Introducing openESM: a database of openly available experience sampling datasets, including the R/Python interface | R bloggers

Experience sampling via mobile devices enables unprecedented insights into everyday life. However, individual studies often cannot adequately answer research questions, and open data is spread across repositories in different formats. This hinders research into robustness, generalizability and heterogeneity. We address this problem by introducing openESMan open source database of openly available experience sampling datasets in a harmonized format. The growing database currently includes 60 datasets with more than 16,000 participants and more than 740,000 observations. You can look up metadata via our website (https://openesmdata.org to select and download datasets via packages in R and Python. We demonstrate the potential of openESM by analyzing within-person correlations between positive and negative affect in 39 data sets, providing evidence for a large negative temporal correlation ($-0.49$, 95% CI: [$-0.54$, $-0.42$]). We end by discussing the design principles that make this possible openESM to become a continuously evolving community resource for cumulative experience sampling research. The preprint is available [Here].

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