Advancing Strategic Science A Spatial Data Infrastructure Roadmap for the U.S. Geological Survey (2012) / Chapter Skim
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-- must be available for scientists and managers to find, use, and share spatial data both within and beyond the USGS. In the opinion of the Committee on Spatial Data Enabling USGS Strategic Science in the 21st Century, an SDI is so important for supporting the six Science Strategy directions that it could have had its own chapter in the Science Strategy report as an underpinning of the six directions.
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Although it is neither appropriate nor feasible for the committee to recommend changes in the organizational structure of the USGS, there are critical elements of successful SDI implementation that pertain to the entire organization that are appropriate to highlight, and these are described in this report. LESSONS LEARNED There is no established, validated process for developing an SDI, and past efforts have produced mixed results.
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Standards should serve the widest range of user types possible. Technology and tools of the underlying database structure will need to adapt constantly in anticipation of data types beyond the current set, such as multispectral data and an expansion of data layers.
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As envisioned, an optimal SDI at the USGS would need to include data acquisition, data standards, modern data management services, and a set of key application services essential for supporting USGS in addressing scientific questions and questions of societal impact. The SDI would also need to consider the importance of data sharing and data discovery and would need flexible methods of preserving geospatial data across extended time frames and through numerous changes and updates because the ability to document and analyze temporal changes on a national scale is of immense scientific and societal value.
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The leadership team will need to determine and define SDI system requirements (based on the six directions in the USGS Science Strategy and with consideration of user needs in other agencies, local governments, academe, and the public) , determine the organizational structure of the SDI, identify goals, establish timeframes and milestones, and develop performance metrics.
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Among the technical considerations, supporting the diverse science workflows will require the Survey to evaluate its current information-technology infrastructure to ensure that it is aligned with the USGS Science Strategy. In light of that assessment, the USGS can implement robust enterprise data management, begin the transition to using the Web as a computing platform, and ultimately implement a comprehensive, long-term knowledge-management infrastructure that supports end-to-end spatial data management, including the collection, integration, maintenance, and delivery of multidisciplinary scientific data.
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