FAIR national election studies: How well are we doing?
Election studies are an important data pillar in political and social science, as most political research investigations involve secondary use of existing datasets. Researchers depend on high-quality data because data quality determines the accuracy of the conclusions drawn from statistical analyses. We outline data reuse quality criteria pertaining to data accessibility, metadata provision, and data documentation using the FAIR Principles of research data management as a framework (Findability, Accessibility, Interoperability, and Reusability). We then investigate the extent to which a selection of election studies fulfils these criteria using studies from Western democracies. Our results reveal that although most election studies are easily accessible and well documented and that the overall level of data processing is satisfactory, some important deficits remain. Further analyses of technical documentation indicate that while a majority of election studies provide the necessary documents, there is still room for improvement.
KeywordsAccessibility Data Documentation Election studies Findability Interoperability Research data management Reusability
We thank Kristi Winters and the anonymous reviewers for their helpful comments on previous versions of the paper. We also like to thank Katharina Bühren, Paul Vierus, and Timo Hutflesz for research assistance.
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