliability - as seen by the experiments, as opposed to that measured by the official tools - still needs to be significantly improved. Prolonged downtimes or degradations of major services or even complete sites are still too common and the operational and coordination effort to keep the overall service running is probably not sustainable at this level. Recently "Cloud Computing" - in terms of pay-per-use fabric provisioning - has emerged as a potentially viable alternative but with rather different strengths and no doubt weaknesses too. Based on the concrete needs of the LHC experiments - where the total data volume that will be acquired over the full lifetime of the project, including the additional data copies that are required by the Computing Models of the experiments, approaches 1 Exabyte - we analyze the pros and cons of Grids versus Clouds. This analysis covers not only technical issues - such as those related to demanding database and data management needs - but also sociological aspects, which cannot be ignored, neither in terms of funding nor in the wider context of the essential but often overlooked role of science in society, education and economy.

  4. Sentinel-1 Interferometry from the Cloud to the Scientist

    NASA Astrophysics Data System (ADS)

    Garron, J.; Stoner, C.; Johnston, A.; Arko, S. A.

    2017-12-01

    Big data problems and solutions are growing in the technological and scientific sectors daily. Cloud computing is a vertically and horizontally scalable solution available now for archiving and processing large volumes of data quickly, without significant on-site computing hardware costs. Be that as it may, the conversion of scientific data processors to these powerful platforms requires not only the proof of concept, but the demonstration of credibility in an operational setting. The Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC), in partnership with NASA's Jet Propulsion Laboratory, is exploring the functional architecture of Amazon Web Services cloud computing environment for the processing, distribution and archival of Synthetic Aperture Radar data in preparation for the NASA-ISRO Synthetic Aperture Radar (NISAR) Mission. Leveraging built-in AWS services for logging, monitoring and dashboarding, the GRFN (Getting Ready for NISAR) team has built a scalable processing, distribution and archival system of Sentinel-1 L2 interferograms produced using the ISCE algorithm. This cloud-based functional prototype provides interferograms over selected global land deformation features (volcanoes, land subsidence, seismic zones) and are accessible to scientists via NASA's EarthData Search client and the ASF DAACs primary SAR interface, Vertex, for direct download. The interferograms are produced using nearest-neighbor logic for identifying pairs of granules for interferometric processing, creating deep stacks of BETA products from almost every satellite orbit for scientists to explore. This presentation highlights the functional lessons learned to date from this exercise, including the cost analysis of various data lifecycle policies as implemented through AWS. While demonstrating the architecture choices in support of efficient big science data management, we invite feedback and questions about the process and products from the InSAR community.

  5. Parallel processing for scientific computations

    NASA Technical Reports Server (NTRS)

    Alkhatib, Hasan S.

    1995-01-01

    The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

  6. Costa - Introduction to 2015 Annual Report

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

    Costa, James E.

    In parallel with Sandia National Laboratories having two major locations (NM and CA), along with a number of smaller facilities across the nation, so too is the distribution of scientific, engineering and computing resources. As a part of Sandia’s Institutional Computing Program, CA site-based Sandia computer scientists and engineers have been providing mission and research staff with local CA resident expertise on computing options while also focusing on two growing high performance computing research problems. The first is how to increase system resilience to failure, as machines grow larger, more complex and heterogeneous. The second is how to ensure thatmore » computer hardware and configurations are optimized for specialized data analytical mission needs within the overall Sandia computing environment, including the HPC subenvironment. All of these activities support the larger Sandia effort in accelerating development and integration of high performance computing into national security missions. Sandia continues to both promote national R&D objectives, including the recent Presidential Executive Order establishing the National Strategic Computing Initiative and work to ensure that the full range of computing services and capabilities are available for all mission responsibilities, from national security to energy to homeland defense.« less

  7. Requirements for a network storage service

    NASA Technical Reports Server (NTRS)

    Kelly, Suzanne M.; Haynes, Rena A.

    1991-01-01

    Sandia National Laboratories provides a high performance classified computer network as a core capability in support of its mission of nuclear weapons design and engineering, physical sciences research, and energy research and development. The network, locally known as the Internal Secure Network (ISN), comprises multiple distributed local area networks (LAN's) residing in New Mexico and California. The TCP/IP protocol suite is used for inter-node communications. Scientific workstations and mid-range computers, running UNIX-based operating systems, compose most LAN's. One LAN, operated by the Sandia Corporate Computing Computing Directorate, is a general purpose resource providing a supercomputer and a file server to the entire ISN. The current file server on the supercomputer LAN is an implementation of the Common File Server (CFS). Subsequent to the design of the ISN, Sandia reviewed its mass storage requirements and chose to enter into a competitive procurement to replace the existing file server with one more adaptable to a UNIX/TCP/IP environment. The requirements study for the network was the starting point for the requirements study for the new file server. The file server is called the Network Storage Service (NSS) and its requirements are described. An application or functional description of the NSS is given. The final section adds performance, capacity, and access constraints to the requirements.

  8. 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).

  9. The National Center for Biomedical Ontology

    PubMed Central

    Noy, Natalya F; Shah, Nigam H; Whetzel, Patricia L; Chute, Christopher G; Story, Margaret-Anne; Smith, Barry

    2011-01-01

    The National Center for Biomedical Ontology is now in its seventh year. The goals of this National Center for Biomedical Computing are to: create and maintain a repository of biomedical ontologies and terminologies; build tools and web services to enable the use of ontologies and terminologies in clinical and translational research; educate their trainees and the scientific community broadly about biomedical ontology and ontology-based technology and best practices; and collaborate with a variety of groups who develop and use ontologies and terminologies in biomedicine. The centerpiece of the National Center for Biomedical Ontology is a web-based resource known as BioPortal. BioPortal makes available for research in computationally useful forms more than 270 of the world's biomedical ontologies and terminologies, and supports a wide range of web services that enable investigators to use the ontologies to annotate and retrieve data, to generate value sets and special-purpose lexicons, and to perform advanced analytics on a wide range of biomedical data. PMID:22081220

  10. Environmental Models as a Service: Enabling Interoperability ...

    EPA Pesticide Factsheets

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantage of streamlined deployment processes and affordable cloud access to move algorithms and data to the web for discoverability and consumption. In these deployments, environmental models can become available to end users through RESTful web services and consistent application program interfaces (APIs) that consume, manipulate, and store modeling data. RESTful modeling APIs also promote discoverability and guide usability through self-documentation. Embracing the RESTful paradigm allows models to be accessible via a web standard, and the resulting endpoints are platform- and implementation-agnostic while simultaneously presenting significant computational capabilities for spatial and temporal scaling. RESTful APIs present data in a simple verb-noun web request interface: the verb dictates how a resource is consumed using HTTP methods (e.g., GET, POST, and PUT) and the noun represents the URL reference of the resource on which the verb will act. The RESTful API can self-document in both the HTTP response and an interactive web page using the Open API standard. This lets models function as an interoperable service that promotes sharing, documentation, and discoverability. Here, we discuss the

  11. Satellite Cloud and Radiative Property Processing and Distribution System on the NASA Langley ASDC OpenStack and OpenShift Cloud Platform

    NASA Astrophysics Data System (ADS)

    Nguyen, L.; Chee, T.; Palikonda, R.; Smith, W. L., Jr.; Bedka, K. M.; Spangenberg, D.; Vakhnin, A.; Lutz, N. E.; Walter, J.; Kusterer, J.

    2017-12-01

    Cloud Computing offers new opportunities for large-scale scientific data producers to utilize Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) IT resources to process and deliver data products in an operational environment where timely delivery, reliability, and availability are critical. The NASA Langley Research Center Atmospheric Science Data Center (ASDC) is building and testing a private and public facing cloud for users in the Science Directorate to utilize as an everyday production environment. The NASA SatCORPS (Satellite ClOud and Radiation Property Retrieval System) team processes and derives near real-time (NRT) global cloud products from operational geostationary (GEO) satellite imager datasets. To deliver these products, we will utilize the public facing cloud and OpenShift to deploy a load-balanced webserver for data storage, access, and dissemination. The OpenStack private cloud will host data ingest and computational capabilities for SatCORPS processing. This paper will discuss the SatCORPS migration towards, and usage of, the ASDC Cloud Services in an operational environment. Detailed lessons learned from use of prior cloud providers, specifically the Amazon Web Services (AWS) GovCloud and the Government Cloud administered by the Langley Managed Cloud Environment (LMCE) will also be discussed.

  12. Cyber-physical geographical information service-enabled control of diverse in-situ sensors.

    PubMed

    Chen, Nengcheng; Xiao, Changjiang; Pu, Fangling; Wang, Xiaolei; Wang, Chao; Wang, Zhili; Gong, Jianya

    2015-01-23

    Realization of open online control of diverse in-situ sensors is a challenge. This paper proposes a Cyber-Physical Geographical Information Service-enabled method for control of diverse in-situ sensors, based on location-based instant sensing of sensors, which provides closed-loop feedbacks. The method adopts the concepts and technologies of newly developed cyber-physical systems (CPSs) to combine control with sensing, communication, and computation, takes advantage of geographical information service such as services provided by the Tianditu which is a basic geographic information service platform in China and Sensor Web services to establish geo-sensor applications, and builds well-designed human-machine interfaces (HMIs) to support online and open interactions between human beings and physical sensors through cyberspace. The method was tested with experiments carried out in two geographically distributed scientific experimental fields, Baoxie Sensor Web Experimental Field in Wuhan city and Yemaomian Landslide Monitoring Station in Three Gorges, with three typical sensors chosen as representatives using the prototype system Geospatial Sensor Web Common Service Platform. The results show that the proposed method is an open, online, closed-loop means of control.

  13. Cyber-Physical Geographical Information Service-Enabled Control of Diverse In-Situ Sensors

    PubMed Central

    Chen, Nengcheng; Xiao, Changjiang; Pu, Fangling; Wang, Xiaolei; Wang, Chao; Wang, Zhili; Gong, Jianya

    2015-01-01

    Realization of open online control of diverse in-situ sensors is a challenge. This paper proposes a Cyber-Physical Geographical Information Service-enabled method for control of diverse in-situ sensors, based on location-based instant sensing of sensors, which provides closed-loop feedbacks. The method adopts the concepts and technologies of newly developed cyber-physical systems (CPSs) to combine control with sensing, communication, and computation, takes advantage of geographical information service such as services provided by the Tianditu which is a basic geographic information service platform in China and Sensor Web services to establish geo-sensor applications, and builds well-designed human-machine interfaces (HMIs) to support online and open interactions between human beings and physical sensors through cyberspace. The method was tested with experiments carried out in two geographically distributed scientific experimental fields, Baoxie Sensor Web Experimental Field in Wuhan city and Yemaomian Landslide Monitoring Station in Three Gorges, with three typical sensors chosen as representatives using the prototype system Geospatial Sensor Web Common Service Platform. The results show that the proposed method is an open, online, closed-loop means of control. PMID:25625906

  14. OMPC: an Open-Source MATLAB®-to-Python Compiler

    PubMed Central

    Jurica, Peter; van Leeuwen, Cees

    2008-01-01

    Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB®, the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB®-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB® functions into Python programs. The imported MATLAB® modules will run independently of MATLAB®, relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB®. OMPC is available at http://ompc.juricap.com. PMID:19225577

  15. Scientific Computing Paradigm

    NASA Technical Reports Server (NTRS)

    VanZandt, John

    1994-01-01

    The usage model of supercomputers for scientific applications, such as computational fluid dynamics (CFD), has changed over the years. Scientific visualization has moved scientists away from looking at numbers to looking at three-dimensional images, which capture the meaning of the data. This change has impacted the system models for computing. This report details the model which is used by scientists at NASA's research centers.

  16. Commentary: Considerations in Pedagogy and Assessment in the Use of Computers to Promote Learning about Scientific Models

    ERIC Educational Resources Information Center

    Adams, Stephen T.

    2004-01-01

    Although one role of computers in science education is to help students learn specific science concepts, computers are especially intriguing as a vehicle for fostering the development of epistemological knowledge about the nature of scientific knowledge--what it means to "know" in a scientific sense (diSessa, 1985). In this vein, the…

  17. Flexible workflow sharing and execution services for e-scientists

    NASA Astrophysics Data System (ADS)

    Kacsuk, Péter; Terstyanszky, Gábor; Kiss, Tamas; Sipos, Gergely

    2013-04-01

    The sequence of computational and data manipulation steps required to perform a specific scientific analysis is called a workflow. Workflows that orchestrate data and/or compute intensive applications on Distributed Computing Infrastructures (DCIs) recently became standard tools in e-science. At the same time the broad and fragmented landscape of workflows and DCIs slows down the uptake of workflow-based work. The development, sharing, integration and execution of workflows is still a challenge for many scientists. The FP7 "Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs" (SHIWA) project significantly improved the situation, with a simulation platform that connects different workflow systems, different workflow languages, different DCIs and workflows into a single, interoperable unit. The SHIWA Simulation Platform is a service package, already used by various scientific communities, and used as a tool by the recently started ER-flow FP7 project to expand the use of workflows among European scientists. The presentation will introduce the SHIWA Simulation Platform and the services that ER-flow provides based on the platform to space and earth science researchers. The SHIWA Simulation Platform includes: 1. SHIWA Repository: A database where workflows and meta-data about workflows can be stored. The database is a central repository to discover and share workflows within and among communities . 2. SHIWA Portal: A web portal that is integrated with the SHIWA Repository and includes a workflow executor engine that can orchestrate various types of workflows on various grid and cloud platforms. 3. SHIWA Desktop: A desktop environment that provides similar access capabilities than the SHIWA Portal, however it runs on the users' desktops/laptops instead of a portal server. 4. Workflow engines: the ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflow engines are already integrated with the execution engine of the SHIWA Portal. Other engines can be added when required. Through the SHIWA Portal one can define and run simulations on the SHIWA Virtual Organisation, an e-infrastructure that gathers computing and data resources from various DCIs, including the European Grid Infrastructure. The Portal via third party workflow engines provides support for the most widely used academic workflow engines and it can be extended with other engines on demand. Such extensions translate between workflow languages and facilitate the nesting of workflows into larger workflows even when those are written in different languages and require different interpreters for execution. Through the workflow repository and the portal lonely scientists and scientific collaborations can share and offer workflows for reuse and execution. Given the integrated nature of the SHIWA Simulation Platform the shared workflows can be executed online, without installing any special client environment and downloading workflows. The FP7 "Building a European Research Community through Interoperable Workflows and Data" (ER-flow) project disseminates the achievements of the SHIWA project and use these achievements to build workflow user communities across Europe. ER-flow provides application supports to research communities within and beyond the project consortium to develop, share and run workflows with the SHIWA Simulation Platform.

  18. docBUILDER - Building Your Useful Metadata for Earth Science Data and Services.

    NASA Astrophysics Data System (ADS)

    Weir, H. M.; Pollack, J.; Olsen, L. M.; Major, G. R.

    2005-12-01

    The docBUILDER tool, created by NASA's Global Change Master Directory (GCMD), assists the scientific community in efficiently creating quality data and services metadata. Metadata authors are asked to complete five required fields to ensure enough information is provided for users to discover the data and related services they seek. After the metadata record is submitted to the GCMD, it is reviewed for semantic and syntactic consistency. Currently, two versions are available - a Web-based tool accessible with most browsers (docBUILDERweb) and a stand-alone desktop application (docBUILDERsolo). The Web version is available through the GCMD website, at http://gcmd.nasa.gov/User/authoring.html. This version has been updated and now offers: personalized templates to ease entering similar information for multiple data sets/services; automatic population of Data Center/Service Provider URLs based on the selected center/provider; three-color support to indicate required, recommended, and optional fields; an editable text window containing the XML record, to allow for quick editing; and improved overall performance and presentation. The docBUILDERsolo version offers the ability to create metadata records on a computer wherever you are. Except for installation and the occasional update of keywords, data/service providers are not required to have an Internet connection. This freedom will allow users with portable computers (Windows, Mac, and Linux) to create records in field campaigns, whether in Antarctica or the Australian Outback. This version also offers a spell-checker, in addition to all of the features found in the Web version.

  19. Scientific Evidence as Content Knowledge: A Replication Study with English and Turkish Pre-Service Primary Teachers

    ERIC Educational Resources Information Center

    Roberts, Ros; Sahin-Pekmez, Esin

    2012-01-01

    Pre-service teachers around the world need to develop their content knowledge of scientific evidence to meet the requirements of recent school curriculum developments which prepare pupils to be scientifically literate. This research reports a replication study in Turkey of an intervention originally carried out with pre-service primary teachers in…

  20. Transformation of OODT CAS to Perform Larger Tasks

    NASA Technical Reports Server (NTRS)

    Mattmann, Chris; Freeborn, Dana; Crichton, Daniel; Hughes, John; Ramirez, Paul; Hardman, Sean; Woollard, David; Kelly, Sean

    2008-01-01

    A computer program denoted OODT CAS has been transformed to enable performance of larger tasks that involve greatly increased data volumes and increasingly intensive processing of data on heterogeneous, geographically dispersed computers. Prior to the transformation, OODT CAS (also alternatively denoted, simply, 'CAS') [wherein 'OODT' signifies 'Object-Oriented Data Technology' and 'CAS' signifies 'Catalog and Archive Service'] was a proven software component used to manage scientific data from spaceflight missions. In the transformation, CAS was split into two separate components representing its canonical capabilities: file management and workflow management. In addition, CAS was augmented by addition of a resource-management component. This third component enables CAS to manage heterogeneous computing by use of diverse resources, including high-performance clusters of computers, commodity computing hardware, and grid computing infrastructures. CAS is now more easily maintainable, evolvable, and reusable. These components can be used separately or, taking advantage of synergies, can be used together. Other elements of the transformation included addition of a separate Web presentation layer that supports distribution of data products via Really Simple Syndication (RSS) feeds, and provision for full Resource Description Framework (RDF) exports of metadata.

  1. The Center for Computational Biology: resources, achievements, and challenges

    PubMed Central

    Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

    2011-01-01

    The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

  2. The Center for Computational Biology: resources, achievements, and challenges.

    PubMed

    Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

    2012-01-01

    The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

  3. Service-oriented infrastructure for scientific data mashups

    NASA Astrophysics Data System (ADS)

    Baru, C.; Krishnan, S.; Lin, K.; Moreland, J. L.; Nadeau, D. R.

    2009-12-01

    An important challenge in informatics is the development of concepts and corresponding architecture and tools to assist scientists with their data integration tasks. A typical Earth Science data integration request may be expressed, for example, as “For a given region (i.e. lat/long extent, plus depth), return a 3D structural model with accompanying physical parameters of density, seismic velocities, geochemistry, and geologic ages, using a cell size of 10km.” Such requests create “mashups” of scientific data. Currently, such integration is hand-crafted and depends heavily upon a scientist’s intimate knowledge of how to process, interpret, and integrate data from individual sources. In most case, the ultimate “integration” is performed by overlaying output images from individual processing steps using image manipulation software such as, say, Adobe Photoshop—leading to “Photoshop science”, where it is neither easy to repeat the integration steps nor to share the data mashup. As a result, scientists share only the final images and not the mashup itself. A more capable information infrastructure is needed to support the authoring and sharing of scientific data mashups. The infrastructure must include services for data discovery, access, and transformation and should be able to create mashups that are interactive, allowing users to probe and manipulate the data and follow its provenance. We present an architectural framework based on a service-oriented architecture for scientific data mashups in a distributed environment. The framework includes services for Data Access, Data Modeling, and Data Interaction. The Data Access services leverage capabilities for discovery and access to distributed data resources provided by efforts such as GEON and the EarthScope Data Portal, and services for federated metadata catalogs under development by projects like the Geosciences Information Network (GIN). The Data Modeling services provide 2D, 3D, and 4D modeling services based on standards such as WFS, WMS, WCS, and GeoSciML that allow integration of disparate data in a distributed, Web-based environment. Along these lines, we introduce the notion of a Web Volume Service (WVS) for modeling and manipulating 3D data. The Data Interaction Services provide services for rich interactions with the integrated 3D data. To provide efficient interactions with large-scale data in a distributed environment the architecture must include capabilities for caching and reuse of data, use of multi-level indexing, and the ability to orchestrate and coordinate execution of data processing and transformation routines as part of the data access and integration steps. The data mashup infrastructure is based on a service-oriented architecture. A range of alternatives are available for implementing these mashup services in a scalable fashion, using the cloud computing paradigm. We will describe the tradeoffs of each approach and provide an evaluation of which options are best suited to which types of services. We will describe security, privacy, performance, and price/performance issues and considerations in implementing services on dedicated servers versus private as well as public clouds, including systems such as Amazon Web Services.

  4. Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

    PubMed Central

    Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

    2014-01-01

    This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

  5. Enhancing UCSF Chimera through web services.

    PubMed

    Huang, Conrad C; Meng, Elaine C; Morris, John H; Pettersen, Eric F; Ferrin, Thomas E

    2014-07-01

    Integrating access to web services with desktop applications allows for an expanded set of application features, including performing computationally intensive tasks and convenient searches of databases. We describe how we have enhanced UCSF Chimera (http://www.rbvi.ucsf.edu/chimera/), a program for the interactive visualization and analysis of molecular structures and related data, through the addition of several web services (http://www.rbvi.ucsf.edu/chimera/docs/webservices.html). By streamlining access to web services, including the entire job submission, monitoring and retrieval process, Chimera makes it simpler for users to focus on their science projects rather than data manipulation. Chimera uses Opal, a toolkit for wrapping scientific applications as web services, to provide scalable and transparent access to several popular software packages. We illustrate Chimera's use of web services with an example workflow that interleaves use of these services with interactive manipulation of molecular sequences and structures, and we provide an example Python program to demonstrate how easily Opal-based web services can be accessed from within an application. Web server availability: http://webservices.rbvi.ucsf.edu/opal2/dashboard?command=serviceList. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Defining Computational Thinking for Mathematics and Science Classrooms

    ERIC Educational Resources Information Center

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

    2016-01-01

    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…

  7. A sustainability model based on cloud infrastructures for core and downstream Copernicus services

    NASA Astrophysics Data System (ADS)

    Manunta, Michele; Calò, Fabiana; De Luca, Claudio; Elefante, Stefano; Farres, Jordi; Guzzetti, Fausto; Imperatore, Pasquale; Lanari, Riccardo; Lengert, Wolfgang; Zinno, Ivana; Casu, Francesco

    2014-05-01

    The incoming Sentinel missions have been designed to be the first remote sensing satellite system devoted to operational services. In particular, the Synthetic Aperture Radar (SAR) Sentinel-1 sensor, dedicated to globally acquire over land in the interferometric mode, guarantees an unprecedented capability to investigate and monitor the Earth surface deformations related to natural and man-made hazards. Thanks to the global coverage strategy and 12-day revisit time, jointly with the free and open access data policy, such a system will allow an extensive application of Differential Interferometric SAR (DInSAR) techniques. In such a framework, European Commission has been funding several projects through the GMES and Copernicus programs, aimed at preparing the user community to the operational and extensive use of Sentinel-1 products for risk mitigation and management purposes. Among them, the FP7-DORIS, an advanced GMES downstream service coordinated by Italian National Council of Research (CNR), is based on the fully exploitation of advanced DInSAR products in landslides and subsidence contexts. In particular, the DORIS project (www.doris-project.eu) has developed innovative scientific techniques and methodologies to support Civil Protection Authorities (CPA) during the pre-event, event, and post-event phases of the risk management cycle. Nonetheless, the huge data stream expected from the Sentinel-1 satellite may jeopardize the effective use of such data in emergency response and security scenarios. This potential bottleneck can be properly overcome through the development of modern infrastructures, able to efficiently provide computing resources as well as advanced services for big data management, processing and dissemination. In this framework, CNR and ESA have tightened up a cooperation to foster the use of GRID and cloud computing platforms for remote sensing data processing, and to make available to a large audience advanced and innovative tools for DInSAR products generation and exploitation. In particular, CNR is porting the multi-temporal DInSAR technique referred to as Small Baseline Subset (SBAS) into the ESA G-POD (Grid Processing On Demand) and CIOP (Cloud Computing Operational Pilot) platforms (Elefante et al., 2013) within the SuperSites Exploitation Platform (SSEP) project, which aim is contributing to the development of an ecosystem for big geo-data processing and dissemination. This work focuses on presenting the main results that have been achieved by the DORIS project concerning the use of advanced DInSAR products for supporting CPA during the risk management cycle. Furthermore, based on the DORIS experience, a sustainability model for Core and Downstream Copernicus services based on the effective exploitation of cloud platforms is proposed. In this framework, remote sensing community, both service providers and users, can significantly benefit from the Helix Nebula-The Science Cloud initiative, created by European scientific institutions, agencies, SMEs and enterprises to pave the way for the development and exploitation of a cloud computing infrastructure for science. REFERENCES Elefante, S., Imperatore, P. , Zinno, I., M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, F. Casu, 2013, "SBAS-DINSAR Time series generation on cloud computing platforms". IEEE IGARSS Conference, Melbourne (AU), July 2013.

  8. Ermittlung von Wortstaemmen in russischen wissenschaftlichen Fachsprachen mit Hilfe des Computers (Establishing Word Stems in Scientific Russian With the Aid of a Computer)

    ERIC Educational Resources Information Center

    Halbauer, Siegfried

    1976-01-01

    It was considered that students of intensive scientific Russian courses could learn vocabulary more efficiently if they were taught word stems and how to combine them with prefixes and suffixes to form scientific words. The computer programs developed to identify the most important stems is discussed. (Text is in German.) (FB)

  9. Scientific Visualization: The Modern Oscilloscope for "Seeing the Unseeable" (LBNL Summer Lecture Series)

    ScienceCinema

    Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division and Scientific Visualization Group

    2018-05-07

    Summer Lecture Series 2008: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

  10. Scientific Visualization, Seeing the Unseeable

    ScienceCinema

    LBNL

    2017-12-09

    June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in bo... June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

  11. Constructing Arguments: Investigating Pre-Service Science Teachers' Argumentation Skills in a Socio-Scientific Context

    ERIC Educational Resources Information Center

    Robertshaw, Brooke; Campbell, Todd

    2013-01-01

    As western society becomes increasingly reliant on scientific information to make decisions, citizens must be equipped to understand how scientific arguments are constructed. In order to do this, pre-service teachers must be prepared to foster students' abilities and understandings of scientific argumentation in the classroom. This study…

  12. Grid site availability evaluation and monitoring at CMS

    DOE PAGES

    Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; ...

    2017-10-01

    The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

  13. The OSG open facility: A sharing ecosystem

    DOE PAGES

    Jayatilaka, B.; Levshina, T.; Rynge, M.; ...

    2015-12-23

    The Open Science Grid (OSG) ties together individual experiments’ computing power, connecting their resources to create a large, robust computing grid, this computing infrastructure started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero. In the years since, the OSG has broadened its focus to also address the needs of other US researchers and increased delivery of Distributed High Through-put Computing (DHTC) to users from a wide variety of disciplines via the OSG Open Facility. Presently, the Open Facility delivers about 100 million computing wall hours per year to researchers whomore » are not already associated with the owners of the computing sites, this is primarily accomplished by harvesting and organizing the temporarily unused capacity (i.e. opportunistic cycles) from the sites in the OSG. Using these methods, OSG resource providers and scientists share computing hours with researchers in many other fields to enable their science, striving to make sure that these computing power used with maximal efficiency. Furthermore, we believe that expanded access to DHTC is an essential tool for scientific innovation and work continues in expanding this service.« less

  14. Grid site availability evaluation and monitoring at CMS

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

    Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe

    The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

  15. Grid site availability evaluation and monitoring at CMS

    NASA Astrophysics Data System (ADS)

    Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; Lammel, Stephan; Sciabà, Andrea

    2017-10-01

    The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impact data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.

  16. 78 FR 50144 - Health Services Research and Development Service, Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-16

    ... Organization and Delivery; Research Methods and Models on August 27-28, 2013, at the VHA National Conference... DEPARTMENT OF VETERANS AFFAIRS Health Services Research and Development Service, Scientific Merit... Advisory Committee Act, 5 U.S.C. App. 2, that the Health Services Research and Development Service (HSR&D...

  17. Realization of ETRF2000 as a New Terrestrial Reference Frame in Republic of Serbia

    NASA Astrophysics Data System (ADS)

    Blagojevic, D.; Vasilic, V.

    2012-12-01

    The International Earth Rotation and Reference Systems Service (IERS) is a joint service of the International Association of Geodesy (IAG) and the International Astronomical Union (IAU), which provides the scientific community with the means for computing the transformation from the International Celestial Reference System (ICRS) to the International Terrestrial Reference System (ITRS). It further maintains the realizations of these systems by appropriate coordinate sets called "frames". The densification of terrestrial frame usually serves as official frame for positioning and navigation tasks within the territory of particular country. One of these densifications was recently performed in order to establish new reference frame for Republic of Serbia. The paper describes related activities resulting in ETRF2000 as a new Serbian terrestrial reference frame.

  18. 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.

  19. ODI - Portal, Pipeline, and Archive (ODI-PPA): a web-based astronomical compute archive, visualization, and analysis service

    NASA Astrophysics Data System (ADS)

    Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Harbeck, Daniel R.; Boroson, Todd; Liu, Wilson; Kotulla, Ralf; Shaw, Richard; Henschel, Robert; Rajagopal, Jayadev; Stobie, Elizabeth; Knezek, Patricia; Martin, R. Pierre; Archbold, Kevin

    2014-07-01

    The One Degree Imager-Portal, Pipeline, and Archive (ODI-PPA) is a web science gateway that provides astronomers a modern web interface that acts as a single point of access to their data, and rich computational and visualization capabilities. Its goal is to support scientists in handling complex data sets, and to enhance WIYN Observatory's scientific productivity beyond data acquisition on its 3.5m telescope. ODI-PPA is designed, with periodic user feedback, to be a compute archive that has built-in frameworks including: (1) Collections that allow an astronomer to create logical collations of data products intended for publication, further research, instructional purposes, or to execute data processing tasks (2) Image Explorer and Source Explorer, which together enable real-time interactive visual analysis of massive astronomical data products within an HTML5 capable web browser, and overlaid standard catalog and Source Extractor-generated source markers (3) Workflow framework which enables rapid integration of data processing pipelines on an associated compute cluster and users to request such pipelines to be executed on their data via custom user interfaces. ODI-PPA is made up of several light-weight services connected by a message bus; the web portal built using Twitter/Bootstrap, AngularJS and jQuery JavaScript libraries, and backend services written in PHP (using the Zend framework) and Python; it leverages supercomputing and storage resources at Indiana University. ODI-PPA is designed to be reconfigurable for use in other science domains with large and complex datasets, including an ongoing offshoot project for electron microscopy data.

  20. A price and performance comparison of three different storage architectures for data in cloud-based systems

    NASA Astrophysics Data System (ADS)

    Gallagher, J. H. R.; Jelenak, A.; Potter, N.; Fulker, D. W.; Habermann, T.

    2017-12-01

    Providing data services based on cloud computing technology that is equivalent to those developed for traditional computing and storage systems is critical for successful migration to cloud-based architectures for data production, scientific analysis and storage. OPeNDAP Web-service capabilities (comprising the Data Access Protocol (DAP) specification plus open-source software for realizing DAP in servers and clients) are among the most widely deployed means for achieving data-as-service functionality in the Earth sciences. OPeNDAP services are especially common in traditional data center environments where servers offer access to datasets stored in (very large) file systems, and a preponderance of the source data for these services is being stored in the Hierarchical Data Format Version 5 (HDF5). Three candidate architectures for serving NASA satellite Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS) were developed and their performance examined for a set of representative use cases. The performance was based both on runtime and incurred cost. The three architectures differ in how HDF5 files are stored in the Amazon Simple Storage Service (S3) and how the Hyrax server (as an EC2 instance) retrieves their data. The results for both the serial and parallel access to HDF5 data in the S3 will be presented. While the study focused on HDF5 data, OPeNDAP and the Hyrax data server, the architectures are generic and the analysis can be extrapolated to many different data formats, web APIs, and data servers.

  1. OMPC: an Open-Source MATLAB-to-Python Compiler.

    PubMed

    Jurica, Peter; van Leeuwen, Cees

    2009-01-01

    Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

  2. Parallel computing works

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

    Not Available

    An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

  3. Scientific Data Services -- A High-Performance I/O System with Array Semantics

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

    Wu, Kesheng; Byna, Surendra; Rotem, Doron

    2011-09-21

    As high-performance computing approaches exascale, the existing I/O system design is having trouble keeping pace in both performance and scalability. We propose to address this challenge by adopting database principles and techniques in parallel I/O systems. First, we propose to adopt an array data model because many scientific applications represent their data in arrays. This strategy follows a cardinal principle from database research, which separates the logical view from the physical layout of data. This high-level data model gives the underlying implementation more freedom to optimize the physical layout and to choose the most effective way of accessing the data.more » For example, knowing that a set of write operations is working on a single multi-dimensional array makes it possible to keep the subarrays in a log structure during the write operations and reassemble them later into another physical layout as resources permit. While maintaining the high-level view, the storage system could compress the user data to reduce the physical storage requirement, collocate data records that are frequently used together, or replicate data to increase availability and fault-tolerance. Additionally, the system could generate secondary data structures such as database indexes and summary statistics. We expect the proposed Scientific Data Services approach to create a “live” storage system that dynamically adjusts to user demands and evolves with the massively parallel storage hardware.« less

  4. Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis

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

    Hasenkamp, Daren; Sim, Alexander; Wehner, Michael

    Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data; however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, whilemore » we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure; as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.« less

  5. Exploring Cloud Computing for Large-scale Scientific Applications

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

    Lin, Guang; Han, Binh; Yin, Jian

    This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

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

    PubMed

    McCorkel, J; Cook, V

    1986-04-01

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

  7. An Overview of the Computational Physics and Methods Group at Los Alamos National Laboratory

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

    Baker, Randal Scott

    CCS Division was formed to strengthen the visibility and impact of computer science and computational physics research on strategic directions for the Laboratory. Both computer science and computational science are now central to scientific discovery and innovation. They have become indispensable tools for all other scientific missions at the Laboratory. CCS Division forms a bridge between external partners and Laboratory programs, bringing new ideas and technologies to bear on today’s important problems and attracting high-quality technical staff members to the Laboratory. The Computational Physics and Methods Group CCS-2 conducts methods research and develops scientific software aimed at the latest andmore » emerging HPC systems.« less

  8. [Earth Science Technology Office's Computational Technologies Project

    NASA Technical Reports Server (NTRS)

    Fischer, James (Technical Monitor); Merkey, Phillip

    2005-01-01

    This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

  9. Computers and Computation. Readings from Scientific American.

    ERIC Educational Resources Information Center

    Fenichel, Robert R.; Weizenbaum, Joseph

    A collection of articles from "Scientific American" magazine has been put together at this time because the current period in computer science is one of consolidation rather than innovation. A few years ago, computer science was moving so swiftly that even the professional journals were more archival than informative; but today it is…

  10. A new generation of cyberinfrastructure and data services for earth system science education and research

    NASA Astrophysics Data System (ADS)

    Ramamurthy, M. K.

    2006-06-01

    A revolution is underway in the role played by cyberinfrastructure and modern data services in the conduct of research and education. We live in an era of an unprecedented data volume from diverse sources, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. Complex environmental problems such as global change and water cycle transcend disciplinary and geographic boundaries, and their solution requires integrated earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing pedagogical techniques such as enquiry-based learning. The resulting transformation in geoscience education and research creates new opportunities for advancement and poses many challenges. The success of the scientific enterprise depends heavily on the availability of a state-of-the-art, robust, and flexible cyberinfrastructure, and on the timely access to quality data, products, and tools to process, manage, analyze, integrate, publish, and visualize those data. Concomittantly, rapid advances in computing, communication, and information technologies have revolutionized the provision and use of data, tools and services. The profound consequences of Moore's Law and the explosive growth of the Internet are well known. On the other hand, how other technological trends have shaped the development of data services is less well understood. For example, the advent of digital libraries, web services, open standards and protocols have been important factors in shaping a new generation of cyberinfrastructure for solving key scientific and educational problems. This paper presents a broad overview of these issues, along with a survey of key information technology trends, and discuses how those trends are enabling new approaches to applying data services for solving geoscientific problems.

  11. The European Plate Observing System (EPOS) Services for Solid Earth Science

    NASA Astrophysics Data System (ADS)

    Cocco, Massimo; Atakan, Kuvvet; Pedersen, Helle; Consortium, Epos

    2016-04-01

    The European Plate Observing System (EPOS) aims to create a pan-European infrastructure for solid Earth science to support a safe and sustainable society. The main vision of the European Plate Observing System (EPOS) is to address the three basic challenges in Earth Sciences: (i) unravelling the Earth's deformational processes which are part of the Earth system evolution in time, (ii) understanding the geo-hazards and their implications to society, and (iii) contributing to the safe and sustainable use of geo-resources. The mission of EPOS is to monitor and understand the dynamic and complex Earth system by relying on new e-science opportunities and integrating diverse and advanced Research Infrastructures in Europe for solid Earth Science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. EPOS will improve our ability to better manage the use of the subsurface of the Earth. Through integration of data, models and facilities EPOS will allow the Earth Science community to make a step change in developing new concepts and tools for key answers to scientific and socio-economic questions concerning geo-hazards and geo-resources as well as Earth sciences applications to the environment and to human welfare. EPOS has now started its Implementation Phase (EPOS-IP). One of the main challenges during the implementation phase is the integration of multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. These include Data, Data-products, Services and Software (DDSS), from seismology, near fault observatories, geodetic observations, volcano observations, satellite observations, geomagnetic observations, as well as data from various anthropogenic hazard episodes, geological information and modelling. In addition, transnational access to multi-scale laboratories and geo-energy test-beds for low-carbon energy will be provided. TCS DDSS will be integrated into Integrated Core Services (ICS), a platform that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. This requires dedicated tasks for interactions with the various TCS-WPs, as well as the various distributed ICS (ICS-Ds), such as High Performance Computing (HPC) facilities, large scale data storage facilities, complex processing and visualization tools etc. Computational Earth Science (CES) services are identified as a transversal activity and is planned to be harmonized and provided within the ICS. The EPOS Thematic Services will rely in part on strong and sustainable participation by national organisations and international consortia. While this distributed architecture will contribute to ensure pan European involvement in EPOS, it also raises specific challenges: ensuring similar granularity of services, compatibility of technical solutions, homogeneous legal agreements and sustainable financial engagement from the partner institutions and organisations. EPOS is engaging actions to address all of these issues during 2016-2017, after which the services will enter a final validation phase by the EPOS Board of Governmental Representatives.

  12. SenSyF Experience on Integration of EO Services in a Generic, Cloud-Based EO Exploitation Platform

    NASA Astrophysics Data System (ADS)

    Almeida, Nuno; Catarino, Nuno; Gutierrez, Antonio; Grosso, Nuno; Andrade, Joao; Caumont, Herve; Goncalves, Pedro; Villa, Guillermo; Mangin, Antoine; Serra, Romain; Johnsen, Harald; Grydeland, Tom; Emsley, Stephen; Jauch, Eduardo; Moreno, Jose; Ruiz, Antonio

    2016-08-01

    SenSyF is a cloud-based data processing framework for EO- based services. It has been pioneer in addressing Big Data issues from the Earth Observation point of view, and is a precursor of several of the technologies and methodologies that will be deployed in ESA's Thematic Exploitation Platforms and other related systems.The SenSyF system focuses on developing fully automated data management, together with access to a processing and exploitation framework, including Earth Observation specific tools. SenSyF is both a development and validation platform for data intensive applications using Earth Observation data. With SenSyF, scientific, institutional or commercial institutions developing EO- based applications and services can take advantage of distributed computational and storage resources, tailored for applications dependent on big Earth Observation data, and without resorting to deep infrastructure and technological investments.This paper describes the integration process and the experience gathered from different EO Service providers during the project.

  13. Realizing the potential of the CUAHSI Water Data Center to advance Earth Science

    NASA Astrophysics Data System (ADS)

    Hooper, R. P.; Seul, M.; Pollak, J.; Couch, A.

    2015-12-01

    The CUAHSI Water Data Center has developed a cloud-based system for data publication, discovery and access. Key features of this system are a semantically enabled catalog to discover data across more than 100 different services and delivery of data and metadata in a standard format. While this represents a significant technical achievement, the purpose of this system is to support data reanalysis for advancing science. A new web-based client, HydroClient, improves access to the data from previous clients. This client is envisioned as the first step in a workflow that can involve visualization and analysis using web-processing services, followed by download to local computers for further analysis. The release of the WaterML library in the R package CRAN repository is an initial attempt at linking the WDC services in a larger analysis workflow. We are seeking community input on other resources required to make the WDC services more valuable in scientific research and education.

  14. [Electronic data processing-assisted bookkeeping and accounting system at the Düsseldorf Institute of Forensic Medicine].

    PubMed

    Bonte, W; Bonte, I

    1989-01-01

    In 1985 we reported about the usefulness of a simple home computer (here: Commodore C 64) for scientific work. This paper will demonstrate, that such an instrument also can be an appropriate tool for the entire accountancy of a medicolegal institute. Presented were self-designed programs which deal with the following matters: complication of monthly performance reports, calculation of services for clinical care, typing of analytical results and brief interpretations, typing of liquidations, clearing of proceeds from written expertises and autopsies against administration and staff.

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

    NASA Astrophysics Data System (ADS)

    Atakan, Kuvvet; Bailo, Daniele; Consortium, Epos

    2016-04-01

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

  16. 42 CFR 52h.2 - Definitions.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... understanding to develop useful materials, devices, systems, or methods. (u) Scientific review group has the... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS SCIENTIFIC PEER REVIEW OF RESEARCH... the review (the Scientific Review Administrator or equivalent) will evaluate the appearance of a...

  17. 42 CFR 52h.2 - Definitions.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... understanding to develop useful materials, devices, systems, or methods. (u) Scientific review group has the... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS SCIENTIFIC PEER REVIEW OF RESEARCH... the review (the Scientific Review Administrator or equivalent) will evaluate the appearance of a...

  18. 42 CFR 52h.2 - Definitions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... understanding to develop useful materials, devices, systems, or methods. (u) Scientific review group has the... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS SCIENTIFIC PEER REVIEW OF RESEARCH... the review (the Scientific Review Administrator or equivalent) will evaluate the appearance of a...

  19. Unidata Cyberinfrastructure in the Cloud

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    Data services, software, and user support are critical components of geosciences cyber-infrastructure to help researchers to advance science. With the maturity of and significant advances in cloud computing, it has recently emerged as an alternative new paradigm for developing and delivering a broad array of services over the Internet. Cloud computing is now mature enough in usability in many areas of science and education, bringing the benefits of virtualized and elastic remote services to infrastructure, software, computation, and data. Cloud environments reduce the amount of time and money spent to procure, install, and maintain new hardware and software, and reduce costs through resource pooling and shared infrastructure. Given the enormous potential of cloud-based services, Unidata has been moving to augment its software, services, data delivery mechanisms to align with the cloud-computing paradigm. To realize the above vision, Unidata has worked toward: * Providing access to many types of data from a cloud (e.g., via the THREDDS Data Server, RAMADDA and EDEX servers); * Deploying data-proximate tools to easily process, analyze, and visualize those data in a cloud environment cloud for consumption by any one, by any device, from anywhere, at any time; * Developing and providing a range of pre-configured and well-integrated tools and services that can be deployed by any university in their own private or public cloud settings. Specifically, Unidata has developed Docker for "containerized applications", making them easy to deploy. Docker helps to create "disposable" installs and eliminates many configuration challenges. Containerized applications include tools for data transport, access, analysis, and visualization: THREDDS Data Server, Integrated Data Viewer, GEMPAK, Local Data Manager, RAMADDA Data Server, and Python tools; * Leveraging Jupyter as a central platform and hub with its powerful set of interlinking tools to connect interactively data servers, Python scientific libraries, scripts, and workflows; * Exploring end-to-end modeling and prediction capabilities in the cloud; * Partnering with NOAA and public cloud vendors (e.g., Amazon and OCC) on the NOAA Big Data Project to harness their capabilities and resources for the benefit of the academic community.

  20. Trident: scalable compute archives: workflows, visualization, and analysis

    NASA Astrophysics Data System (ADS)

    Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Kotulla, Ralf; Henschel, Robert; Harbeck, Daniel

    2016-08-01

    The Astronomy scientific community has embraced Big Data processing challenges, e.g. associated with time-domain astronomy, and come up with a variety of novel and efficient data processing solutions. However, data processing is only a small part of the Big Data challenge. Efficient knowledge discovery and scientific advancement in the Big Data era requires new and equally efficient tools: modern user interfaces for searching, identifying and viewing data online without direct access to the data; tracking of data provenance; searching, plotting and analyzing metadata; interactive visual analysis, especially of (time-dependent) image data; and the ability to execute pipelines on supercomputing and cloud resources with minimal user overhead or expertise even to novice computing users. The Trident project at Indiana University offers a comprehensive web and cloud-based microservice software suite that enables the straight forward deployment of highly customized Scalable Compute Archive (SCA) systems; including extensive visualization and analysis capabilities, with minimal amount of additional coding. Trident seamlessly scales up or down in terms of data volumes and computational needs, and allows feature sets within a web user interface to be quickly adapted to meet individual project requirements. Domain experts only have to provide code or business logic about handling/visualizing their domain's data products and about executing their pipelines and application work flows. Trident's microservices architecture is made up of light-weight services connected by a REST API and/or a message bus; a web interface elements are built using NodeJS, AngularJS, and HighCharts JavaScript libraries among others while backend services are written in NodeJS, PHP/Zend, and Python. The software suite currently consists of (1) a simple work flow execution framework to integrate, deploy, and execute pipelines and applications (2) a progress service to monitor work flows and sub-work flows (3) ImageX, an interactive image visualization service (3) an authentication and authorization service (4) a data service that handles archival, staging and serving of data products, and (5) a notification service that serves statistical collation and reporting needs of various projects. Several other additional components are under development. Trident is an umbrella project, that evolved from the One Degree Imager, Portal, Pipeline, and Archive (ODI-PPA) project which we had initially refactored toward (1) a powerful analysis/visualization portal for Globular Cluster System (GCS) survey data collected by IU researchers, 2) a data search and download portal for the IU Electron Microscopy Center's data (EMC-SCA), 3) a prototype archive for the Ludwig Maximilian University's Wide Field Imager. The new Trident software has been used to deploy (1) a metadata quality control and analytics portal (RADY-SCA) for DICOM formatted medical imaging data produced by the IU Radiology Center, 2) Several prototype work flows for different domains, 3) a snapshot tool within IU's Karst Desktop environment, 4) a limited component-set to serve GIS data within the IU GIS web portal. Trident SCA systems leverage supercomputing and storage resources at Indiana University but can be configured to make use of any cloud/grid resource, from local workstations/servers to (inter)national supercomputing facilities such as XSEDE.

  1. Survey of Scientific-Technical Tape Services.

    ERIC Educational Resources Information Center

    Carroll, Kenneth D., Ed.

    The results of a survey of commercially available tape services which can provide libraries and information centers with data bases of scientific and technical literature are reported. During the past few years there has been an increasing number of tape services entering the information resources market. Each of these services makes available to…

  2. FOSS GIS on the GFZ HPC cluster: Towards a service-oriented Scientific Geocomputation Environment

    NASA Astrophysics Data System (ADS)

    Loewe, P.; Klump, J.; Thaler, J.

    2012-12-01

    High performance compute clusters can be used as geocomputation workbenches. Their wealth of resources enables us to take on geocomputation tasks which exceed the limitations of smaller systems. These general capabilities can be harnessed via tools such as Geographic Information System (GIS), provided they are able to utilize the available cluster configuration/architecture and provide a sufficient degree of user friendliness to allow for wide application. While server-level computing is clearly not sufficient for the growing numbers of data- or computation-intense tasks undertaken, these tasks do not get even close to the requirements needed for access to "top shelf" national cluster facilities. So until recently such kind of geocomputation research was effectively barred due to lack access to of adequate resources. In this paper we report on the experiences gained by providing GRASS GIS as a software service on a HPC compute cluster at the German Research Centre for Geosciences using Platform Computing's Load Sharing Facility (LSF). GRASS GIS is the oldest and largest Free Open Source (FOSS) GIS project. During ramp up in 2011, multiple versions of GRASS GIS (v 6.4.2, 6.5 and 7.0) were installed on the HPC compute cluster, which currently consists of 234 nodes with 480 CPUs providing 3084 cores. Nineteen different processing queues with varying hardware capabilities and priorities are provided, allowing for fine-grained scheduling and load balancing. After successful initial testing, mechanisms were developed to deploy scripted geocomputation tasks onto dedicated processing queues. The mechanisms are based on earlier work by NETELER et al. (2008) and allow to use all 3084 cores for GRASS based geocomputation work. However, in practice applications are limited to fewer resources as assigned to their respective queue. Applications of the new GIS functionality comprise so far of hydrological analysis, remote sensing and the generation of maps of simulated tsunamis in the Mediterranean Sea for the Tsunami Atlas of the FP-7 TRIDEC Project (www.tridec-online.eu). This included the processing of complex problems, requiring significant amounts of processing time up to full 20 CPU days. This GRASS GIS-based service is provided as a research utility in the sense of "Software as a Service" (SaaS) and is a first step towards a GFZ corporate cloud service.

  3. Scientific Inquiry Self-Efficacy and Computer Game Self-Efficacy as Predictors and Outcomes of Middle School Boys' and Girls' Performance in a Science Assessment in a Virtual Environment

    NASA Astrophysics Data System (ADS)

    Bergey, Bradley W.; Ketelhut, Diane Jass; Liang, Senfeng; Natarajan, Uma; Karakus, Melissa

    2015-10-01

    The primary aim of the study was to examine whether performance on a science assessment in an immersive virtual environment was associated with changes in scientific inquiry self-efficacy. A secondary aim of the study was to examine whether performance on the science assessment was equitable for students with different levels of computer game self-efficacy, including whether gender differences were observed. We examined 407 middle school students' scientific inquiry self-efficacy and computer game self-efficacy before and after completing a computer game-like assessment about a science mystery. Results from path analyses indicated that prior scientific inquiry self-efficacy predicted achievement on end-of-module questions, which in turn predicted change in scientific inquiry self-efficacy. By contrast, computer game self-efficacy was neither predictive of nor predicted by performance on the science assessment. While boys had higher computer game self-efficacy compared to girls, multi-group analyses suggested only minor gender differences in how efficacy beliefs related to performance. Implications for assessments with virtual environments and future design and research are discussed.

  4. Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

    ERIC Educational Resources Information Center

    Wolf, Michael Maclean

    2009-01-01

    Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

  5. Software engineering and automatic continuous verification of scientific software

    NASA Astrophysics Data System (ADS)

    Piggott, M. D.; Hill, J.; Farrell, P. E.; Kramer, S. C.; Wilson, C. R.; Ham, D.; Gorman, G. J.; Bond, T.

    2011-12-01

    Software engineering of scientific code is challenging for a number of reasons including pressure to publish and a lack of awareness of the pitfalls of software engineering by scientists. The Applied Modelling and Computation Group at Imperial College is a diverse group of researchers that employ best practice software engineering methods whilst developing open source scientific software. Our main code is Fluidity - a multi-purpose computational fluid dynamics (CFD) code that can be used for a wide range of scientific applications from earth-scale mantle convection, through basin-scale ocean dynamics, to laboratory-scale classic CFD problems, and is coupled to a number of other codes including nuclear radiation and solid modelling. Our software development infrastructure consists of a number of free tools that could be employed by any group that develops scientific code and has been developed over a number of years with many lessons learnt. A single code base is developed by over 30 people for which we use bazaar for revision control, making good use of the strong branching and merging capabilities. Using features of Canonical's Launchpad platform, such as code review, blueprints for designing features and bug reporting gives the group, partners and other Fluidity uers an easy-to-use platform to collaborate and allows the induction of new members of the group into an environment where software development forms a central part of their work. The code repositoriy are coupled to an automated test and verification system which performs over 20,000 tests, including unit tests, short regression tests, code verification and large parallel tests. Included in these tests are build tests on HPC systems, including local and UK National HPC services. The testing of code in this manner leads to a continuous verification process; not a discrete event performed once development has ceased. Much of the code verification is done via the "gold standard" of comparisons to analytical solutions via the method of manufactured solutions. By developing and verifying code in tandem we avoid a number of pitfalls in scientific software development and advocate similar procedures for other scientific code applications.

  6. Online access to journal abstracts and articles.

    PubMed

    Giedd, J N; Smith, K G

    1997-01-01

    Advances in information technology now offer several options for child and adolescent psychopharmacologists to navigate the increasingly complex terrain of scientific literature and keep abreast of the rapidly changing advances in our field. MEDLINE, the world's largest database of medical literature, can be accessed and searched by a variety of free or fee-based services. In addition to efficient retrieval of citations and abstracts based on subject, author, or title, many of these services now provide, for a fee, the entire text and graphics of articles (displayed on computer screen, faxed, or mailed). There are also current awareness services to alert the user when new requested literature become available as well as services to send via e-mail the tables of contents of requested journals (sometimes prior to paper publication). For online citation and abstract retrieval, we found that free services, such as PubMed, performed as good or better than fee-based services. Physicians' Online, sponsored by the pharmaceutical industry, offered the lowest price for full-text manuscript delivery. In this article, we review literature search, delivery, and update services and offer some tips on how to most effectively use these resources.

  7. Enabling Grid Computing resources within the KM3NeT computing model

    NASA Astrophysics Data System (ADS)

    Filippidis, Christos

    2016-04-01

    KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that - located at the bottom of the Mediterranean Sea - will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.

  8. Grid computing technology for hydrological applications

    NASA Astrophysics Data System (ADS)

    Lecca, G.; Petitdidier, M.; Hluchy, L.; Ivanovic, M.; Kussul, N.; Ray, N.; Thieron, V.

    2011-06-01

    SummaryAdvances in e-Infrastructure promise to revolutionize sensing systems and the way in which data are collected and assimilated, and complex water systems are simulated and visualized. According to the EU Infrastructure 2010 work-programme, data and compute infrastructures and their underlying technologies, either oriented to tackle scientific challenges or complex problem solving in engineering, are expected to converge together into the so-called knowledge infrastructures, leading to a more effective research, education and innovation in the next decade and beyond. Grid technology is recognized as a fundamental component of e-Infrastructures. Nevertheless, this emerging paradigm highlights several topics, including data management, algorithm optimization, security, performance (speed, throughput, bandwidth, etc.), and scientific cooperation and collaboration issues that require further examination to fully exploit it and to better inform future research policies. The paper illustrates the results of six different surface and subsurface hydrology applications that have been deployed on the Grid. All the applications aim to answer to strong requirements from the Civil Society at large, relatively to natural and anthropogenic risks. Grid technology has been successfully tested to improve flood prediction, groundwater resources management and Black Sea hydrological survey, by providing large computing resources. It is also shown that Grid technology facilitates e-cooperation among partners by means of services for authentication and authorization, seamless access to distributed data sources, data protection and access right, and standardization.

  9. A distributed computing environment with support for constraint-based task scheduling and scientific experimentation

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

    Ahrens, J.P.; Shapiro, L.G.; Tanimoto, S.L.

    1997-04-01

    This paper describes a computing environment which supports computer-based scientific research work. Key features include support for automatic distributed scheduling and execution and computer-based scientific experimentation. A new flexible and extensible scheduling technique that is responsive to a user`s scheduling constraints, such as the ordering of program results and the specification of task assignments and processor utilization levels, is presented. An easy-to-use constraint language for specifying scheduling constraints, based on the relational database query language SQL, is described along with a search-based algorithm for fulfilling these constraints. A set of performance studies show that the environment can schedule and executemore » program graphs on a network of workstations as the user requests. A method for automatically generating computer-based scientific experiments is described. Experiments provide a concise method of specifying a large collection of parameterized program executions. The environment achieved significant speedups when executing experiments; for a large collection of scientific experiments an average speedup of 3.4 on an average of 5.5 scheduled processors was obtained.« less

  10. Final Report for DOE Award ER25756

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

    Kesselman, Carl

    2014-11-17

    The SciDAC-funded Center for Enabling Distributed Petascale Science (CEDPS) was established to address technical challenges that arise due to the frequent geographic distribution of data producers (in particular, supercomputers and scientific instruments) and data consumers (people and computers) within the DOE laboratory system. Its goal is to produce technical innovations that meet DOE end-user needs for (a) rapid and dependable placement of large quantities of data within a distributed high-performance environment, and (b) the convenient construction of scalable science services that provide for the reliable and high-performance processing of computation and data analysis requests from many remote clients. The Centermore » is also addressing (c) the important problem of troubleshooting these and other related ultra-high-performance distributed activities from the perspective of both performance and functionality« less

  11. Engaging pre-service teachers to teach science contextually with scientific approach instructional video

    NASA Astrophysics Data System (ADS)

    Susantini, E.; Kurniasari, I.; Fauziah, A. N. M.; Prastowo, T.; Kholiq, A.; Rosdiana, L.

    2018-01-01

    Contextual teaching and learning (CTL) present new concepts in real experiences and situations, where students can find out the meaningful relationship between abstract ideas and practical applications. Implementation of CTL using scientific approach fosters teachers to find constructive ways of delivering and organizing science contents in science classroom settings. An instructional video for modelling by using a scientific approach in CTL was then developed. Questionnaires with open-ended questions were used to, asking whether modelling through instructional video could help them to teach science contextually with a scientific approach or not. Data for pre-service teachers’ views were analyzed descriptively. The aims of this research are to engage pre-service teachers in learning how to teach CTL and to show how their responses to learning and how to teach CTL using the video. The study showed that ten pre-service teachers in science department were involved, all observed through videos that demonstrated a combined material of CTL and scientific approach and completed worksheets to analyze the video contents. The results show that pre-service teachers could learn to teach contextual teaching and make use of scientific approach in science classroom settings with the help of model in the video.

  12. Engaging Pre-Service Teachers to Teach Science Contextually with Scientific Approach Instructional Video

    NASA Astrophysics Data System (ADS)

    Susantini, E.; Kurniasari, I.; Fauziah, A. N. M.; Prastowo, T.; Kholiq, A.; Rosdiana, L.

    2018-01-01

    Contextual teaching and learning/CTL presents new concepts in real-life experiences and situations where students can find out the meaningful relationship between abstract ideas and practical applications. Implementing contextual teaching by using scientific approach will foster teachers to find the constructive ways of delivering and organizing science content. This research developed an instructional video that represented a modeling of using a scientific approach in CTL. The aim of this research are to engage pre-service teachers in learning how to teach CTL and to show how pre-service teachers’ responses about learning how to teach CTL using an instructional video. The subjects of this research were ten pre-service teachers in Department of Natural Sciences, Universitas Negeri Surabaya, Indonesia. All subjects observed the instructional video which demonstrated contextual teaching and learning combined with the scientific approach as they completed a worksheet to analyze the video content. The results showed that pre-service teachers could learn to teach contextually as well as applying the scientific approach in science classroom through a modeling in the instructional video. They also responded that the instructional video could help them to learn to teach each component contextual teaching as well as scientific approach.

  13. Computer-Supported Aids to Making Sense of Scientific Articles: Cognitive, Motivational, and Attitudinal Effects

    ERIC Educational Resources Information Center

    Gegner, Julie A.; Mackay, Donald H. J.; Mayer, Richard E.

    2009-01-01

    High school students can access original scientific research articles on the Internet, but may have trouble understanding them. To address this problem of online literacy, the authors developed a computer-based prototype for guiding students' comprehension of scientific articles. High school students were asked to read an original scientific…

  14. Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization

    ERIC Educational Resources Information Center

    Weiss, Charles J.

    2017-01-01

    The Scientific Computing for Chemists course taught at Wabash College teaches chemistry students to use the Python programming language, Jupyter notebooks, and a number of common Python scientific libraries to process, analyze, and visualize data. Assuming no prior programming experience, the course introduces students to basic programming and…

  15. Computational chemistry in pharmaceutical research: at the crossroads.

    PubMed

    Bajorath, Jürgen

    2012-01-01

    Computational approaches are an integral part of pharmaceutical research. However, there are many of unsolved key questions that limit the scientific progress in the still evolving computational field and its impact on drug discovery. Importantly, a number of these questions are not new but date back many years. Hence, it might be difficult to conclusively answer them in the foreseeable future. Moreover, the computational field as a whole is characterized by a high degree of heterogeneity and so is, unfortunately, the quality of its scientific output. In light of this situation, it is proposed that changes in scientific standards and culture should be seriously considered now in order to lay a foundation for future progress in computational research.

  16. Scholarly literature and the press: scientific impact and social perception of physics computing

    NASA Astrophysics Data System (ADS)

    Pia, M. G.; Basaglia, T.; Bell, Z. W.; Dressendorfer, P. V.

    2014-06-01

    The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the relationship between the scientific impact and the social perception of HEP physics research versus that of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing via press releases from the major HEP laboratories would be beneficial to the high energy physics community.

  17. The JINR Tier1 Site Simulation for Research and Development Purposes

    NASA Astrophysics Data System (ADS)

    Korenkov, V.; Nechaevskiy, A.; Ososkov, G.; Pryahina, D.; Trofimov, V.; Uzhinskiy, A.; Voytishin, N.

    2016-02-01

    Distributed complex computing systems for data storage and processing are in common use in the majority of modern scientific centers. The design of such systems is usually based on recommendations obtained via a preliminary simulated model used and executed only once. However big experiments last for years and decades, and the development of their computing system is going on, not only quantitatively but also qualitatively. Even with the substantial efforts invested in the design phase to understand the systems configuration, it would be hard enough to develop a system without additional research of its future evolution. The developers and operators face the problem of the system behaviour predicting after the planned modifications. A system for grid and cloud services simulation is developed at LIT (JINR, Dubna). This simulation system is focused on improving the effciency of the grid/cloud structures development by using the work quality indicators of some real system. The development of such kind of software is very important for making a new grid/cloud infrastructure for such big scientific experiments like the JINR Tier1 site for WLCG. The simulation of some processes of the Tier1 site is considered as an example of our application approach.

  18. 78 FR 6087 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-29

    ... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building... Theory and Experiment (INCITE) Public Comment (10-minute rule) Public Participation: The meeting is open...

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  20. 78 FR 18680 - Rehabilitation Research and Development Scientific Merit Review Board, Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-27

    ... DEPARTMENT OF VETERANS AFFAIRS Rehabilitation Research and Development Scientific Merit Review... Service, and the Chief Research and Development Officer on the scientific and technical merit, the mission... Committee Act, 5 U.S.C. App. 2, that a meeting of the Rehabilitation Research and Development Service...

  1. Highly parallel computation

    NASA Technical Reports Server (NTRS)

    Denning, Peter J.; Tichy, Walter F.

    1990-01-01

    Highly parallel computing architectures are the only means to achieve the computation rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines and current research focuses on which architectures designated as multiple instruction multiple datastream (MIMD) and single instruction multiple datastream (SIMD) have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed.

  2. 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

  3. Building Cognition: The Construction of Computational Representations for Scientific Discovery

    ERIC Educational Resources Information Center

    Chandrasekharan, Sanjay; Nersessian, Nancy J.

    2015-01-01

    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…

  4. Integration and Exposure of Large Scale Computational Resources Across the Earth System Grid Federation (ESGF)

    NASA Astrophysics Data System (ADS)

    Duffy, D.; Maxwell, T. P.; Doutriaux, C.; Williams, D. N.; Chaudhary, A.; Ames, S.

    2015-12-01

    As the size of remote sensing observations and model output data grows, the volume of the data has become overwhelming, even to many scientific experts. As societies are forced to better understand, mitigate, and adapt to climate changes, the combination of Earth observation data and global climate model projects is crucial to not only scientists but to policy makers, downstream applications, and even the public. Scientific progress on understanding climate is critically dependent on the availability of a reliable infrastructure that promotes data access, management, and provenance. The Earth System Grid Federation (ESGF) has created such an environment for the Intergovernmental Panel on Climate Change (IPCC). ESGF provides a federated global cyber infrastructure for data access and management of model outputs generated for the IPCC Assessment Reports (AR). The current generation of the ESGF federated grid allows consumers of the data to find and download data with limited capabilities for server-side processing. Since the amount of data for future AR is expected to grow dramatically, ESGF is working on integrating server-side analytics throughout the federation. The ESGF Compute Working Team (CWT) has created a Web Processing Service (WPS) Application Programming Interface (API) to enable access scalable computational resources. The API is the exposure point to high performance computing resources across the federation. Specifically, the API allows users to execute simple operations, such as maximum, minimum, average, and anomalies, on ESGF data without having to download the data. These operations are executed at the ESGF data node site with access to large amounts of parallel computing capabilities. This presentation will highlight the WPS API, its capabilities, provide implementation details, and discuss future developments.

  5. Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

    NASA Astrophysics Data System (ADS)

    Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

    2017-01-01

    The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

  6. 5 CFR 630.301 - Annual leave accrual and accumulation-Senior Executive Service, Senior-Level, and Scientific and...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...-Senior Executive Service, Senior-Level, and Scientific and Professional Employees. 630.301 Section 630... LEAVE Annual Leave § 630.301 Annual leave accrual and accumulation—Senior Executive Service, Senior... the full pay period, and who— (1) Holds a position in the Senior Executive Service (SES) which is...

  7. Pre-Service Science and Primary School Teachers' Identification of Scientific Process Skills

    ERIC Educational Resources Information Center

    Birinci Konur, Kader; Yildirim, Nagihan

    2016-01-01

    The purpose of this study was to conduct a comparative analysis of pre-service primary school and science teachers' identification of scientific process skills. The study employed the survey method, and the sample included 95 pre-service science teachers and 95 pre-service primary school teachers from the Faculty of Education at Recep Tayyip…

  8. Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

    2016-01-01

    In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

  9. Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

    ERIC Educational Resources Information Center

    Hulshof, Casper D.; de Jong, Ton

    2006-01-01

    Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

  10. Artificial muscles' enrichment text: Chemical Literacy Profile of pre-service teachers

    NASA Astrophysics Data System (ADS)

    Hernani, Ulum, Luthfi Lulul; Mudzakir, Ahmad

    2017-08-01

    This research aims to determine the profile of chemical literacy abilities of pre-service teachers based on scientific attitudes and scientific competencies in PISA 2015 through individualized learning by using an artificial muscle context based-enrichment book. This research uses descriptive method, involving 20 of the 90 randomly selected population. This research uses a multiple-choice questions instrument. The result of this research are : 1) in the attitude aspects of interest in science and technology, valuing scientific approaches to inquiry, and environmental awareness, the results obtained respectively for 90%, 80%, and 30%. 2) for scientific competence of apply appropriate scientific knowledge, identify models and representations, make appropriate predictions, and explain the potential implications of scientific knowledge for society, the results obtained respectively for 30%, 50%, 60%, and 55%. 3) For scientific competence of identify the question explored in a given scientific study and distinguish questions that could be investigated scientifically, the results obtained respectively for 30 % and 50%. 4) For scientific competence of transform data from one representation to another and draw appropriate conclusions, the results obtained respectively for 60% and 45%. Based on the results, which need to be developed in pre-service chemistry teachers are environmental awareness, apply appropriate scientific knowledge, identify the question explored in a given scientific study, and draw appropriate conclusions.

  11. mORCA: ubiquitous access to life science web services.

    PubMed

    Diaz-Del-Pino, Sergio; Trelles, Oswaldo; Falgueras, Juan

    2018-01-16

    Technical advances in mobile devices such as smartphones and tablets have produced an extraordinary increase in their use around the world and have become part of our daily lives. The possibility of carrying these devices in a pocket, particularly mobile phones, has enabled ubiquitous access to Internet resources. Furthermore, in the life sciences world there has been a vast proliferation of data types and services that finish as Web Services. This suggests the need for research into mobile clients to deal with life sciences applications for effective usage and exploitation. Analysing the current features in existing bioinformatics applications managing Web Services, we have devised, implemented, and deployed an easy-to-use web-based lightweight mobile client. This client is able to browse, select, compose parameters, invoke, and monitor the execution of Web Services stored in catalogues or central repositories. The client is also able to deal with huge amounts of data between external storage mounts. In addition, we also present a validation use case, which illustrates the usage of the application while executing, monitoring, and exploring the results of a registered workflow. The software its available in the Apple Store and Android Market and the source code is publicly available in Github. Mobile devices are becoming increasingly important in the scientific world due to their strong potential impact on scientific applications. Bioinformatics should not fall behind this trend. We present an original software client that deals with the intrinsic limitations of such devices and propose different guidelines to provide location-independent access to computational resources in bioinformatics and biomedicine. Its modular design makes it easily expandable with the inclusion of new repositories, tools, types of visualization, etc.

  12. Enhancing Teachers' Awareness About Relations Between Science and Religion. The Debate Between Steady State and Big Bang Theories

    NASA Astrophysics Data System (ADS)

    Bagdonas, Alexandre; Silva, Cibelle Celestino

    2015-11-01

    Educators advocate that science education can help the development of more responsible worldviews when students learn not only scientific concepts, but also about science, or "nature of science". Cosmology can help the formation of worldviews because this topic is embedded in socio-cultural and religious issues. Indeed, during the Cold War period, the cosmological controversy between Big Bang and Steady State theory was tied up with political and religious arguments. The present paper discusses a didactic sequence developed for and applied in a pre-service science teacher-training course on history of science. After studying the historical case, pre-service science teachers discussed how to deal with possible conflicts between scientific views and students' personal worldviews related to religion. The course focused on the study of primary and secondary sources about cosmology and religion written by cosmologists such as Georges Lemaître, Fred Hoyle and the Pope Pius XII. We used didactic strategies such as short seminars given by groups of pre-service teachers, videos, computer simulations, role-play, debates and preparation of written essays. Along the course, most pre-service teachers emphasized differences between science and religion and pointed out that they do not feel prepared to conduct classroom discussions about this topic. Discussing the relations between science and religion using the history of cosmology turned into an effective way to teach not only science concepts but also to stimulate reflections about nature of science. This topic may contribute to increasing students' critical stance on controversial issues, without the need to explicitly defend certain positions, or disapprove students' cultural traditions. Moreover, pre-service teachers practiced didactic strategies to deal with this kind of unusual content.

  13. Pre-Service Versus In-Service Science Teachers' Views of NOS

    ERIC Educational Resources Information Center

    Hoh, Yin Kiong

    2013-01-01

    This article reports on the results of a paper-pen questionnaire study involving certain key aspects of the nature of science. The questionnaire covers, among other things, aspects such as uniqueness of the scientific method, objectivity of scientific data, and immutability of scientific laws. The survey was given out to eighty trainee teachers…

  14. Thai Pre-Service Science Teachers' Conceptions of the Nature of Science

    ERIC Educational Resources Information Center

    Buaraphan, Khajornsak; Sung-ong, Sunun

    2009-01-01

    The conceptions of the nature of science (NOS), particularly scientific knowledge, scientific method, scientists' work, and scientific enterprise, of 113 Thai pre-service science teachers were was captured by the Myths of Science Questionnaire (MOSQ) in the first semester of the 2008 academic year. The data was quantitatively and qualitatively…

  15. Thai In-Service Science Teachers' Conceptions of the Nature of Science

    ERIC Educational Resources Information Center

    Buaraphan, Khajornsak

    2009-01-01

    Understanding of the Nature of Science (NOS) serves as one of the desirable characteristics of science teachers. The current study attempted to explore 101 Thai in-service science teachers' conceptions of the NOS, particularly scientific knowledge, the scientific method, scientists' work, and scientific enterprise, by using the Myths of Science…

  16. 5 CFR 630.301 - Annual leave accrual and accumulation-Senior Executive Service, Senior-Level, and Scientific and...

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... legal authority, for planning, monitoring, developing, evaluating, and rewarding employee performance...-Senior Executive Service, Senior-Level, and Scientific and Professional Employees. 630.301 Section 630...-Level, and Scientific and Professional Employees. (a) Annual leave accrues at the rate of 1 day (8 hours...

  17. 5 CFR 630.301 - Annual leave accrual and accumulation-Senior Executive Service, Senior-Level, and Scientific and...

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... legal authority, for planning, monitoring, developing, evaluating, and rewarding employee performance...-Senior Executive Service, Senior-Level, and Scientific and Professional Employees. 630.301 Section 630...-Level, and Scientific and Professional Employees. (a) Annual leave accrues at the rate of 1 day (8 hours...

  18. 5 CFR 630.301 - Annual leave accrual and accumulation-Senior Executive Service, Senior-Level, and Scientific and...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... legal authority, for planning, monitoring, developing, evaluating, and rewarding employee performance...-Senior Executive Service, Senior-Level, and Scientific and Professional Employees. 630.301 Section 630...-Level, and Scientific and Professional Employees. (a) Annual leave accrues at the rate of 1 day (8 hours...

  19. 5 CFR 630.301 - Annual leave accrual and accumulation-Senior Executive Service, Senior-Level, and Scientific and...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... legal authority, for planning, monitoring, developing, evaluating, and rewarding employee performance...-Senior Executive Service, Senior-Level, and Scientific and Professional Employees. 630.301 Section 630...-Level, and Scientific and Professional Employees. (a) Annual leave accrues at the rate of 1 day (8 hours...

  20. Development of a Centralized Automated Scientific and Technical Information Service in the People's Republic of Bulgaria.

    ERIC Educational Resources Information Center

    Kiratsov, P.

    1983-01-01

    Discusses the design and organization of the Automated Information Centre, a centralized automated scientific and technical information service established within the main organ of Bulgaria's National System for Scientific and Technical Information, with UNESCO and United Nations Development Program assistance. Problems and perspectives for…

  1. The Climate-G Portal: a Grid Enabled Scientifc Gateway for Climate Change

    NASA Astrophysics Data System (ADS)

    Fiore, Sandro; Negro, Alessandro; Aloisio, Giovanni

    2010-05-01

    Grid portals are web gateways aiming at concealing the underlying infrastructure through a pervasive, transparent, user-friendly, ubiquitous and seamless access to heterogeneous and geographical spread resources (i.e. storage, computational facilities, services, sensors, network, databases). Definitively they provide an enhanced problem-solving environment able to deal with modern, large scale scientific and engineering problems. Scientific gateways are able to introduce a revolution in the way scientists and researchers organize and carry out their activities. Access to distributed resources, complex workflow capabilities, and community-oriented functionalities are just some of the features that can be provided by such a web-based environment. In the context of the EGEE NA4 Earth Science Cluster, Climate-G is a distributed testbed focusing on climate change research topics. The Euro-Mediterranean Center for Climate Change (CMCC) is actively participating in the testbed providing the scientific gateway (Climate-G Portal) to access to the entire infrastructure. The Climate-G Portal has to face important and critical challenges as well as has to satisfy and address key requirements. In the following, the most relevant ones are presented and discussed. Transparency: the portal has to provide a transparent access to the underlying infrastructure preventing users from dealing with low level details and the complexity of a distributed grid environment. Security: users must be authenticated and authorized on the portal to access and exploit portal functionalities. A wide set of roles is needed to clearly assign the proper one to each user. The access to the computational grid must be completely secured, since the target infrastructure to run jobs is a production grid environment. A security infrastructure (based on X509v3 digital certificates) is strongly needed. Pervasivity and ubiquity: the access to the system must be pervasive and ubiquitous. This is easily true due to the nature of the needed web approach. Usability and simplicity: the portal has to provide simple, high level and user friendly interfaces to ease the access and exploitation of the entire system. Coexistence of general purpose and domain oriented services: along with general purpose services (file transfer, job submission, etc.), the portal has to provide domain based services and functionalities. Subsetting of data, visualization of 2D maps around a virtual globe, delivery of maps through OGC compliant interfaces (i.e. Web Map Service - WMS) are just some examples. Since april 2009, about 70 users (85% coming from the climate change community) got access to the portal. A key challenge of this work is the idea to provide users with an integrated working environment, that is a place where scientists can find huge amount of data, complete metadata support, a wide set of data access services, data visualization and analysis tools, easy access to the underlying grid infrastructure and advanced monitoring interfaces.

  2. SHIWA Services for Workflow Creation and Sharing in Hydrometeorolog

    NASA Astrophysics Data System (ADS)

    Terstyanszky, Gabor; Kiss, Tamas; Kacsuk, Peter; Sipos, Gergely

    2014-05-01

    Researchers want to run scientific experiments on Distributed Computing Infrastructures (DCI) to access large pools of resources and services. To run these experiments requires specific expertise that they may not have. Workflows can hide resources and services as a virtualisation layer providing a user interface that researchers can use. There are many scientific workflow systems but they are not interoperable. To learn a workflow system and create workflows may require significant efforts. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows developed in other workflow systems. To overcome it requires creating workflow interoperability solutions to allow workflow sharing. The FP7 'Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs' (SHIWA) project developed the Coarse-Grained Interoperability concept (CGI). It enables recycling and sharing workflows of different workflow systems and executing them on different DCIs. SHIWA developed the SHIWA Simulation Platform (SSP) to implement the CGI concept integrating three major components: the SHIWA Science Gateway, the workflow engines supported by the CGI concept and DCI resources where workflows are executed. The science gateway contains a portal, a submission service, a workflow repository and a proxy server to support the whole workflow life-cycle. The SHIWA Portal allows workflow creation, configuration, execution and monitoring through a Graphical User Interface using the WS-PGRADE workflow system as the host workflow system. The SHIWA Repository stores the formal description of workflows and workflow engines plus executables and data needed to execute them. It offers a wide-range of browse and search operations. To support non-native workflow execution the SHIWA Submission Service imports the workflow and workflow engine from the SHIWA Repository. This service either invokes locally or remotely pre-deployed workflow engines or submits workflow engines with the workflow to local or remote resources to execute workflows. The SHIWA Proxy Server manages certificates needed to execute the workflows on different DCIs. Currently SSP supports sharing of ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflows. Further workflow systems can be added to the simulation platform as required by research communities. The FP7 'Building a European Research Community through Interoperable Workflows and Data' (ER-flow) project disseminates the achievements of the SHIWA project to build workflow user communities across Europe. ER-flow provides application supports to research communities within (Astrophysics, Computational Chemistry, Heliophysics and Life Sciences) and beyond (Hydrometeorology and Seismology) to develop, share and run workflows through the simulation platform. The simulation platform supports four usage scenarios: creating and publishing workflows in the repository, searching and selecting workflows in the repository, executing non-native workflows and creating and running meta-workflows. The presentation will outline the CGI concept, the SHIWA Simulation Platform, the ER-flow usage scenarios and how the Hydrometeorology research community runs simulations on SSP.

  3. 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.

  4. An Interdisciplinary Guided Inquiry on Estuarine Transport Using a Computer Model in High School Classrooms

    ERIC Educational Resources Information Center

    Chan, Kit Yu Karen; Yang, Sylvia; Maliska, Max E.; Grunbaum, Daniel

    2012-01-01

    The National Science Education Standards have highlighted the importance of active learning and reflection for contemporary scientific methods in K-12 classrooms, including the use of models. Computer modeling and visualization are tools that researchers employ in their scientific inquiry process, and often computer models are used in…

  5. An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

    ERIC Educational Resources Information Center

    Tuncer, Murat

    2013-01-01

    Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

  6. The Impact of Three-Dimensional Computational Modeling on Student Understanding of Astronomical Concepts: A Quantitative Analysis

    ERIC Educational Resources Information Center

    Hansen, John; Barnett, Michael; MaKinster, James; Keating, Thomas

    2004-01-01

    The increased availability of computational modeling software has created opportunities for students to engage in scientific inquiry through constructing computer-based models of scientific phenomena. However, despite the growing trend of integrating technology into science curricula, educators need to understand what aspects of these technologies…

  7. Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

    NASA Technical Reports Server (NTRS)

    Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob

    2003-01-01

    The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

  8. USRA/RIACS

    NASA Technical Reports Server (NTRS)

    Oliger, Joseph

    1992-01-01

    The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under a cooperative agreement with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing; Advanced Methods for Scientific Computing; Learning Systems; High Performance Networks and Technology; Graphics, Visualization, and Virtual Environments.

  9. Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

    NASA Astrophysics Data System (ADS)

    Develaki, Maria

    2017-11-01

    Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

  10. NASA Nice Climate Change Education

    NASA Astrophysics Data System (ADS)

    Frink, K.; Crocker, S.; Jones, W., III; Marshall, S. S.; Anuradha, D.; Stewart-Gurley, K.; Howard, E. M.; Hill, E.; Merriweather, E.

    2013-12-01

    Authors: 1 Kaiem Frink, 4 Sherry Crocker, 5 Willie Jones, III, 7 Sophia S.L. Marshall, 6 Anuadha Dujari 3 Ervin Howard 1 Kalota Stewart-Gurley 8 Edwinta Merriweathe Affiliation: 1. Mathematics & Computer Science, Virginia Union University, Richmond, VA, United States. 2. Mathematics & Computer Science, Elizabeth City State Univ, Elizabeth City, NC, United States. 3. Education, Elizabeth City State University, Elizabeth City, NC, United States. 4. College of Education, Fort Valley State University , Fort Valley, GA, United States. 5. Education, Tougaloo College, Jackson, MS, United States. 6. Mathematics, Delaware State University, Dover, DE, United States. 7. Education, Jackson State University, Jackson, MS, United States. 8. Education, Alabama Agricultural and Mechanical University, Huntsville, AL, United States. ABSTRACT: In this research initiative, the 2013-2014 NASA NICE workshop participants will present best educational practices for incorporating climate change pedagogy. The presentation will identify strategies to enhance instruction of pre-service teachers to aligned with K-12 Science, Technology, Engineering and Mathematics (STEM) standards. The presentation of best practices should serve as a direct indicator to address pedagogical needs to include climate education within a K-12 curriculum Some of the strategies will include inquiry, direct instructions, and cooperative learning . At this particular workshop, we have learned about global climate change in regards to how this is going to impact our life. Participants have been charged to increase the scientific understanding of pre-service teachers education programs nationally to incorporate climate education lessons. These recommended practices will provide feasible instructional strategies that can be easily implemented and used to clarify possible misconceptions and ambiguities in scientific knowledge. Additionally, the presentation will promote an awareness to the many facets in which climate change education can be beneficial to future learners and general public. The main scope is to increase the amount of STEM knowledge throughout the nations scientific literacy as we are using the platform of climate change. Federal entities which may include but not limited to National Security Agency and the Department of Homeland Security and Management will serve as resources partners for this common goal of having a more knowledgeable technological savvy and scientific literate society. The presentation will show that incorporating these best practices into elementary and early childhood education undergraduate programs will assist with increasing a enhance scientific literate society. As a measurable outcome have a positive impact on instructional effectiveness of future teachers. Their successfully preparing students in meeting the standards of the Common Core Initiative will attempt to measure across the curriculum uniformly.

  11. Scientific and Technological Information Services in Australia: II. Discipline Formation in Information Management

    ERIC Educational Resources Information Center

    Middleton, Michael

    2006-01-01

    This second part of an analysis of scientific and technical information (STI) services in Australia considers their development in the context of discipline formation in information management. The case studies used are the STI services from Part I. A case study protocol is used to consider the extent to which the development of the services may…

  12. Pre-service elementary teachers' understanding of scientific inquiry and its role in school science

    NASA Astrophysics Data System (ADS)

    Macaroglu, Esra

    The purpose of this research was to explore pre-service elementary teachers' developing understanding of scientific inquiry within the context of their elementary science teaching and learning. More specifically, the study examined 24 pre-service elementary teachers' emerging understanding of (1) the nature of science and scientific inquiry; (2) the "place" of scientific inquiry in school science; and (3) the roles and responsibilities of teachers and students within an inquiry-based learning environment. Data sources consisted primarily of student-generated artifacts collected throughout the semester, including pre/post-philosophy statements and text-based materials collected from electronic dialogue journals. Individual data sources were open-coded to identify concepts and categories expressed by students. Cross-comparisons were conducted and patterns were identified. Assertions were formed with these patterns. Findings are hopeful in that they suggest pre-service teachers can develop a more contemporary view of scientific inquiry when immersed in a context that promotes this perspective. Not surprisingly, however, the prospective teachers encountered a number of barriers when attempting to translate their emerging ideas into practice. More research is needed to determine which teacher preparation experiences are most powerful in supporting pre-service teachers as they construct a framework for science teaching and learning that includes scientific inquiry as a central component.

  13. Standardised Embedded Data framework for Drones [SEDD

    NASA Astrophysics Data System (ADS)

    Wyngaard, J.; Barbieri, L.; Peterson, F. S.

    2015-12-01

    A number of barriers to entry remain for UAS use in science. One in particular is that of implementing an experiment and UAS specific software stack. Currently this stack is most often developed in-house and customised for a particular UAS-sensor pairing - limiting its reuse. Alternatively, when adaptable a suitable commercial package may be used, but such systems are both costly and usually suboptimal.In order to address this challenge the Standardised Embedded Data framework for Drones [SEDD] is being developed in μpython. SEDD provides an open source, reusable, and scientist-accessible drop in solution for drone data capture and triage. Targeted at embedded hardware, and offering easy access to standard I/O interfaces, SEDD provides an easy solution for simply capturing data from a sensor. However, the intention is rather to enable more complex systems of multiple sensors, computer hardware, and feedback loops, via 3 primary components.A data asset manager ensures data assets are associated with appropriate metadata as they are captured. Thereafter, the asset is easily archived or otherwise redirected, possibly to - onboard storage, onboard compute resource for processing, an interface for transmission, another sensor control system, remote storage and processing (such as EarthCube's CHORDS), or to any combination of the above.A service workflow managerenables easy implementation of complex onboard systems via dedicated control of multiple continuous and periodic services. Such services will include the housekeeping chores of operating a UAS and multiple sensors, but will also permit a scientist to drop in an initial scientific data processing code utilising on-board compute resources beyond the autopilot. Having such capabilities firstly enables easy creation of real-time feedback, to the human- or auto- pilot, or other sensors, on data quality or needed flight path changes. Secondly, compute hardware provides the opportunity to carry out real-time data triage, for the purposes of conserving on-board storage space or transmission bandwidth in inherently poor connectivity environments.A compute manager is finally included. Depending on system complexity, and given the need for power efficient parallelism, it can quickly become necessary to provide a scheduling service for multiple workflows.

  14. Towards a National Research Information Service for Tanzania.

    ERIC Educational Resources Information Center

    Hjerppe, Roland

    This report documents initiatives taken to establish scientific and technical information services in Tanzania. The program has as a short term goal the establishment of a national information service for research by the Tanzania National Scientific Research Council with the cooperation and assistance of the Swedish Royal Institute of Technology…

  15. Shaping a Science of Social Work

    ERIC Educational Resources Information Center

    Brekke, John S.

    2012-01-01

    Social workers provide more social services to populations across the life span than any other human service profession, including psychiatry, nursing, and psychology. The scientific methodologies and the scientific knowledge relevant to social services have expanded dramatically in the last 30 years. Using the two indicators of the total number…

  16. A toolbox and a record for scientific model development

    NASA Technical Reports Server (NTRS)

    Ellman, Thomas

    1994-01-01

    Scientific computation can benefit from software tools that facilitate construction of computational models, control the application of models, and aid in revising models to handle new situations. Existing environments for scientific programming provide only limited means of handling these tasks. This paper describes a two pronged approach for handling these tasks: (1) designing a 'Model Development Toolbox' that includes a basic set of model constructing operations; and (2) designing a 'Model Development Record' that is automatically generated during model construction. The record is subsequently exploited by tools that control the application of scientific models and revise models to handle new situations. Our two pronged approach is motivated by our belief that the model development toolbox and record should be highly interdependent. In particular, a suitable model development record can be constructed only when models are developed using a well defined set of operations. We expect this research to facilitate rapid development of new scientific computational models, to help ensure appropriate use of such models and to facilitate sharing of such models among working computational scientists. We are testing this approach by extending SIGMA, and existing knowledge-based scientific software design tool.

  17. Workflow based framework for life science informatics.

    PubMed

    Tiwari, Abhishek; Sekhar, Arvind K T

    2007-10-01

    Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

  18. The Petascale Data Storage Institute

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

    Gibson, Garth; Long, Darrell; Honeyman, Peter

    2013-07-01

    Petascale computing infrastructures for scientific discovery make petascale demands on information storage capacity, performance, concurrency, reliability, availability, and manageability.The Petascale Data Storage Institute focuses on the data storage problems found in petascale scientific computing environments, with special attention to community issues such as interoperability, community buy-in, and shared tools.The Petascale Data Storage Institute is a collaboration between researchers at Carnegie Mellon University, National Energy Research Scientific Computing Center, Pacific Northwest National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratory, Los Alamos National Laboratory, University of Michigan, and the University of California at Santa Cruz.

  19. 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

  20. 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.

  1. The need for scientific software engineering in the pharmaceutical industry

    NASA Astrophysics Data System (ADS)

    Luty, Brock; Rose, Peter W.

    2017-03-01

    Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

  2. The need for scientific software engineering in the pharmaceutical industry.

    PubMed

    Luty, Brock; Rose, Peter W

    2017-03-01

    Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

  3. PRACE - The European HPC Infrastructure

    NASA Astrophysics Data System (ADS)

    Stadelmeyer, Peter

    2014-05-01

    The mission of PRACE (Partnership for Advanced Computing in Europe) is to enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process. This talk gives a general overview about PRACE and the PRACE research infrastructure (RI). PRACE is established as an international not-for-profit association and the PRACE RI is a pan-European supercomputing infrastructure which offers access to computing and data management resources at partner sites distributed throughout Europe. Besides a short summary about the organization, history, and activities of PRACE, it is explained how scientists and researchers from academia and industry from around the world can access PRACE systems and which education and training activities are offered by PRACE. The overview also contains a selection of PRACE contributions to societal challenges and ongoing activities. Examples of the latter are beside others petascaling, application benchmark suite, best practice guides for efficient use of key architectures, application enabling / scaling, new programming models, and industrial applications. The Partnership for Advanced Computing in Europe (PRACE) is an international non-profit association with its seat in Brussels. The PRACE Research Infrastructure provides a persistent world-class high performance computing service for scientists and researchers from academia and industry in Europe. The computer systems and their operations accessible through PRACE are provided by 4 PRACE members (BSC representing Spain, CINECA representing Italy, GCS representing Germany and GENCI representing France). The Implementation Phase of PRACE receives funding from the EU's Seventh Framework Programme (FP7/2007-2013) under grant agreements RI-261557, RI-283493 and RI-312763. For more information, see www.prace-ri.eu

  4. Development of a Web Based Simulating System for Earthquake Modeling on the Grid

    NASA Astrophysics Data System (ADS)

    Seber, D.; Youn, C.; Kaiser, T.

    2007-12-01

    Existing cyberinfrastructure-based information, data and computational networks now allow development of state- of-the-art, user-friendly simulation environments that democratize access to high-end computational environments and provide new research opportunities for many research and educational communities. Within the Geosciences cyberinfrastructure network, GEON, we have developed the SYNSEIS (SYNthetic SEISmogram) toolkit to enable efficient computations of 2D and 3D seismic waveforms for a variety of research purposes especially for helping to analyze the EarthScope's USArray seismic data in a speedy and efficient environment. The underlying simulation software in SYNSEIS is a finite difference code, E3D, developed by LLNL (S. Larsen). The code is embedded within the SYNSEIS portlet environment and it is used by our toolkit to simulate seismic waveforms of earthquakes at regional distances (<1000km). Architecturally, SYNSEIS uses both Web Service and Grid computing resources in a portal-based work environment and has a built in access mechanism to connect to national supercomputer centers as well as to a dedicated, small-scale compute cluster for its runs. Even though Grid computing is well-established in many computing communities, its use among domain scientists still is not trivial because of multiple levels of complexities encountered. We grid-enabled E3D using our own dialect XML inputs that include geological models that are accessible through standard Web services within the GEON network. The XML inputs for this application contain structural geometries, source parameters, seismic velocity, density, attenuation values, number of time steps to compute, and number of stations. By enabling a portal based access to a such computational environment coupled with its dynamic user interface we enable a large user community to take advantage of such high end calculations in their research and educational activities. Our system can be used to promote an efficient and effective modeling environment to help scientists as well as educators in their daily activities and speed up the scientific discovery process.

  5. Thai and Bangladeshi In-Service Science Teachers' Conceptions of Nature of Science: A Comparative Study

    ERIC Educational Resources Information Center

    Buaraphan, Khajornsak; Abedin Forhad, Ziaul

    2014-01-01

    Understanding of nature of science (NOS) serves as one of the desirable characteristics of science teachers. The current study explored 55 Thai and 110 Bangladeshi in-service secondary science teachers' conceptions of NOS regarding scientific knowledge, scientific method, scientists' work, and scientific enterprise, by using the Myths of Science…

  6. Pre-Service Science Teachers' Perception of the Principles of Scientific Research

    ERIC Educational Resources Information Center

    Can, Sendil; Kaymakci, Güliz

    2016-01-01

    The purpose of the current study employing the survey method is to determine the pre-service science teachers' perceptions of the principles of scientific research and to investigate the effects of gender, grade level and the state of following scientific publications on their perceptions. The sampling of the current research is comprised of 125…

  7. Balancing the Pros and Cons of GMOs: Socio-Scientific Argumentation in Pre-Service Teacher Education

    ERIC Educational Resources Information Center

    Cinici, Ayhan

    2016-01-01

    This study investigates the role of the discursive process in the act of scientific knowledge building. Specifically, it links scientific knowledge building to risk perception of Genetically Modified Organisms (GMOs). To this end, this study designed and implemented a three-stage argumentation programme giving pre-service teachers (PSTs) the…

  8. High Performance Distributed Computing in a Supercomputer Environment: Computational Services and Applications Issues

    NASA Technical Reports Server (NTRS)

    Kramer, Williams T. C.; Simon, Horst D.

    1994-01-01

    This tutorial proposes to be a practical guide for the uninitiated to the main topics and themes of high-performance computing (HPC), with particular emphasis to distributed computing. The intent is first to provide some guidance and directions in the rapidly increasing field of scientific computing using both massively parallel and traditional supercomputers. Because of their considerable potential computational power, loosely or tightly coupled clusters of workstations are increasingly considered as a third alternative to both the more conventional supercomputers based on a small number of powerful vector processors, as well as high massively parallel processors. Even though many research issues concerning the effective use of workstation clusters and their integration into a large scale production facility are still unresolved, such clusters are already used for production computing. In this tutorial we will utilize the unique experience made at the NAS facility at NASA Ames Research Center. Over the last five years at NAS massively parallel supercomputers such as the Connection Machines CM-2 and CM-5 from Thinking Machines Corporation and the iPSC/860 (Touchstone Gamma Machine) and Paragon Machines from Intel were used in a production supercomputer center alongside with traditional vector supercomputers such as the Cray Y-MP and C90.

  9. 75 FR 65639 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-26

    ...: Computational Biology Special Emphasis Panel A. Date: October 29, 2010. Time: 2 p.m. to 3:30 p.m. Agenda: To.... Name of Committee: Center for Scientific Review Special Emphasis Panel; Member Conflict: Computational...

  10. The Effects of Inquiry-Based Computer Simulation with Cooperative Learning on Scientific Thinking and Conceptual Understanding of Gas Laws

    ERIC Educational Resources Information Center

    Abdullah, Sopiah; Shariff, Adilah

    2008-01-01

    The purpose of the study was to investigate the effects of inquiry-based computer simulation with heterogeneous-ability cooperative learning (HACL) and inquiry-based computer simulation with friendship cooperative learning (FCL) on (a) scientific reasoning (SR) and (b) conceptual understanding (CU) among Form Four students in Malaysian Smart…

  11. Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

    PubMed Central

    Kadima, Hubert; Granado, Bertrand

    2013-01-01

    We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach. PMID:24319361

  12. Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

    PubMed

    Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand

    2013-01-01

    We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

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

    Vinnikov, B.; NRC Kurchatov Inst.

    According to Scientific and Technical Cooperation between the USA and Russia in the field of nuclear engineering the Idaho National Laboratory has transferred to the possession of the National Research Center ' Kurchatov Inst. ' the SAPHIRE software without any fee. With the help of the software Kurchatov Inst. developed a Pilot Living PSA- Model of Leningrad NPP Unit 1. Computations of core damage frequencies were carried out for additional Initiating Events. In the submitted paper such additional Initiating Events are fires in various compartments of the NPP. During the computations of each fire, structure of the PSA - Modelmore » was not changed, but Fault Trees for the appropriate systems, which are removed from service during the fire, were changed. It follows from the computations, that for ten fires Core Damaged Frequencies (CDF) are not changed. Other six fires will cause additional core damage. On the basis of the calculated results it is possible to determine a degree of importance of these fires and to establish sequence of performance of fire-prevention measures in various places of the NPP. (authors)« less

  14. Promoting Science Literacy through Research Service-Learning--An Emerging Pedagogy with Significant Benefits for Students, Faculty, Universities, and Communities

    ERIC Educational Resources Information Center

    Reynolds, Julie A.; Ahern-Dodson, Jennifer

    2010-01-01

    Research service-learning (RSL) is an emerging pedagogy in which students engage in research within a service-learning context. This approach has great potential to promote science literacy because it teaches students how to use scientific knowledge and scientific ways of thinking in the service of society and helps them to better appreciate the…

  15. ESA's Planetary Science Archive: Preserve and present reliable scientific data sets

    NASA Astrophysics Data System (ADS)

    Besse, S.; Vallat, C.; Barthelemy, M.; Coia, D.; Costa, M.; De Marchi, G.; Fraga, D.; Grotheer, E.; Heather, D.; Lim, T.; Martinez, S.; Arviset, C.; Barbarisi, I.; Docasal, R.; Macfarlane, A.; Rios, C.; Saiz, J.; Vallejo, F.

    2018-01-01

    The European Space Agency (ESA) Planetary Science Archive (PSA) is undergoing a significant refactoring of all its components to improve the services provided to the scientific community and the public. The PSA supports ESA's missions exploring the Solar System by archiving scientific peer-reviewed observations as well as engineering data sets. This includes the Giotto, SMART-1, Huygens, Venus Express, Mars Express, Rosetta, Exomars 2016, Exomars RSP, BepiColombo, and JUICE missions. The PSA is offering a newly designed graphical user interface which is simultaneously meant to maximize the interaction with scientific observations and also minimise the efforts needed to download these scientific observations. The PSA still offers the same services as before (i.e., FTP, documentation, helpdesk, etc.). In addition, it will support the two formats of the Planetary Data System (i.e., PDS3 and PDS4), as well as providing new ways for searching the data products with specific metadata and geometrical parameters. As well as enhanced services, the PSA will also provide new services to improve the visualisation of data products and scientific content (e.g., spectra, etc.). Together with improved access to the spacecraft engineering data sets, the PSA will provide easier access to scientific data products that will help to maximize the science return of ESA's space missions.

  16. Biodiversity and ecosystem services science for a sustainable planet: the DIVERSITAS vision for 2012-20.

    PubMed

    Larigauderie, Anne; Prieur-Richard, Anne-Hélène; Mace, Georgina M; Lonsdale, Mark; Mooney, Harold A; Brussaard, Lijbert; Cooper, David; Cramer, Wolfgang; Daszak, Peter; Díaz, Sandra; Duraiappah, Anantha; Elmqvist, Thomas; Faith, Daniel P; Jackson, Louise E; Krug, Cornelia; Leadley, Paul W; Le Prestre, Philippe; Matsuda, Hiroyuki; Palmer, Margaret; Perrings, Charles; Pulleman, Mirjam; Reyers, Belinda; Rosa, Eugene A; Scholes, Robert J; Spehn, Eva; Turner, Bl; Yahara, Tetsukazu

    2012-02-01

    DIVERSITAS, the international programme on biodiversity science, is releasing a strategic vision presenting scientific challenges for the next decade of research on biodiversity and ecosystem services: "Biodiversity and Ecosystem Services Science for a Sustainable Planet". This new vision is a response of the biodiversity and ecosystem services scientific community to the accelerating loss of the components of biodiversity, as well as to changes in the biodiversity science-policy landscape (establishment of a Biodiversity Observing Network - GEO BON, of an Intergovernmental science-policy Platform on Biodiversity and Ecosystem Services - IPBES, of the new Future Earth initiative; and release of the Strategic Plan for Biodiversity 2011-2020). This article presents the vision and its core scientific challenges.

  17. Making Scientific Data Usable and Useful

    NASA Astrophysics Data System (ADS)

    Satwicz, T.; Bharadwaj, A.; Evans, J.; Dirks, J.; Clark Cole, K.

    2017-12-01

    Transforming geological data into information that has broad scientific and societal impact is a process fraught with barriers. Data sets and tools are often reported to have poor user experiences (UX) that make scientific work more challenging than it needs be. While many other technical fields have benefited from ongoing improvements to the UX of their tools (e.g., healthcare and financial services) scientists are faced with using tools that are labor intensive and not intuitive. Our research team has been involved in a multi-year effort to understand and improve the UX of scientific tools and data sets. We use a User-Centered Design (UCD) process that involves naturalistic behavioral observation and other qualitative research methods adopted from Human-Computer Interaction (HCI) and related fields. Behavioral observation involves having users complete common tasks on data sets, tools, and websites to identify usability issues and understand the severity of the issues. We measure how successfully they complete tasks and diagnosis the cause of any failures. Behavioral observation is paired with in-depth interviews where users describe their process for generating results (from initial inquiry to final results). By asking detailed questions we unpack common patterns and challenges scientists experience while working with data. We've found that tools built using the UCD process can have a large impact on scientist work flows and greatly reduce the time it takes to process data before analysis. It is often challenging to understand the organization and nuances of data across scientific fields. By better understanding how scientists work we can create tools that make routine tasks less-labor intensive, data easier to find, and solve common issues with discovering new data sets and engaging in interdisciplinary research. There is a tremendous opportunity for advancing scientific knowledge and helping the public benefit from that work by creating intuitive, interactive, and powerful tools and resources for generating knowledge. The pathway to achieving that is through building a detailed understanding of users and their needs, then using this knowledge to inform the design of the data products, tools, and services scientists and non-scientists use to do their work.

  18. ENES the European Network for Earth System modelling and its infrastructure projects IS-ENES

    NASA Astrophysics Data System (ADS)

    Guglielmo, Francesca; Joussaume, Sylvie; Parinet, Marie

    2016-04-01

    The scientific community working on climate modelling is organized within the European Network for Earth System modelling (ENES). In the past decade, several European university departments, research centres, meteorological services, computer centres, and industrial partners engaged in the creation of ENES with the purpose of working together and cooperating towards the further development of the network, by signing a Memorandum of Understanding. As of 2015, the consortium counts 47 partners. The climate modelling community, and thus ENES, faces challenges which are both science-driven, i.e. analysing of the full complexity of the Earth System to improve our understanding and prediction of climate changes, and have multi-faceted societal implications, as a better representation of climate change on regional scales leads to improved understanding and prediction of impacts and to the development and provision of climate services. ENES, promoting and endorsing projects and initiatives, helps in developing and evaluating of state-of-the-art climate and Earth system models, facilitates model inter-comparison studies, encourages exchanges of software and model results, and fosters the use of high performance computing facilities dedicated to high-resolution multi-model experiments. ENES brings together public and private partners, integrates countries underrepresented in climate modelling studies, and reaches out to different user communities, thus enhancing European expertise and competitiveness. In this need of sophisticated models, world-class, high-performance computers, and state-of-the-art software solutions to make efficient use of models, data and hardware, a key role is played by the constitution and maintenance of a solid infrastructure, developing and providing services to the different user communities. ENES has investigated the infrastructural needs and has received funding from the EU FP7 program for the IS-ENES (InfraStructure for ENES) phase I and II projects. We present here the case study of an existing network of institutions brought together toward common goals by a non-binding agreement, ENES, and of its two IS-ENES projects. These latter will be discussed in their double role as a means to provide and/or maintain the actual infrastructure (hardware, software, skilled human resources, services) to achieve ENES scientific goals -fulfilling the aims set in a strategy document-, but also to inform and provide to the network a structured way of working and of interacting with the extended community. The genesis and evolution of the network and the interaction network/projects will also be analysed in terms of long-term sustainability.

  19. Virtual Geophysics Laboratory: Exploiting the Cloud and Empowering Geophysicsts

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  20. RIACS/USRA

    NASA Technical Reports Server (NTRS)

    Oliger, Joseph

    1993-01-01

    The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing, Advanced Methods for Scientific Computing, High Performance Networks and Technology, and Learning Systems. Parallel compiler techniques, adaptive numerical methods for flows in complicated geometries, and optimization were identified as important problems to investigate for ARC's involvement in the Computational Grand Challenges of the next decade.

  1. A framework to evaluate proposals for scientific activities in wilderness

    Treesearch

    Peter Landres

    2010-01-01

    Every year, the four Federal wilderness management agencies - U.S. DOI Bureau of Land Management, Fish and Wildlife Service, National Park Service, and the USDA Forest Service - receive hundreds of proposals to conduct scientific studies within wilderness. There is no consistent and comprehensive framework for evaluating such proposals that accounts for the unique...

  2. Scientific and Technological Information Services in Australia: I. History and Development

    ERIC Educational Resources Information Center

    Middleton, Michael

    2006-01-01

    An investigation of the development of Australian scientific and technological information (STI) services has been undertaken. It comprises a consideration of the characteristics and development of the services, which is the focus of this part of the paper, along with a broader examination of discipline formation in information management covered…

  3. Virtual Exploitation Environment Demonstration for Atmospheric Missions

    NASA Astrophysics Data System (ADS)

    Natali, Stefano; Mantovani, Simone; Hirtl, Marcus; Santillan, Daniel; Triebnig, Gerhard; Fehr, Thorsten; Lopes, Cristiano

    2017-04-01

    The scientific and industrial communities are being confronted with a strong increase of Earth Observation (EO) satellite missions and related data. This is in particular the case for the Atmospheric Sciences communities, with the upcoming Copernicus Sentinel-5 Precursor, Sentinel-4, -5 and -3, and ESA's Earth Explorers scientific satellites ADM-Aeolus and EarthCARE. The challenge is not only to manage the large volume of data generated by each mission / sensor, but to process and analyze the data streams. Creating synergies among the different datasets will be key to exploit the full potential of the available information. As a preparation activity supporting scientific data exploitation for Earth Explorer and Sentinel atmospheric missions, ESA funded the "Technology and Atmospheric Mission Platform" (TAMP) [1] [2] project; a scientific and technological forum (STF) has been set-up involving relevant European entities from different scientific and operational fields to define the platforḿs requirements. Data access, visualization, processing and download services have been developed to satisfy useŕs needs; use cases defined with the STF, such as study of the SO2 emissions for the Holuhraun eruption (2014) by means of two numerical models, two satellite platforms and ground measurements, global Aerosol analyses from long time series of satellite data, and local Aerosol analysis using satellite and LIDAR, have been implemented to ensure acceptance of TAMP by the atmospheric sciences community. The platform pursues the "virtual workspace" concept: all resources (data, processing, visualization, collaboration tools) are provided as "remote services", accessible through a standard web browser, to avoid the download of big data volumes and for allowing utilization of provided infrastructure for computation, analysis and sharing of results. Data access and processing are achieved through standardized protocols (WCS, WPS). As evolution toward a pre-operational environment, the "Virtual Exploitation Environment Demonstration for Atmospheric Missions" (VEEDAM) aims at maintaining, running and evolving the platform, demonstrating e.g. the possibility to perform massive processing over heterogeneous data sources. This work presents the VEEDAM concepts, provides pre-operational examples, stressing on the interoperability achievable exposing standardized data access and processing services (e.g. making accessible data and processing resources from different VREs). [1] TAMP platform landing page http://vtpip.zamg.ac.at/ [2] TAMP introductory video https://www.youtube.com/watch?v=xWiy8h1oXQY

  4. The emergence of spatial cyberinfrastructure.

    PubMed

    Wright, Dawn J; Wang, Shaowen

    2011-04-05

    Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge.

  5. The emergence of spatial cyberinfrastructure

    PubMed Central

    Wright, Dawn J.; Wang, Shaowen

    2011-01-01

    Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge. PMID:21467227

  6. [AERA. Dream machines and computing practices at the Mathematical Center].

    PubMed

    Alberts, Gerard; De Beer, Huub T

    2008-01-01

    Dream machines may be just as effective as the ones materialised. Their symbolic thrust can be quite powerful. The Amsterdam 'Mathematisch Centrum' (Mathematical Center), founded February 11, 1946, created a Computing Department in an effort to realise its goal of serving society. When Aad van Wijngaarden was appointed as head of the Computing Department, however, he claimed space for scientific research and computer construction, next to computing as a service. Still, the computing service following the five stage style of Hartree's numerical analysis remained a dominant characteristic of the work of the Computing Department. The high level of ambition held by Aad van Wijngaarden lead to ever renewed projections of big automatic computers, symbolised by the never-built AERA. Even a machine that was actually constructed, the ARRA which followed A.D. Booth's design of the ARC, never made it into real operation. It did serve Van Wijngaarden to bluff his way into the computer age by midsummer 1952. Not until January 1954 did the computing department have a working stored program computer, which for reasons of policy went under the same name: ARRA. After just one other machine, the ARMAC, had been produced, a separate company, Electrologica, was set up for the manufacture of computers, which produced the rather successful X1 computer. The combination of ambition and absence of a working machine lead to a high level of work on programming, way beyond the usual ideas of libraries of subroutines. Edsger W. Dijkstra in particular led the way to an emphasis on the duties of the programmer within the pattern of numerical analysis. Programs generating programs, known elsewhere as autocoding systems, were at the 'Mathematisch Centrum' called 'superprograms'. Practical examples were usually called a 'complex', in Dutch, where in English one might say 'system'. Historically, this is where software begins. Dekker's matrix complex, Dijkstra's interrupt system, Dijkstra and Zonneveld's ALGOL compiler--which for housekeeping contained 'the complex'--were actual examples of such super programs. In 1960 this compiler gave the Mathematical Center a leading edge in the early development of software.

  7. 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.

  8. [Preventive programmes for school children. Organization, duties and activities of the School Health Service of the city of Basel].

    PubMed

    Ritzel, G; Mühlemann, R

    1978-07-01

    From a historical point of view it was the federal tuberculosis law of 1928 which gave an impulse to the Swiss School health services. Almost simultaneously a psychological service for school children was established in Basle. Besides physicians and psychologists, the present staff comprises speech pathologists and scientific coworkers. The mandate issued by the canton's government is mostly geared toward prevention of somatic, psychological and social disorders in the individual child and in risk groups, in the sense of social pediatrics. Carrying out this mandate requires a unity of investigation methods and the decisions resulting from findings. The statistical evaluation of epidemiological data depends on efficient computer use. High priority is given to data protection. With reference to the basic possibilities and limitations of activities in preventive medicine, questions of goals, acceptability and acceptance, curability and cost-benefit are discussed. The competitive situation between therapy and prevention is critically considered. An interdisciplinary approach including all the helping professions is strongly suggested.

  9. Science Teaching Attitudes and Scientific Attitudes of Pre-Service Teachers of Gifted Students

    ERIC Educational Resources Information Center

    Erdogan, Sezen Camci

    2017-01-01

    The purpose of this study is to determine science teaching attitudes and scientific attitudes of pre-service teachers of gifted students due to gender and grade level and also correlation among these variables. It is a survey study that the group is 82 students attending Gifted Education undergraduate level. Data is gathered by Scientific Attitude…

  10. Thai Pre-Service Science Teachers' Struggles in Using Socio-Scientific Issues (SSIs) during Practicum

    ERIC Educational Resources Information Center

    Pitiporntapin, Sasithep; Yutakom, Naruemon; Sadler, Troy D.

    2016-01-01

    In educational reform, teaching through socio-scientific issues (SSIs) is considered the best way to promote scientific literacy for citizenship as the goal of science teaching. To bring SSIs into the science classroom, Thai pre-service science teachers (PSTs) are expected to understand the concept of SSI-based teaching and to use it effectively…

  11. Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

    NASA Astrophysics Data System (ADS)

    Adakin, A.; Anisenkov, A.; Belov, S.; Chubarov, D.; Kalyuzhny, V.; Kaplin, V.; Korol, A.; Kuchin, N.; Lomakin, S.; Nikultsev, V.; Skovpen, K.; Sukharev, A.; Zaytsev, A.

    2012-12-01

    Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM&MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM&MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

  12. Advanced Optical Burst Switched Network Concepts

    NASA Astrophysics Data System (ADS)

    Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

    In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

  13. Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

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

    Prowell, Stacy J; Symons, Christopher T

    2015-01-01

    Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.

  14. Root resorption during orthodontic treatment.

    PubMed

    Walker, Sally

    2010-01-01

    Medline, Embase, LILACS, The Cochrane Library (Cochrane Database of Systematic Reviews, CENTRAL, and Cochrane Oral Health Group Trials Register) Web of Science, EBM Reviews, Computer Retrieval of Information on Scientific Project (CRISP, www.crisp.cit.nih.gov), On-Line Computer Library Center (www.oclc.org), Google Index to Scientific and Technical Proceedings, PAHO (www.paho.org), WHOLis (www.who.int/library/databases/en), BBO (Brazilian Bibliography of Dentistry), CEPS (Chinese Electronic Periodical Services), Conference materials (www.bl.uk/services/bsds/dsc/conference.html), ProQuest Dissertation Abstracts and Thesis database, TrialCentral (www.trialscentral.org), National Research Register (www.controlled-trials.com), www.Clinicaltrials.gov and SIGLE (System for Information on Grey Literature in Europe). Randomised controlled trials including split mouth design, recording the presence or absence of external apical root resorption (EARR) by treatment group at the end of the treatment period. Data were extracted independently by two reviewers using specially designed and piloted forms. Quality was also assessed independently by the same reviewers. After evaluating titles and abstracts, 144 full articles were obtained of which 13 articles, describing 11 trials, fulfilled the criteria for inclusion. Differences in the methodological approaches and reporting results made quantitative statistical comparisons impossible. Evidence suggests that comprehensive orthodontic treatment causes increased incidence and severity of root resorption, and heavy forces might be particularly harmful. Orthodontically induced inflammatory root resorption is unaffected by archwire sequencing, bracket prescription, and self-ligation. Previous trauma and tooth morphology are unlikely causative factors. There is some evidence that a two- to three-month pause in treatment decreases total root resorption. The results were inconclusive in the clinical management of root resorption, but there is evidence to support the use of light forces, especially with incisor intrusion.

  15. Collaborative workbench for cyberinfrastructure to accelerate science algorithm development

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. Quantum Testbeds Stakeholder Workshop (QTSW) Report meeting purpose and agenda.

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

    Hebner, Gregory A.

    Quantum computing (QC) is a promising early-stage technology with the potential to provide scientific computing capabilities far beyond what is possible with even an Exascale computer in specific problems of relevance to the Office of Science. These include (but are not limited to) materials modeling, molecular dynamics, and quantum chromodynamics. However, commercial QC systems are not yet available and the technical maturity of current QC hardware, software, algorithms, and systems integration is woefully incomplete. Thus, there is a significant opportunity for DOE to define the technology building blocks, and solve the system integration issues to enable a revolutionary tool. Oncemore » realized, QC will have world changing impact on economic competitiveness, the scientific enterprise, and citizen well-being. Prior to this workshop, DOE / Office of Advanced Scientific Computing Research (ASCR) hosted a workshop in 2015 to explore QC scientific applications. The goal of that workshop was to assess the viability of QC technologies to meet the computational requirements in support of DOE’s science and energy mission and to identify the potential impact of these technologies.« less

  17. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

    DOE PAGES

    Haidar, Azzam; Jagode, Heike; Vaccaro, Phil; ...

    2018-03-22

    The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

  18. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

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

    Haidar, Azzam; Jagode, Heike; Vaccaro, Phil

    The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

  19. 77 FR 8330 - Health Services Research and Development Service Scientific Merit Review Board; Notice of Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-14

    ... Disorders; HCR 2--Substance Use Disorders; HCR 3--Rehabilitation/Rural; HCR 4--Women's Health; HCR 5--Pain... Development Service Scientific Merit Review Board will meet on March 6-8, 2012, at the Hilton New Orleans... to the Chief Research and Development Officer. On March 6, the subcommittee on Nursing Research...

  20. Educating Science Teachers in the Twenty-First Century: Implications for Pre-Service Teacher Education

    ERIC Educational Resources Information Center

    Tan, Aik-Ling; Lee, Peter Peng Foo; Cheah, Yin Hong

    2017-01-01

    This study examines the verbal interactions among a group of pre-service teachers as they engaged in scientific discussions in a medicinal chemistry course. These discussions were part of the course that encompassed an explicit instruction of scientific argumentation structures as well as an applied component, whereby the pre-service teachers…

  1. Exploring the use of I/O nodes for computation in a MIMD multiprocessor

    NASA Technical Reports Server (NTRS)

    Kotz, David; Cai, Ting

    1995-01-01

    As parallel systems move into the production scientific-computing world, the emphasis will be on cost-effective solutions that provide high throughput for a mix of applications. Cost effective solutions demand that a system make effective use of all of its resources. Many MIMD multiprocessors today, however, distinguish between 'compute' and 'I/O' nodes, the latter having attached disks and being dedicated to running the file-system server. This static division of responsibilities simplifies system management but does not necessarily lead to the best performance in workloads that need a different balance of computation and I/O. Of course, computational processes sharing a node with a file-system service may receive less CPU time, network bandwidth, and memory bandwidth than they would on a computation-only node. In this paper we begin to examine this issue experimentally. We found that high performance I/O does not necessarily require substantial CPU time, leaving plenty of time for application computation. There were some complex file-system requests, however, which left little CPU time available to the application. (The impact on network and memory bandwidth still needs to be determined.) For applications (or users) that cannot tolerate an occasional interruption, we recommend that they continue to use only compute nodes. For tolerant applications needing more cycles than those provided by the compute nodes, we recommend that they take full advantage of both compute and I/O nodes for computation, and that operating systems should make this possible.

  2. Requirements for a network storage service

    NASA Technical Reports Server (NTRS)

    Kelly, Suzanne M.; Haynes, Rena A.

    1992-01-01

    Sandia National Laboratories provides a high performance classified computer network as a core capability in support of its mission of nuclear weapons design and engineering, physical sciences research, and energy research and development. The network, locally known as the Internal Secure Network (ISN), was designed in 1989 and comprises multiple distributed local area networks (LAN's) residing in Albuquerque, New Mexico and Livermore, California. The TCP/IP protocol suite is used for inner-node communications. Scientific workstations and mid-range computers, running UNIX-based operating systems, compose most LAN's. One LAN, operated by the Sandia Corporate Computing Directorate, is a general purpose resource providing a supercomputer and a file server to the entire ISN. The current file server on the supercomputer LAN is an implementation of the Common File System (CFS) developed by Los Alamos National Laboratory. Subsequent to the design of the ISN, Sandia reviewed its mass storage requirements and chose to enter into a competitive procurement to replace the existing file server with one more adaptable to a UNIX/TCP/IP environment. The requirements study for the network was the starting point for the requirements study for the new file server. The file server is called the Network Storage Services (NSS) and is requirements are described in this paper. The next section gives an application or functional description of the NSS. The final section adds performance, capacity, and access constraints to the requirements.

  3. Bringing Web 2.0 to bioinformatics.

    PubMed

    Zhang, Zhang; Cheung, Kei-Hoi; Townsend, Jeffrey P

    2009-01-01

    Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.

  4. Idle waves in high-performance computing

    NASA Astrophysics Data System (ADS)

    Markidis, Stefano; Vencels, Juris; Peng, Ivy Bo; Akhmetova, Dana; Laure, Erwin; Henri, Pierre

    2015-01-01

    The vast majority of parallel scientific applications distributes computation among processes that are in a busy state when computing and in an idle state when waiting for information from other processes. We identify the propagation of idle waves through processes in scientific applications with a local information exchange between the two processes. Idle waves are nondispersive and have a phase velocity inversely proportional to the average busy time. The physical mechanism enabling the propagation of idle waves is the local synchronization between two processes due to remote data dependency. This study provides a description of the large number of processes in parallel scientific applications as a continuous medium. This work also is a step towards an understanding of how localized idle periods can affect remote processes, leading to the degradation of global performance in parallel scientific applications.

  5. 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.

  6. Comparisons of some large scientific computers

    NASA Technical Reports Server (NTRS)

    Credeur, K. R.

    1981-01-01

    In 1975, the National Aeronautics and Space Administration (NASA) began studies to assess the technical and economic feasibility of developing a computer having sustained computational speed of one billion floating point operations per second and a working memory of at least 240 million words. Such a powerful computer would allow computational aerodynamics to play a major role in aeronautical design and advanced fluid dynamics research. Based on favorable results from these studies, NASA proceeded with developmental plans. The computer was named the Numerical Aerodynamic Simulator (NAS). To help insure that the estimated cost, schedule, and technical scope were realistic, a brief study was made of past large scientific computers. Large discrepancies between inception and operation in scope, cost, or schedule were studied so that they could be minimized with NASA's proposed new compter. The main computers studied were the ILLIAC IV, STAR 100, Parallel Element Processor Ensemble (PEPE), and Shuttle Mission Simulator (SMS) computer. Comparison data on memory and speed were also obtained on the IBM 650, 704, 7090, 360-50, 360-67, 360-91, and 370-195; the CDC 6400, 6600, 7600, CYBER 203, and CYBER 205; CRAY 1; and the Advanced Scientific Computer (ASC). A few lessons learned conclude the report.

  7. Bringing numerous methods for expression and promoter analysis to a public cloud computing service.

    PubMed

    Polanski, Krzysztof; Gao, Bo; Mason, Sam A; Brown, Paul; Ott, Sascha; Denby, Katherine J; Wild, David L

    2018-03-01

    Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project. The integrated apps can be found at http://www.cyverse.org/discovery-environment, while the raw code is available at https://github.com/cyversewarwick and the corresponding Docker images are housed at https://hub.docker.com/r/cyversewarwick/. info@cyverse.warwick.ac.uk or D.L.Wild@warwick.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  8. TIPTOPbase: the Iron Project and the Opacity Project Atomic Database

    NASA Astrophysics Data System (ADS)

    Mendoza, Claudio; Nahar, Sultana; Pradhan, Anil; Seaton, Micheal; Zeippen, Claude

    2001-05-01

    The Opacity Project, the IRON Project, and the RmaX Network (The Opacity Project Team, Vol.1,2), IOPP, Bristol (1995,1996); Hummer et al., Astron. Astrophys. 279, 298 (1993) are international computational efforts concerned with the production of high quality atomic data for astrophysical applications. Research groups from Canada, France, Germany, UK, USA and Venezuela are involved. Extensive data sets containing accurate energy levels, f-values, A-values, photoionisation cross sections, collision strengths, recombination rates, and opacitites have been computed for cosmically abundant elements using state-of-the-art atomic physics codes. Their volume, completeness and overall accuracy are presently unmatched in the field of laboratory astrophysics. Some of the data sets have been available since 1993 from a public on-line database service referred to as TOPbase (Cunto et al Astron. Astrophys. 275), L5 (1993), ( http://cdsweb.u-strasbg.fr/OP.html at CDS France, and http://heasarc.gsfc.nasa.gov/topbase, at NSAS USA). We are currently involved in a major effort to scale the existing database services to develop a robust platform for the high-profile dissemination of atomic data to the scientific community within the next 12 months. (Partial support from the NSF and NASA is acknowledged.)

  9. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

    NASA Astrophysics Data System (ADS)

    Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

    2017-01-01

    Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

  10. USSR Report: Cybernetics, Computers and Automation Technology. No. 69.

    DTIC Science & Technology

    1983-05-06

    computers in multiprocessor and multistation design , control and scientific research automation systems. The results of comparing the efficiency of...Podvizhnaya, Scientific Research Institute of Control Computers, Severodonetsk] [Text] The most significant change in the design of the SM-2M compared to...UPRAVLYAYUSHCHIYE SISTEMY I MASHINY, Nov-Dec 82) 95 APPLICATIONS Kiev Automated Control System, Design Features and Prospects for Development (V. A

  11. Monitoring of IaaS and scientific applications on the Cloud using the Elasticsearch ecosystem

    NASA Astrophysics Data System (ADS)

    Bagnasco, S.; Berzano, D.; Guarise, A.; Lusso, S.; Masera, M.; Vallero, S.

    2015-05-01

    The private Cloud at the Torino INFN computing centre offers IaaS services to different scientific computing applications. The infrastructure is managed with the OpenNebula cloud controller. The main stakeholders of the facility are a grid Tier-2 site for the ALICE collaboration at LHC, an interactive analysis facility for the same experiment and a grid Tier-2 site for the BES-III collaboration, plus an increasing number of other small tenants. Besides keeping track of the usage, the automation of dynamic allocation of resources to tenants requires detailed monitoring and accounting of the resource usage. As a first investigation towards this, we set up a monitoring system to inspect the site activities both in terms of IaaS and applications running on the hosted virtual instances. For this purpose we used the Elasticsearch, Logstash and Kibana stack. In the current implementation, the heterogeneous accounting information is fed to different MySQL databases and sent to Elasticsearch via a custom Logstash plugin. For the IaaS metering, we developed sensors for the OpenNebula API. The IaaS level information gathered through the API is sent to the MySQL database through an ad-hoc developed RESTful web service, which is also used for other accounting purposes. Concerning the application level, we used the Root plugin TProofMonSenderSQL to collect accounting data from the interactive analysis facility. The BES-III virtual instances used to be monitored with Zabbix, as a proof of concept we also retrieve the information contained in the Zabbix database. Each of these three cases is indexed separately in Elasticsearch. We are now starting to consider dismissing the intermediate level provided by the SQL database and evaluating a NoSQL option as a unique central database for all the monitoring information. We setup a set of Kibana dashboards with pre-defined queries in order to monitor the relevant information in each case. In this way we have achieved a uniform monitoring interface for both the IaaS and the scientific applications, mostly leveraging off-the-shelf tools.

  12. Analysis, Mining and Visualization Service at NCSA

    NASA Astrophysics Data System (ADS)

    Wilhelmson, R.; Cox, D.; Welge, M.

    2004-12-01

    NCSA's goal is to create a balanced system that fully supports high-end computing as well as: 1) high-end data management and analysis; 2) visualization of massive, highly complex data collections; 3) large databases; 4) geographically distributed Grid computing; and 5) collaboratories, all based on a secure computational environment and driven with workflow-based services. To this end NCSA has defined a new technology path that includes the integration and provision of cyberservices in support of data analysis, mining, and visualization. NCSA has begun to develop and apply a data mining system-NCSA Data-to-Knowledge (D2K)-in conjunction with both the application and research communities. NCSA D2K will enable the formation of model-based application workflows and visual programming interfaces for rapid data analysis. The Java-based D2K framework, which integrates analytical data mining methods with data management, data transformation, and information visualization tools, will be configurable from the cyberservices (web and grid services, tools, ..) viewpoint to solve a wide range of important data mining problems. This effort will use modules, such as a new classification methods for the detection of high-risk geoscience events, and existing D2K data management, machine learning, and information visualization modules. A D2K cyberservices interface will be developed to seamlessly connect client applications with remote back-end D2K servers, providing computational resources for data mining and integration with local or remote data stores. This work is being coordinated with SDSC's data and services efforts. The new NCSA Visualization embedded workflow environment (NVIEW) will be integrated with D2K functionality to tightly couple informatics and scientific visualization with the data analysis and management services. Visualization services will access and filter disparate data sources, simplifying tasks such as fusing related data from distinct sources into a coherent visual representation. This approach enables collaboration among geographically dispersed researchers via portals and front-end clients, and the coupling with data management services enables recording associations among datasets and building annotation systems into visualization tools and portals, giving scientists a persistent, shareable, virtual lab notebook. To facilitate provision of these cyberservices to the national community, NCSA will be providing a computational environment for large-scale data assimilation, analysis, mining, and visualization. This will be initially implemented on the new 512 processor shared memory SGI's recently purchased by NCSA. In addition to standard batch capabilities, NCSA will provide on-demand capabilities for those projects requiring rapid response (e.g., development of severe weather, earthquake events) for decision makers. It will also be used for non-sequential interactive analysis of data sets where it is important have access to large data volumes over space and time.

  13. Accelerating scientific discovery : 2007 annual report.

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

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

    2008-11-14

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

  14. Data Processing Center of Radioastron Project: 3 years of operation.

    NASA Astrophysics Data System (ADS)

    Shatskaya, Marina

    ASC DATA PROCESSING CENTER (DPC) of Radioastron Project is a fail-safe complex centralized system of interconnected software/ hardware components along with organizational procedures. Tasks facing of the scientific data processing center are organization of service information exchange, collection of scientific data, storage of all of scientific data, data science oriented processing. DPC takes part in the informational exchange with two tracking stations in Pushchino (Russia) and Green Bank (USA), about 30 ground telescopes, ballistic center, tracking headquarters and session scheduling center. Enormous flows of information go to Astro Space Center. For the inquiring of enormous data volumes we develop specialized network infrastructure, Internet channels and storage. The computer complex has been designed at the Astro Space Center (ASC) of Lebedev Physical Institute and includes: - 800 TB on-line storage, - 2000 TB hard drive archive, - backup system on magnetic tapes (2000 TB); - 24 TB redundant storage at Pushchino Radio Astronomy Observatory; - Web and FTP servers, - DPC management and data transmission networks. The structure and functions of ASC Data Processing Center are fully adequate to the data processing requirements of the Radioastron Mission and has been successfully confirmed during Fringe Search, Early Science Program and first year of Key Science Program.

  15. Using Social Media to Promote Pre-Service Science Teachers' Practices of Socio-Scientific Issue (SSI) - Based Teaching

    ERIC Educational Resources Information Center

    Pitiporntapin, Sasithep; Lankford, Deanna Marie

    2015-01-01

    This paper addresses using social media to promote pre-service science teachers' practices of Socio-Scientific Issue (SSI) based teaching in a science classroom setting. We designed our research in two phases. The first phase examined pre-service science teachers' perceptions about using social media to promote their SSI-based teaching. The…

  16. Pre-Service Science Teachers' Written Argumentation Qualities: From the Perspectives of Socio- Scientific Issues, Epistemic Belief Levels and Online Discussion Environment

    ERIC Educational Resources Information Center

    Isbilir, Erdinc; Cakiroglu, Jale; Ertepinar, Hamide

    2014-01-01

    This study investigated the relationship between pre-service science teachers' written argumentation levels about socio-scientific issues and epistemic belief levels in an online discussion environment. A mixed-methods approach was used: 30 Turkish pre-service science teachers contributed with their written argumentations to four socio-scientific…

  17. 75 FR 35075 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-21

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... unwarranted invasion of personal privacy. Name of Committee: Center for Scientific Review Special Emphasis..., PhD, Scientific Review Officer, Center for Scientific Review, National Institutes of Health, 6701...

  18. 78 FR 9064 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-07

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... unwarranted invasion of personal privacy. Name of Committee: Center for Scientific Review Special Emphasis..., Ph.D., Scientific Review Officer, Center for Scientific Review, National Institutes of Health, 6701...

  19. 76 FR 35454 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-17

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel, PAR10-074...D, Scientific Review Officer, Center for Scientific Review, National Institutes of Health, 6701...

  20. 77 FR 33476 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-06

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel; Small Business... Person: John Firrell, Ph.D., Scientific Review Officer, Center for Scientific Review, National Institutes...

  1. 78 FR 66026 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-04

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel; Member Conflict...: Julius Cinque, MS, Scientific Review Officer, Center for Scientific Review, National Institutes of Health...

  2. Consolidation and development roadmap of the EMI middleware

    NASA Astrophysics Data System (ADS)

    Kónya, B.; Aiftimiei, C.; Cecchi, M.; Field, L.; Fuhrmann, P.; Nilsen, J. K.; White, J.

    2012-12-01

    Scientific research communities have benefited recently from the increasing availability of computing and data infrastructures with unprecedented capabilities for large scale distributed initiatives. These infrastructures are largely defined and enabled by the middleware they deploy. One of the major issues in the current usage of research infrastructures is the need to use similar but often incompatible middleware solutions. The European Middleware Initiative (EMI) is a collaboration of the major European middleware providers ARC, dCache, gLite and UNICORE. EMI aims to: deliver a consolidated set of middleware components for deployment in EGI, PRACE and other Distributed Computing Infrastructures; extend the interoperability between grids and other computing infrastructures; strengthen the reliability of the services; establish a sustainable model to maintain and evolve the middleware; fulfil the requirements of the user communities. This paper presents the consolidation and development objectives of the EMI software stack covering the last two years. The EMI development roadmap is introduced along the four technical areas of compute, data, security and infrastructure. The compute area plan focuses on consolidation of standards and agreements through a unified interface for job submission and management, a common format for accounting, the wide adoption of GLUE schema version 2.0 and the provision of a common framework for the execution of parallel jobs. The security area is working towards a unified security model and lowering the barriers to Grid usage by allowing users to gain access with their own credentials. The data area is focusing on implementing standards to ensure interoperability with other grids and industry components and to reuse already existing clients in operating systems and open source distributions. One of the highlights of the infrastructure area is the consolidation of the information system services via the creation of a common information backbone.

  3. RAPPORT: running scientific high-performance computing applications on the cloud.

    PubMed

    Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

    2013-01-28

    Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

  4. 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.

  5. Shepherds' local knowledge and scientific data on the scavenging ecosystem service: Insights for conservation.

    PubMed

    Morales-Reyes, Zebensui; Martín-López, Berta; Moleón, Marcos; Mateo-Tomás, Patricia; Olea, Pedro P; Arrondo, Eneko; Donázar, José A; Sánchez-Zapata, José A

    2018-05-05

    Integrating indigenous and local knowledge (ILK) and scientific knowledge (SK) in the evaluation of ecosystem services has been recommended by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. We examined the similarities and contradictions between shepherds' ILK and SK on the scavenging service provided by vertebrates in Spain. We conducted 73 face-to-face surveys with shepherds to evaluate their ILK. We collected scientific information on 20 scavenger species by monitoring the consumption of 45 livestock carcasses with camera traps. We found a high consistency between ILK and SK regarding the provision of the scavenging service by vertebrates, which was also consistent over the range of shepherd ages and experience. Our findings support the importance of ILK held by shepherds to better understand and to collect information on the scavenging service, particularly at the species level. The integration of ILK and SK into the management strategies of scavengers can benefit the conservation of globally endangered scavengers and the ecosystem services they provide.

  6. Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis.

    PubMed

    Weber, Nick; Liou, David; Dommer, Jennifer; MacMenamin, Philip; Quiñones, Mariam; Misner, Ian; Oler, Andrew J; Wan, Joe; Kim, Lewis; Coakley McCarthy, Meghan; Ezeji, Samuel; Noble, Karlynn; Hurt, Darrell E

    2018-04-15

    Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools. The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions. https://nephele.niaid.nih.gov and https://github.com/niaid/Nephele. darrell.hurt@nih.gov.

  7. Distributed data mining on grids: services, tools, and applications.

    PubMed

    Cannataro, Mario; Congiusta, Antonio; Pugliese, Andrea; Talia, Domenico; Trunfio, Paolo

    2004-12-01

    Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.

  8. Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis

    PubMed Central

    Weber, Nick; Liou, David; Dommer, Jennifer; MacMenamin, Philip; Quiñones, Mariam; Misner, Ian; Oler, Andrew J; Wan, Joe; Kim, Lewis; Coakley McCarthy, Meghan; Ezeji, Samuel; Noble, Karlynn; Hurt, Darrell E

    2018-01-01

    Abstract Motivation Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools. Results The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions. Availability and implementation https://nephele.niaid.nih.gov and https://github.com/niaid/Nephele Contact darrell.hurt@nih.gov PMID:29028892

  9. Generating Animated Displays of Spacecraft Orbits

    NASA Technical Reports Server (NTRS)

    Candey, Robert M.; Chimiak, Reine A.; Harris, Bernard T.

    2005-01-01

    Tool for Interactive Plotting, Sonification, and 3D Orbit Display (TIPSOD) is a computer program for generating interactive, animated, four-dimensional (space and time) displays of spacecraft orbits. TIPSOD utilizes the programming interface of the Satellite Situation Center Web (SSCWeb) services to communicate with the SSC logic and database by use of the open protocols of the Internet. TIPSOD is implemented in Java 3D and effects an extension of the preexisting SSCWeb two-dimensional static graphical displays of orbits. Orbits can be displayed in any or all of the following seven reference systems: true-of-date (an inertial system), J2000 (another inertial system), geographic, geomagnetic, geocentric solar ecliptic, geocentric solar magnetospheric, and solar magnetic. In addition to orbits, TIPSOD computes and displays Sibeck's magnetopause and Fairfield's bow-shock surfaces. TIPSOD can be used by the scientific community as a means of projection or interpretation. It also has potential as an educational tool.

  10. Support Science by Publishing in Scientific Society Journals.

    PubMed

    Schloss, Patrick D; Johnston, Mark; Casadevall, Arturo

    2017-09-26

    Scientific societies provide numerous services to the scientific enterprise, including convening meetings, publishing journals, developing scientific programs, advocating for science, promoting education, providing cohesion and direction for the discipline, and more. For most scientific societies, publishing provides revenues that support these important activities. In recent decades, the proportion of papers on microbiology published in scientific society journals has declined. This is largely due to two competing pressures: authors' drive to publish in "glam journals"-those with high journal impact factors-and the availability of "mega journals," which offer speedy publication of articles regardless of their potential impact. The decline in submissions to scientific society journals and the lack of enthusiasm on the part of many scientists to publish in them should be matters of serious concern to all scientists because they impact the service that scientific societies can provide to their members and to science. Copyright © 2017 Schloss et al.

  11. Support Science by Publishing in Scientific Society Journals

    PubMed Central

    Johnston, Mark

    2017-01-01

    ABSTRACT Scientific societies provide numerous services to the scientific enterprise, including convening meetings, publishing journals, developing scientific programs, advocating for science, promoting education, providing cohesion and direction for the discipline, and more. For most scientific societies, publishing provides revenues that support these important activities. In recent decades, the proportion of papers on microbiology published in scientific society journals has declined. This is largely due to two competing pressures: authors’ drive to publish in “glam journals”—those with high journal impact factors—and the availability of “mega journals,” which offer speedy publication of articles regardless of their potential impact. The decline in submissions to scientific society journals and the lack of enthusiasm on the part of many scientists to publish in them should be matters of serious concern to all scientists because they impact the service that scientific societies can provide to their members and to science. PMID:28951482

  12. Characteristics of Pre-Service Teachers' Online Discourse: The Study of Local Streams

    NASA Astrophysics Data System (ADS)

    Liang, Ling L.; Ebenezer, Jazlin; Yost, Deborah S.

    2010-02-01

    This study describes the characteristics of pre-service teachers' discourse on a WebCT Bulletin Board in their investigations of local streams in an integrated mathematics and science course. A qualitative analysis of data revealed that the pre-service teachers conducted collaborative discourse in framing their research questions, conducting research and writing reports. The science teacher educator provided feedback and carefully crafted prompts to help pre-service teachers develop and refine their work. Overall, the online discourse formats enhance out-of-class communication and support collaborative group work. But the discourse on the critical examination of one another's point of views rooted in scientific inquiry appeared to be missing. It is suggested that pre-service teachers should be given more guidance and opportunities in science courses in carrying out scientific discourse that reflects reform-based scientific inquiry.

  13. Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

    2016-08-01

    This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

  14. Manual of Documentation Practices Applicable to Defence-Aerospace Scientific and Technical Information. Volume 2. Section 4 - Data Recording and Storage. Section 5 - Mechanization Systems and Operations. Section 6 - Announcement Services and Publications

    DTIC Science & Technology

    1979-07-01

    processes rely upon the coincidence of holes drilled , with considerable precision, in special cards. The computer can handle this kind of basic...PERFORMANCE 70No.12,17/2 Gray.R.A. Cabaniss,0.H. 4i.1972 63PP 57ref Indexing Terms: * Metrology /*Standards/Physics/Physicr Availability: TRC L1.20 A1-SURV...within the parent organsation is gauged to fit within this requitement. The imiphiations of this aspvct of SI processing are dealt with in detail in

  15. Activities of the Research Institute for Advanced Computer Science

    NASA Technical Reports Server (NTRS)

    Oliger, Joseph

    1994-01-01

    The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

  16. 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

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

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

    Potok, Thomas; Schuman, Catherine; Patton, Robert

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

  18. Computational science: shifting the focus from tools to models

    PubMed Central

    Hinsen, Konrad

    2014-01-01

    Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication of big data sets or complex models. As a consequence, these crucial pieces of information no longer enter the scientific record. Moreover, they have become prisoners of scientific software: many models exist only as software implementations, and the data are often stored in proprietary formats defined by the software. In this article, I argue that this emphasis on software tools over models and data is detrimental to science in the long term, and I propose a means by which this can be reversed. PMID:25309728

  19. 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

  20. The International Conference on Vector and Parallel Computing (2nd)

    DTIC Science & Technology

    1989-01-17

    Computation of the SVD of Bidiagonal Matrices" ...................................... 11 " Lattice QCD -As a Large Scale Scientific Computation...vectorizcd for the IBM 3090 Vector Facility. In addition, elapsed times " Lattice QCD -As a Large Scale Scientific have been reduced by using 3090...benchmarked Lattice QCD on a large number ofcompu- come from the wavefront solver routine. This was exten- ters: CrayX-MP and Cray 2 (vector

  1. Multi-threading: A new dimension to massively parallel scientific computation

    NASA Astrophysics Data System (ADS)

    Nielsen, Ida M. B.; Janssen, Curtis L.

    2000-06-01

    Multi-threading is becoming widely available for Unix-like operating systems, and the application of multi-threading opens new ways for performing parallel computations with greater efficiency. We here briefly discuss the principles of multi-threading and illustrate the application of multi-threading for a massively parallel direct four-index transformation of electron repulsion integrals. Finally, other potential applications of multi-threading in scientific computing are outlined.

  2. 28 CFR 0.15 - Deputy Attorney General.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Executive Service or the equivalent; Senior-Level and Scientific and Professional positions; and of... Executive Office of the President. (4) Coordinate and control the Department's reaction to civil..., including attorneys, in the Senior Executive Service or the equivalent, and Senior-Level and Scientific and...

  3. 28 CFR 0.15 - Deputy Attorney General.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Executive Service or the equivalent; Senior-Level and Scientific and Professional positions; and of... Executive Office of the President. (4) Coordinate and control the Department's reaction to civil..., including attorneys, in the Senior Executive Service or the equivalent, and Senior-Level and Scientific and...

  4. Autonomous mission planning and scheduling: Innovative, integrated, responsive

    NASA Technical Reports Server (NTRS)

    Sary, Charisse; Liu, Simon; Hull, Larry; Davis, Randy

    1994-01-01

    Autonomous mission scheduling, a new concept for NASA ground data systems, is a decentralized and distributed approach to scientific spacecraft planning, scheduling, and command management. Systems and services are provided that enable investigators to operate their own instruments. In autonomous mission scheduling, separate nodes exist for each instrument and one or more operations nodes exist for the spacecraft. Each node is responsible for its own operations which include planning, scheduling, and commanding; and for resolving conflicts with other nodes. One or more database servers accessible to all nodes enable each to share mission and science planning, scheduling, and commanding information. The architecture for autonomous mission scheduling is based upon a realistic mix of state-of-the-art and emerging technology and services, e.g., high performance individual workstations, high speed communications, client-server computing, and relational databases. The concept is particularly suited to the smaller, less complex missions of the future.

  5. Scientific Data Storage for Cloud Computing

    NASA Astrophysics Data System (ADS)

    Readey, J.

    2014-12-01

    Traditionally data storage used for geophysical software systems has centered on file-based systems and libraries such as NetCDF and HDF5. In contrast cloud based infrastructure providers such as Amazon AWS, Microsoft Azure, and the Google Cloud Platform generally provide storage technologies based on an object based storage service (for large binary objects) complemented by a database service (for small objects that can be represented as key-value pairs). These systems have been shown to be highly scalable, reliable, and cost effective. We will discuss a proposed system that leverages these cloud-based storage technologies to provide an API-compatible library for traditional NetCDF and HDF5 applications. This system will enable cloud storage suitable for geophysical applications that can scale up to petabytes of data and thousands of users. We'll also cover other advantages of this system such as enhanced metadata search.

  6. 76 FR 32221 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-03

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel, Fellowship: Cell... Person: Ross D Shonat, PH.D, Scientific Review Officer, Center for Scientific Review, National Institutes...

  7. 78 FR 13363 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-27

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel; Small Business...). Contact Person: Bukhtiar H Shah, DVM, Ph.D., Scientific Review Officer, Center for Scientific Review...

  8. 77 FR 71429 - Center For Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-30

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center For Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel Cancer Therapy... Conference Call). Contact Person: Lilia Topol, Ph.D., Scientific Review Officer, Center for Scientific Review...

  9. Comment on "Most computational hydrology is not reproducible, so is it really science?" by Christopher Hutton et al.

    NASA Astrophysics Data System (ADS)

    Añel, Juan A.

    2017-03-01

    Nowadays, the majority of the scientific community is not aware of the risks and problems associated with an inadequate use of computer systems for research, mostly for reproducibility of scientific results. Such reproducibility can be compromised by the lack of clear standards and insufficient methodological description of the computational details involved in an experiment. In addition, the inappropriate application or ignorance of copyright laws can have undesirable effects on access to aspects of great importance of the design of experiments and therefore to the interpretation of results.Plain Language SummaryThis article highlights several important issues to ensure the scientific reproducibility of results within the current scientific framework, going beyond simple documentation. Several specific examples are discussed in the field of hydrological modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AIPC.1868c0007H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AIPC.1868c0007H"><span>The first year pre-service teachers' chemical literacy in individual learning case using the fuel cell technology based-chemical enrichment book</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hernani, Saefulloh, Mudzakir, Ahmad</p> <p>2017-08-01</p> <p>This research aims to analyze chemical literacy ability of pre-service teachers based on PISA 2015 scientific competency. This research used descriptive method. Instrument that used in this research is multiple choice question that built based on scientific competency of PISA 2015. The result is grouping by PISA 2015 competency and mapped by high, medium and low GPA classified. This research involves 19 the first year pre-service teachers of 90 population that randomly chosen. According to the result, chemical literacy ability of pre-service described as follows: 1) 35.5% of sample are able to explain phenomena scientifically. Based on GPA, for high, medium and low GPA group respectively 25.0%, 40.3% and 29.2%; 2) 31.6% of sample are able to evaluate and design scientific enquiry. Based on GPA, for high, medium and low GPA group respectively 16.7%, 35.4% and 31.3%; 3) 31.6% of sample are able to Interpret data and evidence scientifically. Based on GPA, for high, medium and low GPA group respectively 50.0%, 25.0% and 37.5%; For the attitude competency, 68.4% of sample able to showing PISA attitude competency that consist of interest in science, environment awareness and Valuing scientific approaches to enquiry attitude. Based on GPA, for high, medium and low GPA group respectively 77.8%, 63.9% and 75.0%. According to the data, chemical literacy ability of pre-service teachers in average are bellow to 50.0% thereby need to be given special attention while scientific attitude are above to 50.0%.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2012-02-24/pdf/2012-4346.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2012-02-24/pdf/2012-4346.pdf"><span>77 FR 11139 - Center for Scientific Review; Notice of Closed Meetings</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2012-02-24</p> <p>...: Center for Scientific Review Special Emphasis Panel; ``Genetics and Epigenetics of Disease.'' Date: March... Scientific Review Special Emphasis Panel; Small Business: Cell, Computational, and Molecular Biology. Date...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19940000357&hterms=scientific+method&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dscientific%2Bmethod','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19940000357&hterms=scientific+method&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dscientific%2Bmethod"><span>Program Supports Scientific Visualization</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Keith, Stephan</p> <p>1994-01-01</p> <p>Primary purpose of General Visualization System (GVS) computer program is to support scientific visualization of data generated by panel-method computer program PMARC_12 (inventory number ARC-13362) on Silicon Graphics Iris workstation. Enables user to view PMARC geometries and wakes as wire frames or as light shaded objects. GVS is written in C language.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=Python&pg=2&id=EJ1042419','ERIC'); return false;" href="https://eric.ed.gov/?q=Python&pg=2&id=EJ1042419"><span>Using POGIL to Help Students Learn to Program</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Hu, Helen H.; Shepherd, Tricia D.</p> <p>2013-01-01</p> <p>POGIL has been successfully implemented in a scientific computing course to teach science students how to program in Python. Following POGIL guidelines, the authors have developed guided inquiry activities that lead student teams to discover and understand programming concepts. With each iteration of the scientific computing course, the authors…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005APS..MAR.J6001T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005APS..MAR.J6001T"><span>Scientific Discovery through Advanced Computing in Plasma Science</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tang, William</p> <p>2005-03-01</p> <p>Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of plasma turbulence in magnetically-confined high temperature plasmas. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to the computational science area.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1993AIPC..283..375T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1993AIPC..283..375T"><span>Computer network access to scientific information systems for minority universities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thomas, Valerie L.; Wakim, Nagi T.</p> <p>1993-08-01</p> <p>The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9913E..1GS','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9913E..1GS"><span>Cloud services on an astronomy data center</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Solar, Mauricio; Araya, Mauricio; Farias, Humberto; Mardones, Diego; Wang, Zhong</p> <p>2016-08-01</p> <p>The research on computational methods for astronomy performed by the first phase of the Chilean Virtual Observatory (ChiVO) led to the development of functional prototypes, implementing state-of-the-art computational methods and proposing new algorithms and techniques. The ChiVO software architecture is based on the use of the IVOA protocols and standards. These protocols and standards are grouped in layers, with emphasis on the application and data layers, because their basic standards define the minimum operation that a VO should conduct. As momentary verification, the current implementation works with a set of data, with 1 TB capacity, which comes from the reduction of the cycle 0 of ALMA. This research was mainly focused on spectroscopic data cubes coming from the cycle 0 ALMA's public data. As the dataset size increases when the cycle 1 ALMA's public data is also increasing every month, data processing is becoming a major bottleneck for scientific research in astronomy. When designing the ChiVO, we focused on improving both computation and I/ O costs, and this led us to configure a data center with 424 high speed cores of 2,6 GHz, 1 PB of storage (distributed in hard disk drives-HDD and solid state drive-SSD) and high speed communication Infiniband. We are developing a cloud based e-infrastructure for ChiVO services, in order to have a coherent framework for developing novel web services for on-line data processing in the ChiVO. We are currently parallelizing these new algorithms and techniques using HPC tools to speed up big data processing, and we will report our results in terms of data size, data distribution, number of cores and response time, in order to compare different processing and storage configurations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2010-04-26/pdf/2010-9652.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2010-04-26/pdf/2010-9652.pdf"><span>75 FR 21641 - Center for Scientific Review; Notice of Closed Meetings</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2010-04-26</p> <p>... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel; OBT IRG Member... Call). Contact Person: Angela Y. Ng, MBA, PhD, Scientific Review Officer, Center for Scientific Review...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7840E..1ET','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7840E..1ET"><span>IDP camp evolvement analysis in Darfur using VHSR optical satellite image time series and scientific visualization on virtual globes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tiede, Dirk; Lang, Stefan</p> <p>2010-11-01</p> <p>In this paper we focus on the application of transferable, object-based image analysis algorithms for dwelling extraction in a camp for internally displaced people (IDP) in Darfur, Sudan along with innovative means for scientific visualisation of the results. Three very high spatial resolution satellite images (QuickBird: 2002, 2004, 2008) were used for: (1) extracting different types of dwellings and (2) calculating and visualizing added-value products such as dwelling density and camp structure. The results were visualized on virtual globes (Google Earth and ArcGIS Explorer) revealing the analysis results (analytical 3D views,) transformed into the third dimension (z-value). Data formats depend on virtual globe software including KML/KMZ (keyhole mark-up language) and ESRI 3D shapefiles streamed as ArcGIS Server-based globe service. In addition, means for improving overall performance of automated dwelling structures using grid computing techniques are discussed using examples from a similar study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMIN53A3790B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMIN53A3790B"><span>Advances in Data Management in Remote Sensing and Climate Modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brown, P. G.</p> <p>2014-12-01</p> <p>Recent commercial interest in "Big Data" information systems has yielded little more than a sense of deja vu among scientists whose work has always required getting their arms around extremely large databases, and writing programs to explore and analyze it. On the flip side, there are some commercial DBMS startups building "Big Data" platform using techniques taken from earth science, astronomy, high energy physics and high performance computing. In this talk, we will introduce one such platform; Paradigm4's SciDB, the first DBMS designed from the ground up to combine the kinds of quality-of-service guarantees made by SQL DBMS platforms—high level data model, query languages, extensibility, transactions—with the kinds of functionality familiar to scientific users—arrays as structural building blocks, integrated linear algebra, and client language interfaces that minimize the learning curve. We will review how SciDB is used to manage and analyze earth science data by several teams of scientific users.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JPhCS.331g2031S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JPhCS.331g2031S"><span>Operating a production pilot factory serving several scientific domains</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sfiligoi, I.; Würthwein, F.; Andrews, W.; Dost, J. M.; MacNeill, I.; McCrea, A.; Sheripon, E.; Murphy, C. W.</p> <p>2011-12-01</p> <p>Pilot infrastructures are becoming prominent players in the Grid environment. One of the major advantages is represented by the reduced effort required by the user communities (also known as Virtual Organizations or VOs) due to the outsourcing of the Grid interfacing services, i.e. the pilot factory, to Grid experts. One such pilot factory, based on the glideinWMS pilot infrastructure, is being operated by the Open Science Grid at University of California San Diego (UCSD). This pilot factory is serving multiple VOs from several scientific domains. Currently the three major clients are the analysis operations of the HEP experiment CMS, the community VO HCC, which serves mostly math, biology and computer science users, and the structural biology VO NEBioGrid. The UCSD glidein factory allows the served VOs to use Grid resources distributed over 150 sites in North and South America, in Europe, and in Asia. This paper presents the steps taken to create a production quality pilot factory, together with the challenges encountered along the road.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4730470','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4730470"><span>A Comparative Study of Scientific Publications in Health Care Sciences and Services from Mainland China, Taiwan, Japan, and India (2007–2014)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Lv, Yipeng; Tang, Bihan; Liu, Xu; Xue, Chen; Liu, Yuan; Kang, Peng; Zhang, Lulu</p> <p>2015-01-01</p> <p>In this study, we aimed to compare the quantity and quality of publications in health care sciences and services journals from the Chinese mainland, Taiwan, Japan, and India. Journals in this category of the Science Citation Index Expanded were included in the study. Scientific papers were retrieved from the Web of Science online database. Quality was measured according to impact factor, citation of articles, number of articles published in top 10 journals, and the 10 most popular journals by country (area). In the field of health care sciences and services, the annual incremental rates of scientific articles published from 2007 to 2014 were higher than rates of published scientific articles in all fields. Researchers from the Chinese mainland published the most original articles and reviews and had the highest accumulated impact factors, highest total article citations, and highest average citation. Publications from India had the highest average impact factor. In the field of health care sciences and services, China has made remarkable progress during the past eight years in the annual number and percentage of scientific publications. Yet, there is room for improvement in the quantity and quality of such articles. PMID:26712774</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26712774','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26712774"><span>A Comparative Study of Scientific Publications in Health Care Sciences and Services from Mainland China, Taiwan, Japan, and India (2007-2014).</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lv, Yipeng; Tang, Bihan; Liu, Xu; Xue, Chen; Liu, Yuan; Kang, Peng; Zhang, Lulu</p> <p>2015-12-24</p> <p>In this study, we aimed to compare the quantity and quality of publications in health care sciences and services journals from the Chinese mainland, Taiwan, Japan, and India. Journals in this category of the Science Citation Index Expanded were included in the study. Scientific papers were retrieved from the Web of Science online database. Quality was measured according to impact factor, citation of articles, number of articles published in top 10 journals, and the 10 most popular journals by country (area). In the field of health care sciences and services, the annual incremental rates of scientific articles published from 2007 to 2014 were higher than rates of published scientific articles in all fields. Researchers from the Chinese mainland published the most original articles and reviews and had the highest accumulated impact factors, highest total article citations, and highest average citation. Publications from India had the highest average impact factor. In the field of health care sciences and services, China has made remarkable progress during the past eight years in the annual number and percentage of scientific publications. Yet, there is room for improvement in the quantity and quality of such articles.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21143775','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21143775"><span>2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yang, Jack Y; Niemierko, Andrzej; Bajcsy, Ruzena; Xu, Dong; Athey, Brian D; Zhang, Aidong; Ersoy, Okan K; Li, Guo-Zheng; Borodovsky, Mark; Zhang, Joe C; Arabnia, Hamid R; Deng, Youping; Dunker, A Keith; Liu, Yunlong; Ghafoor, Arif</p> <p>2010-12-01</p> <p>Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2999338','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2999338"><span>2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2010-01-01</p> <p>Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine. PMID:21143775</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JPhCS.513c2058L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JPhCS.513c2058L"><span>Implementation of Grid Tier 2 and Tier 3 facilities on a Distributed OpenStack Cloud</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Limosani, Antonio; Boland, Lucien; Coddington, Paul; Crosby, Sean; Huang, Joanna; Sevior, Martin; Wilson, Ross; Zhang, Shunde</p> <p>2014-06-01</p> <p>The Australian Government is making a AUD 100 million investment in Compute and Storage for the academic community. The Compute facilities are provided in the form of 30,000 CPU cores located at 8 nodes around Australia in a distributed virtualized Infrastructure as a Service facility based on OpenStack. The storage will eventually consist of over 100 petabytes located at 6 nodes. All will be linked via a 100 Gb/s network. This proceeding describes the development of a fully connected WLCG Tier-2 grid site as well as a general purpose Tier-3 computing cluster based on this architecture. The facility employs an extension to Torque to enable dynamic allocations of virtual machine instances. A base Scientific Linux virtual machine (VM) image is deployed in the OpenStack cloud and automatically configured as required using Puppet. Custom scripts are used to launch multiple VMs, integrate them into the dynamic Torque cluster and to mount remote file systems. We report on our experience in developing this nation-wide ATLAS and Belle II Tier 2 and Tier 3 computing infrastructure using the national Research Cloud and storage facilities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3933453','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3933453"><span>The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.</p> <p>2013-01-01</p> <p>The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/881640','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/881640"><span>ISCR Annual Report: Fical Year 2004</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>McGraw, J R</p> <p>2005-03-03</p> <p>Large-scale scientific computation and all of the disciplines that support and help to validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of computational simulation as a tool of scientific and engineering research is underscored in the November 2004 statement of the Secretary of Energy that, ''high performance computing is the backbone of the nation's science and technologymore » enterprise''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use efficiently. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to LLNL's core missions than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In Fiscal Year 2004, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for short- and long-term visits with the aim of encouraging long-term academic research agendas that address LLNL's research priorities. Through such collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''feet and hands'' that carry those advances into the Laboratory and incorporates them into practice. ISCR research participants are integrated into LLNL's Computing and Applied Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other five institutes of the URP, it navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20658333','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20658333"><span>Exploiting graphics processing units for computational biology and bioinformatics.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H</p> <p>2010-09-01</p> <p>Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1408072','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1408072"><span>A characterization of workflow management systems for extreme-scale applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia</p> <p></p> <p>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</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1408072-characterization-workflow-management-systems-extreme-scale-applications','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1408072-characterization-workflow-management-systems-extreme-scale-applications"><span>A characterization of workflow management systems for extreme-scale applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...</p> <p>2017-02-16</p> <p>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</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA130978','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA130978"><span>A Numerical Method for Computing the Transonic Fan Duct Flow over a Centerbody into an Exterior Free Stream - Program Tea-343,</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>1974-09-24</p> <p>Transonic Flows with Imbedded Shock Waves", Boeing Scientific Research Laboratories Document D1-82-1053 (1971); also as invited lecture series for AGARD...Past Thin Lifting Airfoils", Boeing Scientific Research Laboratories Document D180-2298-1, June 1971. 5. Krupp, J. A. and Ia-man, 9. M., "Computation...Aerodynamics and Marine Sciences Laboratory, Boeing Scientific Research Laboratories, June 1971. 7. Krupp, J. A., "Documentation for Program TSONIC", Technical</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2010-title42-vol1/pdf/CFR-2010-title42-vol1-sec52h-2.pdf','CFR'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2010-title42-vol1/pdf/CFR-2010-title42-vol1-sec52h-2.pdf"><span>42 CFR 52h.2 - Definitions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2010&page.go=Go">Code of Federal Regulations, 2010 CFR</a></p> <p></p> <p>2010-10-01</p> <p>... areas under review, to give expert advice on the scientific and technical merit of grant applications or... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS SCIENTIFIC PEER REVIEW OF RESEARCH GRANT APPLICATIONS AND RESEARCH AND DEVELOPMENT CONTRACT PROJECTS § 52h.2 Definitions. As used in this...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2011-title42-vol1/pdf/CFR-2011-title42-vol1-sec52h-2.pdf','CFR2011'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2011-title42-vol1/pdf/CFR-2011-title42-vol1-sec52h-2.pdf"><span>42 CFR 52h.2 - Definitions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2011&page.go=Go">Code of Federal Regulations, 2011 CFR</a></p> <p></p> <p>2011-10-01</p> <p>... areas under review, to give expert advice on the scientific and technical merit of grant applications or... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS SCIENTIFIC PEER REVIEW OF RESEARCH GRANT APPLICATIONS AND RESEARCH AND DEVELOPMENT CONTRACT PROJECTS § 52h.2 Definitions. As used in this...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/883740','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/883740"><span>ISCR FY2005 Annual Report</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Keyes, D E; McGraw, J R</p> <p>2006-02-02</p> <p>Large-scale scientific computation and all of the disciplines that support and help validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of simulation as a fundamental tool of scientific and engineering research is underscored in the President's Information Technology Advisory Committee (PITAC) June 2005 finding that ''computational science has become critical to scientific leadership, economic competitiveness, and nationalmore » security''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed, most notably the molecular dynamics simulation that sustained more than 100 Teraflop/s and won the 2005 Gordon Bell Prize. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use in an efficient manner. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to the core missions of LLNL than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In FY 2005, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for both brief and extended visits with the aim of encouraging long-term academic research agendas that address LLNL research priorities. Through these collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''hands and feet'' that carry those advances into the Laboratory and incorporate them into practice. ISCR research participants are integrated into LLNL's Computing Applications and Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other four institutes of the URP, the ISCR navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort. The pages of this annual report summarize the activities of the faculty members, postdoctoral researchers, students, and guests from industry and other laboratories who participated in LLNL's computational mission under the auspices of the ISCR during FY 2005.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016DPS....4832517B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016DPS....4832517B"><span>M4AST - A Tool for Asteroid Modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Birlan, Mirel; Popescu, Marcel; Irimiea, Lucian; Binzel, Richard</p> <p>2016-10-01</p> <p>M4AST (Modelling for asteroids) is an online tool devoted to the analysis and interpretation of reflection spectra of asteroids in the visible and near-infrared spectral intervals. It consists into a spectral database of individual objects and a set of routines for analysis which address scientific aspects such as: taxonomy, curve matching with laboratory spectra, space weathering models, and mineralogical diagnosis. Spectral data were obtained using groundbased facilities; part of these data are precompiled from the literature[1].The database is composed by permanent and temporary files. Each permanent file contains a header and two or three columns (wavelength, spectral reflectance, and the error on spectral reflectance). Temporary files can be uploaded anonymously, and are purged for the property of submitted data. The computing routines are organized in order to accomplish several scientific objectives: visualize spectra, compute the asteroid taxonomic class, compare an asteroid spectrum with similar spectra of meteorites, and computing mineralogical parameters. One facility of using the Virtual Observatory protocols was also developed.A new version of the service was released in June 2016. This new release of M4AST contains a database and facilities to model more than 6,000 spectra of asteroids. A new web-interface was designed. This development allows new functionalities into a user-friendly environment. A bridge system of access and exploiting the database SMASS-MIT (http://smass.mit.edu) allows the treatment and analysis of these data in the framework of M4AST environment.Reference:[1] M. Popescu, M. Birlan, and D.A. Nedelcu, "Modeling of asteroids: M4AST," Astronomy & Astrophysics 544, EDP Sciences, pp. A130, 2012.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=record+AND+scientific&pg=6&id=EJ266263','ERIC'); return false;" href="https://eric.ed.gov/?q=record+AND+scientific&pg=6&id=EJ266263"><span>Environmentalists and the Computer.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Baron, Robert C.</p> <p>1982-01-01</p> <p>Review characteristics, applications, and limitations of computers, including word processing, data/record keeping, scientific and industrial, and educational applications. Discusses misuse of computers and role of computers in environmental management. (JN)</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16203701','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16203701"><span>Thomson Scientific's expanding Web of Knowledge: beyond citation databases and current awareness services.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>London, Sue; Brahmi, Frances A</p> <p>2005-01-01</p> <p>As end-user demand for easy access to electronic full text continues to climb, an increasing number of information providers are combining that access with their other products and services, making navigating their Web sites by librarians seeking information on a given product or service more daunting than ever. One such provider of a complex array of products and services is Thomson Scientific. This paper looks at some of the many products and tools available from two of Thomson Scientific's businesses, Thomson ISI and Thomson ResearchSoft. Among the items of most interest to health sciences and veterinary librarians and their users are the variety of databases available via the ISI Web of Knowledge platform and the information management products available from ResearchSoft.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16113776','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16113776"><span>The challenge of ubiquitous computing in health care: technology, concepts and solutions. Findings from the IMIA Yearbook of Medical Informatics 2005.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bott, O J; Ammenwerth, E; Brigl, B; Knaup, P; Lang, E; Pilgram, R; Pfeifer, B; Ruderich, F; Wolff, A C; Haux, R; Kulikowski, C</p> <p>2005-01-01</p> <p>To review recent research efforts in the field of ubiquitous computing in health care. To identify current research trends and further challenges for medical informatics. Analysis of the contents of the Yearbook on Medical Informatics 2005 of the International Medical Informatics Association (IMIA). The Yearbook of Medical Informatics 2005 includes 34 original papers selected from 22 peer-reviewed scientific journals related to several distinct research areas: health and clinical management, patient records, health information systems, medical signal processing and biomedical imaging, decision support, knowledge representation and management, education and consumer informatics as well as bioinformatics. A special section on ubiquitous health care systems is devoted to recent developments in the application of ubiquitous computing in health care. Besides additional synoptical reviews of each of the sections the Yearbook includes invited reviews concerning E-Health strategies, primary care informatics and wearable healthcare. Several publications demonstrate the potential of ubiquitous computing to enhance effectiveness of health services delivery and organization. But ubiquitous computing is also a societal challenge, caused by the surrounding but unobtrusive character of this technology. Contributions from nearly all of the established sub-disciplines of medical informatics are demanded to turn the visions of this promising new research field into reality.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN41A1386E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN41A1386E"><span>A Cloud-Based Infrastructure for Near-Real-Time Processing and Dissemination of NPP Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Evans, J. D.; Valente, E. G.; Chettri, S. S.</p> <p>2011-12-01</p> <p>We are building a scalable cloud-based infrastructure for generating and disseminating near-real-time data products from a variety of geospatial and meteorological data sources, including the new National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP). Our approach relies on linking Direct Broadcast and other data streams to a suite of scientific algorithms coordinated by NASA's International Polar-Orbiter Processing Package (IPOPP). The resulting data products are directly accessible to a wide variety of end-user applications, via industry-standard protocols such as OGC Web Services, Unidata Local Data Manager, or OPeNDAP, using open source software components. The processing chain employs on-demand computing resources from Amazon.com's Elastic Compute Cloud and NASA's Nebula cloud services. Our current prototype targets short-term weather forecasting, in collaboration with NASA's Short-term Prediction Research and Transition (SPoRT) program and the National Weather Service. Direct Broadcast is especially crucial for NPP, whose current ground segment is unlikely to deliver data quickly enough for short-term weather forecasters and other near-real-time users. Direct Broadcast also allows full local control over data handling, from the receiving antenna to end-user applications: this provides opportunities to streamline processes for data ingest, processing, and dissemination, and thus to make interpreted data products (Environmental Data Records) available to practitioners within minutes of data capture at the sensor. Cloud computing lets us grow and shrink computing resources to meet large and rapid fluctuations in data availability (twice daily for polar orbiters) - and similarly large fluctuations in demand from our target (near-real-time) users. This offers a compelling business case for cloud computing: the processing or dissemination systems can grow arbitrarily large to sustain near-real time data access despite surges in data volumes or user demand, but that computing capacity (and hourly costs) can be dropped almost instantly once the surge passes. Cloud computing also allows low-risk experimentation with a variety of machine architectures (processor types; bandwidth, memory, and storage capacities, etc.) and of system configurations (including massively parallel computing patterns). Finally, our service-based approach (in which user applications invoke software processes on a Web-accessible server) facilitates access into datasets of arbitrary size and resolution, and allows users to request and receive tailored products on demand. To maximize the usefulness and impact of our technology, we have emphasized open, industry-standard software interfaces. We are also using and developing open source software to facilitate the widespread adoption of similar, derived, or interoperable systems for processing and serving near-real-time data from NPP and other sources.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.osti.gov/sciencecinema/biblio/1026265','SCIGOVIMAGE-SCICINEMA'); return false;" href="http://www.osti.gov/sciencecinema/biblio/1026265"><span>Massive Data, the Digitization of Science, and Reproducibility of Results</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/sciencecinema/">ScienceCinema</a></p> <p>Stodden, Victoria</p> <p>2018-04-27</p> <p>As the scientific enterprise becomes increasingly computational and data-driven, the nature of the information communicated must change. Without inclusion of the code and data with published computational results, we are engendering a credibility crisis in science. Controversies such as ClimateGate, the microarray-based drug sensitivity clinical trials under investigation at Duke University, and retractions from prominent journals due to unverified code suggest the need for greater transparency in our computational science. In this talk I argue that the scientific method be restored to (1) a focus on error control as central to scientific communication and (2) complete communication of the underlying methodology producing the results, ie. reproducibility. I outline barriers to these goals based on recent survey work (Stodden 2010), and suggest solutions such as the “Reproducible Research Standard” (Stodden 2009), giving open licensing options designed to create an intellectual property framework for scientists consonant with longstanding scientific norms.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19247811','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19247811"><span>Programmers, professors, and parasites: credit and co-authorship in computer science.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Solomon, Justin</p> <p>2009-12-01</p> <p>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.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2011-title48-vol4/pdf/CFR-2011-title48-vol4-sec435-010.pdf','CFR2011'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2011-title48-vol4/pdf/CFR-2011-title48-vol4-sec435-010.pdf"><span>48 CFR 435.010 - Scientific and technical reports.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2011&page.go=Go">Code of Federal Regulations, 2011 CFR</a></p> <p></p> <p>2011-10-01</p> <p>... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Scientific and technical...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/945748','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/945748"><span>In Defense of the National Labs and Big-Budget Science</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Goodwin, J R</p> <p>2008-07-29</p> <p>The purpose of this paper is to present the unofficial and unsanctioned opinions of a Visiting Scientist at Lawrence Livermore National Laboratory on the values of LLNL and the other National Labs. The basic founding value and goal of the National Labs is big-budget scientific research, along with smaller-budget scientific research that cannot easily be done elsewhere. The most important example in the latter category is classified defense-related research. The historical guiding light here is the Manhattan Project. This endeavor was unique in human history, and might remain so. The scientific expertise and wealth of an entire nation was tappedmore » in a project that was huge beyond reckoning, with no advance guarantee of success. It was in many respects a clash of scientific titans, with a large supporting cast, collaborating toward a single well-defined goal. Never had scientists received so much respect, so much money, and so much intellectual freedom to pursue scientific progress. And never was the gap between theory and implementation so rapidly narrowed, with results that changed the world, completely. Enormous resources are spent at the national or international level on large-scale scientific projects. LLNL has the most powerful computer in the world, Blue Gene/L. (Oops, Los Alamos just seized the title with Roadrunner; such titles regularly change hands.) LLNL also has the largest laser in the world, the National Ignition Facility (NIF). Lawrence Berkeley National Lab (LBNL) has the most powerful microscope in the world. Not only is it beyond the resources of most large corporations to make such expenditures, but the risk exceeds the possible rewards for those corporations that could. Nor can most small countries afford to finance large scientific projects, and not even the richest can afford largess, especially if Congress is under major budget pressure. Some big-budget research efforts are funded by international consortiums, such as the Large Hadron Collider (LHC) at CERN, and the International Tokamak Experimental Reactor (ITER) in Cadarache, France, a magnetic-confinement fusion research project. The postWWII histories of particle and fusion physics contain remarkable examples of both international competition, with an emphasis on secrecy, and international cooperation, with an emphasis on shared knowledge and resources. Initiatives to share sometimes came from surprising directions. Most large-scale scientific projects have potential defense applications. NIF certainly does; it is primarily designed to create small-scale fusion explosions. Blue Gene/L operates in part in service to NIF, and in part to various defense projects. The most important defense projects include stewardship of the national nuclear weapons stockpile, and the proposed redesign and replacement of those weapons with fewer, safer, more reliable, longer-lived, and less apocalyptic warheads. Many well-meaning people will consider the optimal lifetime of a nuclear weapon to be zero, but most thoughtful people, when asked how much longer they think this nation will require them, will ask for some time to think. NIF is also designed to create exothermic small-scale fusion explosions. The malapropos 'exothermic' here is a convenience to cover a profusion of complexities, but the basic idea is that the explosions will create more recoverable energy than was used to create them. One can hope that the primary future benefits of success for NIF will be in cost-effective generation of electrical power through controlled small-scale fusion reactions, rather than in improved large-scale fusion explosions. Blue Gene/L also services climate research, genomic research, materials research, and a myriad of other computational problems that become more feasible, reliable, and precise the larger the number of computational nodes employed. Blue Gene/L has to be sited within a security complex for obvious reasons, but its value extends to the nation and the world. There is a duality here between large-scale scientific research machines and the supercomputers used to model them. An astounding example is illustrated in a graph released by EFDAJET, at Oxfordshire, UK, presently the largest operating magnetic-confinement fusion experiment. The graph shows plasma confinement times (an essential performance parameter) for all the major tokamaks in the international fusion program, over their existing lifetimes. The remarkable thing about the data is not so much confinement-time versus date or scale, but the fact that the data are given for both the computer model predictions and the actual experimental measurements, and the two are in phenomenal agreement over the extended range of scales. Supercomputer models, sometimes operating with the intricacy of Schroedinger's equation at quantum physical scales, have become a costly but enormously cost-saving tool.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN31D1793B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN31D1793B"><span>Enabling Data-as- a-Service (DaaS) - Biggest Challenge of Geoscience Australia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bastrakova, I.; Kemp, C.; Car, N. J.</p> <p>2016-12-01</p> <p>Geoscience Australia (GA) is recognised and respected as the national repository and steward of multiple national significance data collections that provides geoscience information, services and capability to the Australian Government, industry and stakeholders. Provision of Data-as-a-Service is both GA's key responsibility and core business. Through the Science First Transformation Program GA is undergoing a significant rethinking of its data architecture, curation and access to support the Digital Science capability for which DaaS forms both a dependency and underpins its implementation. DaaS, being a service, means we can deliver its outputs in multiple ways thus providing users with data on demand in ready-for-consumption forms. We can then to reuse prebuilt data constructions to allow self-serviced integration of data underpinned by dynamic query tools. In GA's context examples of DaaS are the Australian Geoscience Data Cube, the Foundation Spatial Data Framework and data served through several Virtual Laboratories. We have implemented a three-layered architecture for DaaS in order to store and manage the data while honouring the semantics of Scientific Data Models defined by subject matter experts and GA's Enterprise Data Architecture as well as retain that delivery flexibility. The foundation layer of DaaS is Canonical Datasets, which are optimised for a long-term data stewardship and curation. Data is well structured, standardised, described and audited. All data creation and editing happen within this layer. The middle Data Transformation layer assists with transformation of data from Canonical Datasets to data integration layer. It provides mechanisms for multi-format and multi-technology data transformation. The top Data Integration layer is optimised for data access. Data can be easily reused and repurposed; data formats made available are optimised for scientific computing and adjusted for access by multiple applications, tools and libraries. Moving to DaaS enables GA to increase data alertness, generate new capabilities and be prepared for emerging technological challengers.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JPhCS.396d2027H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JPhCS.396d2027H"><span>Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hendrix, Val; Benjamin, Doug; Yao, Yushu</p> <p>2012-12-01</p> <p>Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment in a cloud environment. Our future cloud efforts will further build on this work.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA557625','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA557625"><span>Models of Dynamic Relations Among Service Activities, System State and Service Quality on Computer and Network Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2010-01-01</p> <p>Service quality on computer and network systems has become increasingly important as many conventional service transactions are moved online. Service quality of computer and network services can be measured by the performance of the service process in throughput, delay, and so on. On a computer and network system, competing service requests of users and associated service activities change the state of limited system resources which in turn affects the achieved service ...relations of service activities, system state and service</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol2/pdf/CFR-2010-title30-vol2-sec280-21.pdf','CFR'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol2/pdf/CFR-2010-title30-vol2-sec280-21.pdf"><span>30 CFR 280.21 - What must I do in conducting G&G prospecting or scientific research?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2010&page.go=Go">Code of Federal Regulations, 2010 CFR</a></p> <p></p> <p>2010-07-01</p> <p>... scientific research? 280.21 Section 280.21 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE... prospecting or scientific research? While conducting G&G prospecting or scientific research activities under a... you are prospecting or conducting scientific research activities. (b) Consult and coordinate your G&G...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=water+AND+quality&pg=2&id=EJ1060250','ERIC'); return false;" href="https://eric.ed.gov/?q=water+AND+quality&pg=2&id=EJ1060250"><span>Scaffolding Argumentation about Water Quality: A Mixed-Method Study in a Rural Middle School</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Belland, Brian R.; Gu, Jiangyue; Armbrust, Sara; Cook, Brant</p> <p>2015-01-01</p> <p>A common way for students to develop scientific argumentation abilities is through argumentation about socioscientific issues, defined as scientific problems with social, ethical, and moral aspects. Computer-based scaffolding can support students in this process. In this mixed method study, we examined the use and impact of computer based…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2012-title48-vol7/pdf/CFR-2012-title48-vol7-sec9904-410-60.pdf','CFR2012'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2012-title48-vol7/pdf/CFR-2012-title48-vol7-sec9904-410-60.pdf"><span>48 CFR 9904.410-60 - Illustrations.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2012&page.go=Go">Code of Federal Regulations, 2012 CFR</a></p> <p></p> <p>2012-10-01</p> <p>... budgets for the other segment should be removed from B's G&A expense pool and transferred to the other...; all home office expenses allocated to Segment H are included in Segment H's G&A expense pool. (2) This... cost of scientific computer operations in its G&A expense pool. The scientific computer is used...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2014-title48-vol7/pdf/CFR-2014-title48-vol7-sec9904-410-60.pdf','CFR2014'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2014-title48-vol7/pdf/CFR-2014-title48-vol7-sec9904-410-60.pdf"><span>48 CFR 9904.410-60 - Illustrations.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2014&page.go=Go">Code of Federal Regulations, 2014 CFR</a></p> <p></p> <p>2014-10-01</p> <p>... budgets for the other segment should be removed from B's G&A expense pool and transferred to the other...; all home office expenses allocated to Segment H are included in Segment H's G&A expense pool. (2) This... cost of scientific computer operations in its G&A expense pool. The scientific computer is used...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA502694','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA502694"><span>America COMPETES Act and the FY2010 Budget</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2009-06-29</p> <p>Outstanding Junior Investigator, Fusion Energy Sciences Plasma Physics Junior Faculty Development; Advanced Scientific Computing Research Early Career...the Fusion Energy Sciences Graduate Fellowships.2 If members of Congress agree with this contention, these America COMPETES Act programs were...Physics Outstanding Junior Investigator, Fusion Energy Sciences Plasma Physics Junior Faculty Development; Advanced Scientific Computing Research Early</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1049042','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1049042"><span>Argonne Leadership Computing Facility 2011 annual report : Shaping future supercomputing.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Papka, M.; Messina, P.; Coffey, R.</p> <p></p> <p>The ALCF's Early Science Program aims to prepare key applications for the architecture and scale of Mira and to solidify libraries and infrastructure that will pave the way for other future production applications. Two billion core-hours have been allocated to 16 Early Science projects on Mira. The projects, in addition to promising delivery of exciting new science, are all based on state-of-the-art, petascale, parallel applications. The project teams, in collaboration with ALCF staff and IBM, have undertaken intensive efforts to adapt their software to take advantage of Mira's Blue Gene/Q architecture, which, in a number of ways, is a precursormore » to future high-performance-computing architecture. The Argonne Leadership Computing Facility (ALCF) enables transformative science that solves some of the most difficult challenges in biology, chemistry, energy, climate, materials, physics, and other scientific realms. Users partnering with ALCF staff have reached research milestones previously unattainable, due to the ALCF's world-class supercomputing resources and expertise in computation science. In 2011, the ALCF's commitment to providing outstanding science and leadership-class resources was honored with several prestigious awards. Research on multiscale brain blood flow simulations was named a Gordon Bell Prize finalist. Intrepid, the ALCF's BG/P system, ranked No. 1 on the Graph 500 list for the second consecutive year. The next-generation BG/Q prototype again topped the Green500 list. Skilled experts at the ALCF enable researchers to conduct breakthrough science on the Blue Gene system in key ways. The Catalyst Team matches project PIs with experienced computational scientists to maximize and accelerate research in their specific scientific domains. The Performance Engineering Team facilitates the effective use of applications on the Blue Gene system by assessing and improving the algorithms used by applications and the techniques used to implement those algorithms. The Data Analytics and Visualization Team lends expertise in tools and methods for high-performance, post-processing of large datasets, interactive data exploration, batch visualization, and production visualization. The Operations Team ensures that system hardware and software work reliably and optimally; system tools are matched to the unique system architectures and scale of ALCF resources; the entire system software stack works smoothly together; and I/O performance issues, bug fixes, and requests for system software are addressed. The User Services and Outreach Team offers frontline services and support to existing and potential ALCF users. The team also provides marketing and outreach to users, DOE, and the broader community.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN13C1679C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN13C1679C"><span>Big Data Processing for a Central Texas Groundwater Case Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cantu, A.; Rivera, O.; Martínez, A.; Lewis, D. H.; Gentle, J. N., Jr.; Fuentes, G.; Pierce, S. A.</p> <p>2016-12-01</p> <p>As computational methods improve, scientists are able to expand the level and scale of experimental simulation and testing that is completed for case studies. This study presents a comparative analysis of multiple models for the Barton Springs segment of the Edwards aquifer. Several numerical simulations using state-mandated MODFLOW models ran on Stampede, a High Performance Computing system housed at the Texas Advanced Computing Center, were performed for multiple scenario testing. One goal of this multidisciplinary project aims to visualize and compare the output data of the groundwater model using the statistical programming language R to find revealing data patterns produced by different pumping scenarios. Presenting data in a friendly post-processing format is covered in this paper. Visualization of the data and creating workflows applicable to the management of the data are tasks performed after data extraction. Resulting analyses provide an example of how supercomputing can be used to accelerate evaluation of scientific uncertainty and geological knowledge in relation to policy and management decisions. Understanding the aquifer behavior helps policy makers avoid negative impact on the endangered species, environmental services and aids in maximizing the aquifer yield.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1361292-exascale-computing-big-data','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1361292-exascale-computing-big-data"><span>Exascale computing and big data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Reed, Daniel A.; Dongarra, Jack</p> <p>2015-06-25</p> <p>Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1361292','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1361292"><span>Exascale computing and big data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Reed, Daniel A.; Dongarra, Jack</p> <p></p> <p>Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2011-05-13/pdf/2011-11707.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2011-05-13/pdf/2011-11707.pdf"><span>76 FR 27952 - Small Business Size Standards: Professional, Scientific and Technical Services.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2011-05-13</p> <p>... Administration (SBA or Agency) proposed to increase small business size standards for 35 industries and one sub... SMALL BUSINESS ADMINISTRATION 13 CFR Part 121 RIN 3245-AG07 Small Business Size Standards: Professional, Scientific and Technical Services. AGENCY: U.S. Small Business Administration. ACTION: Proposed...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2010-03-09/pdf/2010-4976.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2010-03-09/pdf/2010-4976.pdf"><span>75 FR 10809 - Outer Continental Shelf (OCS) Scientific Committee-Notice of Renewal</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2010-03-09</p> <p>... AGENCY: Minerals Management Service (MMS), Interior. ACTION: Notice of renewal of the Outer Continental... Minerals Management Service. The Committee reviews the relevance of the research and data being produced to meet MMS scientific information needs for decisionmaking and may recommend changes in scope, direction...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JPhCS..16.....M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JPhCS..16.....M"><span>Preface: SciDAC 2005</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mezzacappa, Anthony</p> <p>2005-01-01</p> <p>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.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1076794','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1076794"><span>The Magellan Final Report on Cloud Computing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>,; Coghlan, Susan; Yelick, Katherine</p> <p></p> <p>The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computingmore » Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/EJ1128266.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/EJ1128266.pdf"><span>Evolution and Natural Selection: Learning by Playing and Reflecting</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Herrero, David; del Castillo, Héctor; Monjelat, Natalia; García-Varela, Ana Belén; Checa, Mirian; Gómez, Patricia</p> <p>2014-01-01</p> <p>Scientific literacy is more than the simple reproduction of traditional school science knowledge and requires a set of skills, among them identifying scientific issues, explaining phenomena scientifically and using scientific evidence. Several studies have indicated that playing computer games in the classroom can support the development of…</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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