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A data sharing infrastructure could effectively enable such partnership

Data Overlaps. Shared Data. Monitoring. Satellite. Modeling. EPA, NASA, NOAA Partnership through Data Sharing. R. Scheffe, EPA:. Integration of AQ information in EPA, NASA and NOAA through partnerships.

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A data sharing infrastructure could effectively enable such partnership

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  1. Data Overlaps Shared Data Monitoring Satellite Modeling EPA, NASA, NOAA Partnership through Data Sharing R. Scheffe, EPA: Integration of AQ information in EPA, NASA and NOAA through partnerships A data sharing infrastructure could effectively enable such partnership F. Lindsey, NASA: Shared data resources could form the next generation of capabilities for AQ research and decision support Are the stars aligned? Please join us and bring your ideas to the discussion at the AQ cluster session: Thursday, 10-12 am.

  2. GEOSS PM research NAS, CAAAC CASAC, OMB NOAA EPA PHASE Eco-informatics NASA CDC Programs Risk/exposure assessments Organizations Private Sector AQ forecasting NPS States/Tribes RPO’s/Interstate NAAQS setting Accountability/ indicators USDA SIPs, nat.rules designations NARSTO DOE Enviros Academia NADP Satellite data IMPROVE, NCore PM monit, PAMS Intensive studies PM centers Data sources Supersites CASTNET Health/mort. records Other networks: SEARCH, IADN.. Lidar systems CMAQ GEOS-CHEM Emissions Meteorology Entities participating in AQ information exchannge Unfortunately, the inner working of the IS that links these entities is not yet understood. The challenge posed by R. Scheffe: Please explain this Informatics Mess

  3. Uniform Access Data Processing Web Service Chain ProductsReports Users Provider SciFlo Public EPA SurfObs Forecast NASA DAACs DataFed EPA Model Compli. Manager Science Scientist Custom Processing User Agencies others Other other Agile Information System: Data Access, Processing and Products Control Data Control Seeking Information User Programs Negotiating & Market Space Data NAAQS SIPs Forecast GEOSS … Providing Information

  4. Generic Decision Support for Air Quality Decisions Reports:Model Forecasts, Obs. Evidence Models Knowledge into the Minds of Technical Analysts Knowledge into the Minds of Decision- making managers Decisions Knowledge into the Minds ofRegulatory Analysts Observations Decision Support System Global Earth Observing System of Systems GEOSS Architecture Framework

  5. GEOSS-Like Air Quality System of Systems? Characteristics of System of Systems (SoS) (Based on DoD Descriptions) • Autonomous constituents managed/operated independently • Independent evolution of each constituent • Displays emergent behavior Must recognize, manage, exploit the characteristics: • No stakeholder has complete SoS insight • Central control is limited; distributed control is essential • Users, must be involved throughout the life of a SoS

  6. App App App App WCS/WMS Some major AQ Information System Challenges(Same as the DoD, ES Challenges?) What few things must be the same so that everything else can be different? (GEOSS) Connecting Humans! Are WCS/WMS Convergence Protocols? Right Level of Networking?

  7. NPS Protect ecosystems, AQ WQ USDA Protect/optimize Ag and forest resources CDC To promote health and quality of life …. R. Scheffe: Apparent divergences? Organizations have different missions NASA Explore fundamental Earth System Properties EPA (Protect human health & envi. Improve air, water, ecosystem NOAA To understand and predict changes in the Earth’s environment and …

  8. Collaboration (culture) empire building? Observation technologies {e.g., satellites} Computational power Science, talent {embodied in AQ models and young geniuses} Accountability,↓ regulatory assessments {e.g., NAS, CASAC} Information technologies {e.g., data sharing protocols} Alignment Budgets, agency collaboration resource/program accountability R. Scheffe: Stars aligned?

  9. Applications Private Shared AQ Policy NOAA NASA EPA Other FedS Air Quality Consortium Data, Tools, Methods Priv Regulation DoI Research F. Lindsey, NASA:Air Quality Collaborative Consortium Goal: Cross-leverage the shared partner resources and activities, while Maintaining partner’s autonomy in capabilities and activities Approach: Exchange the resources at the web ‘interfaces’, like portals. Infuse cutting-edge technologies and resources into Agencies as needed. Use ESIP portal as the linker and the Air Quality cluster as the mediator. Outcome: Sharing and integration could form next-generation capabilities. Savings by re-use and better information by broader perspectives Better air quality through more informed management

  10. Summary • There IS an ‘alignment of stars’ for integrating AQ data systems • Third-party mediation can homogenize the distributed data • Agile SOA-based IS can deliver info products to diverse users • Since 2005, one such IS, DataFed is used by EPA and in research • Many more data and technologies are available from the community

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