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US-EU Research Cooperation Interagency/International Cooperation on Ecoinformatics

US-EU Research Cooperation Interagency/International Cooperation on Ecoinformatics. Interagency/International Cooperation on Ecoinformatics Brussels, Belgium. September 2004. Bruce Bargmeyer +1 (510) 495-2905 bebargmeyer@lbl.gov. Ecoinformatics.

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US-EU Research Cooperation Interagency/International Cooperation on Ecoinformatics

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  1. US-EU Research CooperationInteragency/International Cooperation on Ecoinformatics Interagency/International Cooperation on Ecoinformatics Brussels, Belgium September 2004 Bruce Bargmeyer +1 (510) 495-2905 bebargmeyer@lbl.gov

  2. Ecoinformatics Information science and information technology for the environment • Sound information as the basis for environmental policy, decisions, and action • Information technology that supports and enables development of sound information • Facilitate interaction with the information • Human – Computer • Computer - Computer

  3. Ecoinformatics • What are the key elements needed for an ecoinformatics marketplace? • What actions should this Interagency/ International Cooperation on Ecoinformatics take? • How can the I/ICE contribute to and draw on R&D programs of NSF, & EU DGs?

  4. Past, Present, … Future? EEA DOE text text data data text data ambiente agricultura tiempo salud hunano industria turismo tierra agua aero environ agriculture climate human health industry tourism soil water air environ agriculture climate human health industry tourism soil water air DoD 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 text data environ agriculture climate human health industry tourism soil water air EPA 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 text data 3268 0825 1348 5038 2708 0000 2178 123 345 445 670 248 591 308 ambiente agricultura tiempo salud huno industria turismo tierra agua aero 123 345 445 670 248 591 308 3268 0825 1348 5038 Others . . . Users Lots of users Lots of information systems Lots of Data Sources

  5. Actions • Much is already being done on environmental & health information • Billions are being spent on data, systems, analysis • Millions are being spent on information technology • Millions are being spent on standards • Millions being spent on semantics development and data harmonization • We can have great influence in bringing coherence to these expenditures/efforts with a tiny fraction of these funds.

  6. Data Standards • Avoid a combinatorial explosion of data content, description, and metadata arrangements for information access and exchange. Data standards and metadata registries can help.

  7. Then there is one point of access to our environmental data resources: Separate Environmental Media Legislation Separate Regs/ Procedures Regulated Facility Complete Warehouse Repository Separate Data Repositories State Regs Fed Air Reg Fed Water Reg Fed RCRA Reg Fed TSCA Reg “ “ State Laws CAA CWA RCRA TSCA “ “ Public/ Environmental Regulators/ Environmental Community Regulated Facility June 1996

  8. Data and Semantics Management DBMS/XML/ Documents Dictionary DataElements Keyword Thesaurus Semantic Web Terms Ontology Concepts 11179 Metadata Registry

  9. Possible Actions • Identify and develop ecoinformatics key elements • Lead semantics development efforts and provide semantic services • Lead standards efforts • E.g., for Reportnet, the Exchange Network, GBIF • Lead adaptation/adoption of emerging technology • Environmental semantic grid • Environmental data grid • Environmental computational grid • Hardware cycles • Software/models

  10. Users World Wide Web Companies Data Services Metadata Registries Universities Environmental Data Grid Semantic Services TerminologyThesaurus Ontology Taxonomy Computation Services Agencies Data Standards Structured Metadata Others Environmental Semantics Grid Software: Models, Visualization, Analysis Agent systems Semantic Based Computing Environmental Computer Grid High Performance, cluster, Personal September 2004

  11. Users World Wide Web Companies Data Services Metadata Registries Universities Environmental Data Grid Semantic Services TerminologyThesaurus Ontology Taxonomy Computation Services Agencies Data Standards Structured Metadata Others Environmental Semantics Grid Software: Models, Visualization, Analysis Agent systems Semantic Based Computing Environmental Computer Grid High Performance, cluster, Personal September 2004

  12. A Possible Collaborative Project • Initiate an interconnected EU-US: • Environmental Data Grid • Environmental Computation Grid • Environmental Semantics Grid • Organize key infrastructure components for demonstration • E.g., EDR, EPA supercomputer, models • DOE/LBNL supercomputer (under DOE-EPA MOU) • XMDR Semantics Server • Interagency semantic and data resources e.g., GBIF • Hold competition for innovative use of the Grids. • Organize conference(s) • Funding: $50m over three years • Seed money for organizing $300k each in US in EU • Possible funding for workshop

  13. US – EU Collaboration • US • NSF • EPA and I/ICE partners • EU • DG Environment, DG Research, DG Information Society • EEA • R&D Lead and Project Central • US – LBNL • EU – JRC • Private firms

  14. Application Areas • Biodiversity • Climate • Genomics • computational toxicology • Spatial data – GEO/GEOS & GMES • Ecological Modeling • Security, ecological risk management • Invasive species-industrial costs

  15. Related Efforts • Semantic Environment for Ecological Knowledge (SEEK) • Knowledge Network for Biocomplexity (KNB) • DataGrid Project (FP5) • Environmental Cyber Infrastructure • DOE Science Grid • Cancer Biomedical Informatics Grid (caBIG)

  16. Example Tasks • Production Grid Services • Develop the components necessary to use Grids in production. Define Grid-capable Web services standards, develop concrete implementations of Grid services, participate in interoperability testing between different Grid service implementations, and implement production Grids (see: DOE Production Science Grid). • Grid Services Architecture • Develop an architecture which supports dynamic, programmatic access to local and remote data sources and metadata repositories without sacrificing the high-performance requirement. E.g., address this problem through a peer-to-peer service infrastructure which supports queries across autonomous data repositories, including dynamic and heterogeneous information sources. • Security/Authentication/Access Control • Develop secure grid technologies e.g., authorization services for heterogeneous, widely distributed resources that require a combination of local and centralized access control. Apply these principles of policy-based access control both to group query protocols and to individual peer-to-peer data sharing responses.

  17. Example Tasks (Cont) • Grid Workflow • Many scientific projects have developed workflows which are regularly used in their research. Develop a graphical user interface for composition and monitoring of Grid-based workflows. E.g., enable scientists to design workflow networks by “dragging and dropping” existing Grid service components and monitoring the resulting workflow execution visually. Enable end users to submit complex queries through a friendly Web interface, while also allowing the production Grid managers to execute and monitor regularly scheduled complex, compute- and data-intensive production workflows. • Collaboration Technologies • Distributed scientific collaborations need tools to support development of topical communities of researchers working together regardless of actual physical location. E.g, Pervasive Collaborative Computing Environment (PCCE). • Semantic Grids • A Semantic Grid adapts the Semantic Web and metadata registries to the service-oriented architecture being used to develop next-generation Grid services.

  18. Some Precedents • Cancer Bioinformatics Grid (caBIG) – expected funding $20m each year for three years • Includes the caDSR (a ISO/IEC 11179 metadata registry like the EDR) • DOE Competition for Supercomputer time

  19. Organizational Meeting • Berkeley, California • January 18 & 19, 2005 (Tue & Wed) • Host: LBNL • Location UC Berkeley Campus • Attendance: 25 or less

  20. Workshop: Statement of Purpose E.g., • Environmental science involves many collaborators at multiple institutions. The leading edge of science depends critically on an infrastructure that supports widely distributed computing, data, and instrument resources. An Environmental Science Grid is being developed and deployed across the Environmental organizations, providing infrastructure services for advanced scientific applications and problem solving frameworks. By reducing barriers to the use of remote resources, it is deploying the cyber infrastructure required for the next generation of science. • The goal of the Environmental Science Grid project is to provide this advanced cyber infrastructure as persistent, scalable, community standards based, Grid services to support environmental science projects. Grid services provide security, resource discovery, resource access, monitoring, data access, tools for advanced scientific applications and problem solving frameworks. These services reduce barriers to the use of remote resources and facilitate large-scale collaboration.

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