Introducing openESM: A database of openly available experience sampling datasets

Abstract Experience sampling via mobile devices enables unprecedented insights into daily life. However, individual studies often cannot answer research questions conclusively, and open data are scattered across repositories in different formats. This impedes research into robustness, generalizability, and heterogeneity. We address this issue by introducing , an open-source database of openly available experience sampling datasets in a harmonized format. The growing database currently comprises 60 datasets with more than 16,000 participants and more than 740,000 observations. Metadata can be searched via our website ( openesmdata.org ) to select and download datasets via packages in R and Python. We demonstrate the potential of through an analysis of within-person correlations of positive and negative affect in 39 datasets, providing evidence for a large negative momentary correlation ( $$-0.49$$ - 0.49 , 95% CI: [ $$-0.54$$ - 0.54 , $$-0.42$$ - 0.42 ]). We end by discussing the design principles that will allow to become a continuously evolving community resource for cumulative experience sampling research.