1 / 28

EPA Data Architecture for DRM 2.0

EPA Data Architecture for DRM 2.0. Brand Niemann Enterprise Architecture Team, US EPA, and Co-Chair, SICoP August 7, 2006. Request. 1. Data Models by EPA Business Line using DRM 2.0 Structure:

madridl
Download Presentation

EPA Data Architecture for DRM 2.0

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. EPA Data Architecturefor DRM 2.0 Brand Niemann Enterprise Architecture Team, US EPA, and Co-Chair, SICoP August 7, 2006

  2. Request • 1. Data Models by EPA Business Line using DRM 2.0 Structure: • Example: Made the Draft 2007 EPA Report on Indicators DRM 2.0 Compliant and integrated it with other indicator reports using an overall data model (actually ontology) for indicators being developed in cooperation with the NAS Key National Indicator Initiative and others (CEQ, etc.). • 2. Data collection, sources, and validation: • Example: Relied on OIAA's work on Indicators from 2003 to the present for metadata and broadened that to include many others high-quality sources of indicator data that have metadata since EPA originates very little indicator data itself. • Note: These new Data Models are available as DRM 2.0 Templates at the top of the online data assets (XML) and/or as formal ontologies (OWL). See slides 3-5.

  3. DRM 2.0 Templates

  4. Ontology for Indicators Schematic of the Ontology Indicators Topics Organizations Jurisdictions Publicly led U.S. local/regional level The Economy Privately led U.S. state level Society Culture Led by public-private partnership National level outside the United States The Environment Supranational level Cross-Cutting Note that each of these classes can and do have multiple instances underneath them, etc.

  5. Semantic Wiki Ontologies E.g. Data Model Classes of interest to Kevin Brett, SRA

  6. Explanation • The "data model" for DRM 2.0 has three parts (description, context, and sharing) and its best practice implementation (which I led for OMB/AIC and now oversee in SICoP/SWIM WG under the Best Practices Committee*) is fundamentally different from what EPA has been doing in the past in that: • the three types of data (structured, unstructured, and semi-structured) are integrated together, along with their metadata; • the data assets and taxonomies/ontologies are made visible and operational; and • the data is actually made available as either exchange packages or query points or both. • Note: See Slides 8-12. * http://colab.cim3.net/cgi-bin/wiki.pl?SICoP/SemanticWikisandInformationManagementWG

  7. Explanation • We have many examples of this to show from the past year and are been doing this in the Summer Collaborative Expedition Workshops using new Semantic Wiki Technology for: • Geospatial Data (June 20-22nd); • Information Sharing and Knowledge Management (July 18th); and • Multiple Ontologies in Semantic Data Networks (August 15th). • I would strongly encourage attendance at the August 15th Workshop to more fully understand this new approach than is going to be possible in just two hours. • See http://colab.cim3.net/cgi-bin/wiki.pl?ExpeditionWorkshop/OpenCollaboration_NetworkingSemanticInteroperability_2006_08_15

  8. Data Reference Model 2.0 • One of SICoPs Projects Was the DRM: • December 2004, DRM 1.0 – Just structured data (Description) and exchange packages (Sharing). • February 2005, SICoP White Paper 1 (“Data Architecture of the Future”) – All three types of data (Description) and ontologies (Context). • October 2005, SICoP DRM 2.0 Implementation Guide – Metamodel and Semantic Metadata (see slides 9 - 10). • December 2005, DRM 2.0 – Description (3), Context (2), and Sharing (2) (see slide 11). • So DRM 2.0 + Semantic Metadata = SICoP Knowledge Reference Model (KRM). • DRM 2.0 Implementation Evolves to the SICoP Semantic Wikis and Information Management (SWIM) WG

  9. Data Reference Model 2.0 Relationships and associations • Metamodel: Precise definitions of constructs and rules needed for abstraction, generalization, and semantic models. • Model: Relationships between the data and its metadata. • Metadata: Data about the data. • Data: Facts or figures from which conclusions can be inferred. Source: Professor Andreas Tolk, August 16, 2005 The purpose of this schematic is to show that we need to describe information model relationships and associations in a way that can be accessed and searched.

  10. Data Reference Model 2.0 The point of this graph is that Increasing Metadata (from glossaries to ontologies) is highly correlated with Increasing Search Capability (from discovery to reasoning).

  11. Data Reference Model 2.0 DRM 1.0 SICoP All Three Ontologies Source: Expanding E-Government, Improved Service Delivery for the American People Using Information Technology, December 2005, pp. 2-3. http://www.whitehouse.gov/omb/budintegration/expanding_egov_2005.pdf

  12. Data Reference Model 2.0 • Summary: • Slide 9: We need to describe information model relationships and associations in a way that can be accessed and searched. • Slide 10: Increasing Metadata (from glossaries to ontologies) is highly correlated with Increasing Search Capability (from discovery to reasoning). • Slide 11: Three things about data (Description, Context, and Sharing) are needed for information sharing.

  13. More Results • Excerpts: Roadmap for EPA Data Architecture for DRM 2.0 and Semantic Networks, July 3, 2006: • Bigger Picture for EPA Data Architecture. • http://colab.cim3.net/cgi-bin/wiki.pl?EPADataArchitectureforDRM2 • Excerpts: Implementing the Semantic Web - Part 1. Semantic Technology Profile for the Data Reference Model: Use Case 2 - U.S. EPA, August 24, 2005: • Bigger Picture for EPA Enterprise Architecture: • See Government Computer News, At your service: Forget buying software; build your next application from existing components, April 24, 2006, See end of article.

  14. Roadmap for EPA Data Architecture for DRM 2.0 and Semantic Networks Brand Niemann Enterprise Architecture Team, US EPA, and Co-Chair, SICoP July 3, 2006

  15. Overview • Reviewed the earlier “data architecture” work with SRA consultants and concluded that we need more than use of the EPA Strategic Plan and the “EPA data standards – System of Registries”. • Decided to focus on making EPA Data DRM 2.0 Compliant in a Semantic Network in support of Network Data Model (Ontologies), Indicators, the “Big Decision”, Model-Driven Architecture, and recent requests for assistance.

  16. Roadmap for EPA Data Architecture See notes on next slide.

  17. Roadmap for EPA Data Architecture • General – all of these are developing ontologies individually that can be managed and interrelated collectively in the Semantic Wiki. • 1. Compliance/Performance – see Facility Registry System Pilot to improve accuracy in 2003 using the Qsent Telephone Directory Web Service. • 2. Indicators – see Sustainable Water Resources Roundtable and Chesapeake Bay 2005 Health and Restoration Assessment Reports (DRM 2.0 - Compliant Semantic Wiki Versions) • 3. Geospatial – see Collaborative Expedition Workshop, June 20-22nd Open Collaboration: Networking Geospatial Information Technology. • 4. Emergency Response – see Improving Rapid First Response at the SOA for E-Government Conference, May 24th. • 5. Assessment – see Semantic (Bayesian) Web Tutorial, April 28th. • 6. Health – see Third National Report on Human Exposure to Environmental Chemicals (2005) (in process) (DRM 2.0 - Compliant and Semantic Wiki Version).

  18. EPA System of Registries See next slide for contents and types.

  19. EPA System of Registries http://iaspub.epa.gov/sor/intro$.startup

  20. Implementing the Semantic WebPart 1. Semantic Technology Profile for the Data Reference Model: Use Case 2 - U.S. EPA Brand Niemann (US EPA), Chair, Semantic Interoperability Community of Practice (SICoP) Best Practices Committee (BPC), CIO Council August 24, 2005 http://web-services.gov/ and http://colab.cim3.net/cgi-bin/wiki.pl?SICoP

  21. 2. EPA DRM Status • 2.1 DRM Water Resources Use Case in Composite Application Platform: • Use Case 3: Demonstrating the maturity of FEA for multi-agency and community-of-interest information sharing and issue analysis. • This use case demonstrates how semantic models (ontology) can provide a framework for data interoperability where similar datasets need to be combined to support an aggregated business context for tactical decision making, analysis, and policy making across multiple communities of interest.

  22. 2. EPA DRM Status • 2.1 DRM Water Resources Use Case in Composite Application Platform (continued): • The FEA Business Reference Model provides a framework that facilitates a functional (rather than organizational) view of the federal government’s lines of business (LoBs), independent of the agencies, bureaus and offices that perform them. • This pilot focuses on the specific business function Environmental Monitoring and Forecasting (1-108-023). The end Use Case is to provide an interactive Composite Report on the Environment (EPA ROE 2006) that combines data about water indicators from a number of agencies into a coherent picture reflecting the status of nation’s waters in the social, economic and environmental context.

  23. 2. EPA DRM Status • 2.1 DRM Water Resources Use Case in Composite Application Platform (continued): • Recently started, the pilot will illustrate how indicator ontology can be created for water that uses ontological relationships to relate different indicators based on their properties, use and the type and quality of impact. The ontology can then be used to drive an interactive report that supports seamless navigation across the indicators and their cumulative impact on a particular area of concern. • See Use Case 1 Demo: • http://web-services.gov/pilots/DigitalHarbor/terrorismdemo.htm • See Use Case 2 Demo: • http://web-services.gov/pilots/DigitalHarbor/CampaignFinance.htm

  24. 2. EPA DRM Status Executable Integration of the FEA Reference Models in Composite Applications Fact Sheet at http://web-services.gov/SICoPPilotFactSheet_Final.pdf

  25. 2. EPA DRM Status • 2.1 DRM Water Resources Use Case in Composite Application Platform (continued): • Repurposed all the text and graphics from PDF to Word and PNG and added semantic structure linking (see next slide). • Extract the water data sources URL and documents for data mining by the Digital Harbor PiiE Platform. • Categorized the EPA Applied Analyses & Applications Workshop (AAAW) Into a Composite Application Business Ontology: • See Section 2.2 and http://www.aaaw2005.com/

  26. 2. EPA DRM Status See http://web-services.gov/lpBin22/lpext.dll/Folder5/Infobase5/1?fn=main-j.htm&f=templates&2.0

  27. 2. EPA DRM Status • 2.2 EPA Applied Analyses & Applications Workshop (AAAW) Composite Application Ontology: • The Composite Applications Business Ontology consists of: • Service Oriented Architecture (SOA) • Portals • Enterprise Integration • The titles and contents of the 64 presentations were analyzed and assigned to three basic categories and 14 sub-categories (see next slide).

  28. 2. EPA DRM Status • 2.2 EPA Applied Analyses & Applications Workshop (AAAW) Composite Application Ontology (continued): • The Composite Applications Business Ontology consists of: • SOA: .NET (1), Scientific Computing (1), GIS (2), Architecture (19), & Web Services (5). • Portals: Agency (3), Health (3), Environmental (4), Research & Science (4), and Other (3). • Enterprise Integration: Environmental Justice and Siting (4), Emergency Response (2), Report on the Environment (3), and Analytical and Quality Services (7). • Other: Future Trends (3). • Preparing for Composite Applications that (1) reduce redundant IT applications, increase interoperability, and facilitate business improvement (2) and produce data integration with EPA content and interoperability with non-EPA content. • (1) Source: Pat Plunkett, Chair, Federal IT Performance Measurement CoP, January 13, 2005. • (2) Source: John Sullivan, EPA Chief Architect, March 2, 2005.

More Related