2002 Denver Annual Meeting (October 27-30, 2002)

Paper No. 9
Presentation Time: 3:45 PM


LAGUEUX, Francois1, NASSER, Khalil H.1, O'BRIEN, Grady M.2 and D'AGNESE, Frank A.2, (1)Software Engineering Group, reVision, Inc, 1320 Detroit Street, Suite 1, Denver, CO 80206, (2)United States Geol Survey, 520 North Park Avenue, Suite 221, Tucson, AZ 85719, knasser@revisioninc.com

The Geoscience Knowledge Integration Protocol (GeoPro) is managed by an enterprise knowledge management system. This system operates on three enterprise levels: data and information management, work-flow management, and decision processes.

DATA AND INFORMATION MANAGEMENT –Integration of multidisciplinary geoscience point and spatial data from multiple sources is managed in a relational technical database. The technical database is refreshed on-demand and includes an audit trail detailing data updates and sources. This provides the enterprise with a single source of data and information with documented integrity. Users can create a project database for each enterprise project, which contains a subset of the enterprise technical data. Extraction, transformation, and loading (ETL) systems manage the information flow between the initial data sources, technical database, and the project database.

WORK-FLOW MANAGEMENT- This module formalizes, integrates, and automates geosciences work-flow processes. The user can design work processes including input file preparation, selection of analytical and numerical tools, and visualization tools, using the process-modeling interface. Execution of the designed process will gather and transform the project data into input files, run the analytical and numerical tools, and version and store the resulting data into the project database. The work process models and underlying project data can be shared among enterprise teams. GeoPro is a shift from project-centric to enterprise-wide management of resources, knowledge and data.

DECISION PROCESSES - A data warehouse with multi-dimensional cubes are created using on-line analytical processing (OLAP) technology. Decision-analysis tools can access these powerful multi-dimensional cubes to support rapid analysis of several decision-analysis scenarios using up-to-date multidisciplinary data.