Brand Niemann
Senior Enterprise Architect
US EPA

Tuesday 2:15pm - 3:15pm

Level: Data Management - Introductory

At present, EPA has no overarching strategy or comprehensive set of business and technical rules that can support the level of integration and data sharing that the EPA target applications architecture recommends. This will be addressed, in part, by an enterprise data management strategy being developed by a Data Integration Workgroup Community of Interest hosted by the EA Team this fall. A key premise articulated by participants in the recent Enterprise Data Integration and Data Warehousing Meeting was to “Design to Share” for new data systems and to “Enable to Share” existing data systems from the Federal Enterprise Architecture’s Data Reference Model 2.0. An EPA Data Architecture for DRM 2.0 was developed and applied last year based on the premise of reusing the data and information rather than changing the data systems themselves. The concepts and standards of the Semantic Web (also called the Data Web or Web 3.0) are being applied to the reuse of data and information in an EPA Data Architecture for DRM 3.0 and Web 3.0 using EPA and interagency data and information sources. This is a fundamentally different approach than conventional data integration and data warehousing that requires changes in data systems and is being applied to net-centric operations by the Federal Semantic Interoperability Community of Practice (SICoP).

This enterprise data management strategy illustrates (a) “how the DRM’s abstract nature enables agencies to use multiple implementation approaches, methodologies, and technologies while remaining consistent with the foundational principles of the DRM”, and (b) “that associating elements of concrete architectures with the DRM abstract model promotes interoperability between cross-agency architectures / implementations.” The example used in this enterprise data management strategy illustrates how (a) bringing the data and the metadata back together, (b) bringing the structured data and unstructured information back together, and (c) bringing the data description and context back together promotes sharing and reuse and makes further sharing and reuse easier.