State of the data: Assessing the FAIRness of USGS data

Data Science Journal
By: , and 

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Abstract

In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.

Publication type Article
Publication Subtype Journal Article
Title State of the data: Assessing the FAIRness of USGS data
Series title Data Science Journal
DOI 10.5334/dsj-2024-022
Volume 23
Year Published 2024
Language English
Publisher CODATA
Contributing office(s) Science Analytics and Synthesis
Description 20 p.
Google Analytic Metrics Metrics page
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