Paper No. 7
Presentation Time: 2:30 PM


HILLS, Denise J., Energy Investigations, Geological Survey of Alabama, P.O. Box 869999, Tuscaloosa, AL 35486-6999 and RICHARD, Stephen M., Arizona Geological Survey, 416 W. Congress, #100, Tucson, AZ 85701,

The Geological Survey of Alabama (GSA) has been providing data to the National Geothermal Data System (NGDS), which was organized by the Association of American State Geologists with funding from the U.S. Department of Energy. The goal of NGDS is to make large quantities of geothermal-relevant geoscience data available to the public by creating a national, sustainable, distributed, and interoperable network of data providers. The GSA had little previous experience developing the necessary resources to move over 100 years of mainly analog data into the digital environment. Some data (e.g., oil and gas well logs) had been scanned, but even much of that has not been digitized (e.g., is not machine-readable). Here we expand upon some of the lessons the GSA has learned throughout this process, including a vision of a path forward.

A major challenge that had to be overcome was the disconnect between interoperability requirements for the content models and the research interests of scientists providing the data. Content models had to address different user needs, and different data provider scenarios. These were developed for interoperability, and therefore had to incorporate practices from every data provider (in theory, at least one provider for each state). This challenge was overcome by open and direct dialogue between the content developers and content providers. Although the iterative process could be frustrating at times, the result is a robust and thoroughly tested content model for geothermal data. This content model shall provide an excellent starting point for other geoscience data content models.

GSA encountered other issues during the NGDS project, primarily in regards to stewardship of data. Standardization and documentation of our own data resources were found lacking. Data discoverability of GSA data proved difficult for anyone not “in the know,” while quality and provenance were often unknown. Moving forward, the GSA has a working model for stewardship of data, including what information and metadata should be collected to ensure future interoperability and discoverability.