WHAT A STATE GEOLOGICAL SURVEY LEARNED FROM CONTRIBUTING TO THE NATIONAL GEOTHERMAL DATABASE SYSTEM

State Geological Surveys in the U.S., in conjunction with the U.S. Geological Survey, have thousands of databases, directories, and 85,000+ geologic maps that collectively constitute a national geoscience data “backbone” for research and practical applications. Much of this data has been at-risk in its current format or is difficult to access. The National Geothermal Data System (NGDS) was implemented with the goal of making large quantities of geothermal-relevant geoscience data available to the public by creating a national, sustainable, distributed, and interoperable network of data providers. The NGDS can therefore be used as a model moving forward for improving data set discovery, access, and stewardship in the geosciences.

Many involved with the NGDS had no previous experience developing the necessary resources for credibility, sustainability, and interoperability of digital data sets. The Geological Survey of Alabama (GSA) was no exception, having had little previous experience developing the necessary resources to move 100+ years of mainly analog data into the digital environment. Some data (e.g., oil and gas well logs from the state Oil and Gas Board, older geologic maps) had been electronically scanned to an image, but much of that has not been digitized (e.g., is not machine-readable).

Even with machine-readable data sets, many times the metadata was not standardized, even within the GSA. The NGDS had to incorporate practices from every data provider who may have had different data user needs. Building on existing standards (e.g., OneGeology), and utilizing an iterative process, content models were developed for state geologic maps, oil and gas wells, and other data sets relevant to geothermal systems. These content models are an excellent basis for development and refinement of other geoscience content models.

Other issues encountered were primarily with regard to stewardship of data. Standardization and documentation of our own data resources were found lacking, while data discoverability proved near impossible for those not “in the know.” Data quality and provenance were often not clearly documented. Being aware of these issues is the first step to resolving them for the future. Thus, the GSA is able to develop a robust data management plan moving forward.