GSA Connects 2021 in Portland, Oregon

Paper No. 188-20
Presentation Time: 2:30 PM-6:30 PM

COMPILING RECOMMENDED PRACTICES FOR THE PRESERVATION OF GEOLOGICAL DATA AND SAMPLES TO PROMOTE THE FAIR PRINCIPLES


MASSEY, Madalyn, Front Range Community College, Fort Collins, CO 80526 and WALSTON, Patrick, Fort Lewis College, Durango, CO 81301

The US Geological Survey (USGS) National Geological and Geophysical Data Preservation Program (NGGDPP) is creating and updating recommended practices for the preservation of various geological and geophysical data collections. Many organizations, institutions, and agencies have collected data that is of use to the USGS and other researchers, but without applying modern recommended practices, this data can lose its integrity and value. We evaluated existing practices for Well Log Digitization, Structure-from-Motion (SfM), and Digital Scanning and compiled updated recommended practices. Legacy well log information stored on paper and film sit in repositories around the country, at risk of physical damage, and largely unavailable to researchers. Using a digital scanner to create images and extract data will allow for preservation of the records and facilitate access and reuse by the scientific community. SfM, a growing practice in geosciences, is the reconstruction of 2D images into 3D models with the application of photogrammetry software. This aspect of SfM will focus on the collection of 3D models of physical samples such as rock cores, hand samples, and fossils. Standardized recommended practices will promote FAIR principles (Findable, Accessible, Interoperable and Reusable) for data and samples. The information we collected on the subjects was compiled, analyzed, and then reported to our USGS project mentors and the larger scientific community through virtual webinars. The USGS Geological Materials Repository and NGGDPP promote the preservation, curation, retrieval and availability of data and samples for research. The goal of this project is to continue supporting these practices, and values, to further maximize the integrity of data for the use in research.