232 Opening up translational data impact through the Data Citation Corpus

Abstract

Objectives/Goals: Evaluate use and reuse of data in biomedical fields to explore how data advances translational benefit for science and patients. Methods/Study Population: In this study, we use the metadata for 5 million data citations in the Data Citation Corpus as a source to analyze the use of datasets from biomedical fields across a number of facets, including date, affiliations, and funders. We identify examples of datasets that have been used across different research fields by analyzing the disciplinary scopes of the datasets and the publications that cite them and explore patterns of reuse of datasets beyond the original research project from which it was created. Results/Anticipated Results: The analysis will provide insights into datasets showing broad usage in biomedical fields, the patterns of data use over time, and the affiliations and funders associated with highly used datasets. The analysis will also dive into examples of datasets showing use across different fields and usage beyond the original project. The results will showcase examples of valuable datasets in translational research and serve as a basis for exploring different considerations around the impact of open datasets. Discussion/Significance of Impact: The exploration of data citations will provide insights into open data showing translational reach and an example of how the Data Citation Corpus can support evaluation of the impact of research data.