through the cyberinfrastructure pipeline. Once standards have been determined, the committee found, it was essential to move forward by consistently applying the standards and to avoid indecision over which standards to follow.

Technical Concerns

In examining the various SDIs and how they were implemented across different agencies, the committee found that agencies had to overcome some technical concerns. Data quality was an issue, and it was best addressed at the time of collection before data were propagated through the SDI. On a technical point, the primary requirement for fusing data is accurate georeferencing of data products; changing the detection or classification of data can result in large errors that arise because of small co-registration or geo-registration errors. The committee found that with evolving technology, the technology and tools of the underlying database structure would need to adapt constantly in anticipation of data types beyond the current set, such as multispectral data and an expansion of data layers. In this case, the automation of a stewardship process is valuable so that updates can occur regularly. It is imperative to avoid frequently changing formats. Large-scale data repositories with clear priority issues depended on the long-term sustainability of data-acquisition programs. In addition to data collection and analysis, it is important to archive data: the best integrated data in the world are of little value if they are not easily discoverable.

Funding and Contracting

The committee found that funding and contracting mechanisms affected how well implementation could be carried out. One key factor was adequate funding for carrying out activities—not overfunding or underfunding. Overfunding can lead to waste, whereas underfunding can lead to frustration and the inability to reach goals in a reasonable time, and the exact level of adequate funding for the USGS SDI will vary with each phase of the roadmap suggested in Chapter 5. With dedicated capital funds, resources can be properly allocated for data purchases and for developing clear metrics to track data priorities and results. An organization-wide purchasing contract allowed an organization to acquire technology and data in weeks instead of months. An open-data policy is fundamental for long-term support by stakeholders, and this long-term approach was necessary to withstand cycles in funding and priorities for public geodata.

Workforce Competence

The committee observed that workforce competence contributed to successful implementation of SDIs. Training and retaining a skilled workforce will be critical for introducing and maintaining an SDI. An SDI introduction will

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement