This study will examine progress made in establishing spatial data infrastructures and the challenges faced by those infrastructures, within the context of the National Spatial Data Infrastructure. The study will examine the role that the USGS can play in continuing to ensure access to high quality geospatial data and support its use in scientific analyses and decision-making through a spatial data infrastructure (SDI) construct.
The committee will undertake three main tasks:
1. Identify existing knowledge and document lessons learned during previous efforts to develop SDIs and their support of scientific endeavors;
2. Develop a vision for optimizing an SDI to organize, integrate, access, and use scientific data; and
3. Create a roadmap to guide the USGS in accomplishing the vision within the scope of the USGS Science Strategy.
private institutions, large discipline-specific organizations, and spatial data at the USGS.
Successful implementation of an SDI depends on an agency’s roadmap and strategy, organizational leadership and culture, standardization, technical competence, funding and contracting, workforce competence, and cooperation and partnerships. SDI roadmaps that were well developed and consistently reviewed and updated were the ones that were most successful. Roadmaps that were essentially well-written business plans clearly articulated the merit of an SDI and the community that it would serve. Organizational leadership and culture influence how roadmaps and strategic goals are carried out on a daily basis and probably determine the success or failure of SDI implementation. Establishing standards for the data community is critical for SDI success. Implementation was more seamless and effective in organizations that incorporated the needs of the user community to develop and improve standards, and ones that also accepted the need for data and information products to conform with consensus standards developed by domestic and international standards bodies. 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. Funding and contracting mechanisms affect SDI development. One key factor was adequate funding—not overfunding or underfunding—for carrying out critical activities. Workforce competence is another contributing factor: successful SDI implementation requires the presence throughout the organization of well-trained and respected professionals who understand the technology. Finally, partnerships with state and federal agencies