How FAIR are empirical political science studies?

Within the domain of political science studies, I have recently done a paper evaluating the FAIR criteria (making data findable, accessible, interoperable, and reusable) for some of the most relevant general election studies. This covered eighteen large-scale surveys from western democracies with at least two waves and incorporated a comparison between 2018 and 2024. The assessment of FAIRness for these studies showed much room for improvement, and results remained relatively the same compared to the last six years. However, these datasets only represent a small area in terms of empirical political science research, resulting in a new effort to evaluate FAIR criteria for a broader universe.

The new study includes datasets used in articles from six well-known and highly recognized political science journals: American Political Science Review (APSR), American Journal of Political Science (AJPS), British Journal of Political Science (BJPS), International Organization (IO), Journal of Politics (JOP), and Political Analysis (PA). It is based on previous work (Key, 2016) with a dataset using the volumes from 2013/2014 and extends this by the volumes of 2022/2023. The FAIR scores for all available studies can be evaluated using dataset persistent identifiers. The analysis will show the state of FAIRness for the whole corpus of data used by these relevant political science studies. In addition, a comparison between recent studies and those from nine years before will be done. Also, factors for increased FAIRness of studies in the domain of empirical political science will be highlighted.