GIGAPsych: A Platform for Psychology Data Merging and Sharing

Our platform advances personality and work psychology by integrating data and making it available to scientists worldwide to address interdisciplinary scientific questions and societal problems. It facilitates the re-use of research data to test the robustness of research findings and address new research questions in the field of personality and work psychology. The database operates based on unique IDs used by participants in the acknowledged internet panels. Researchers can match such anonymous data of participants across studies conducted in various labs. Our database contains data science solutions to automatically read and create codebooks, merge all donated data vertically by adding new data of new participants and horizontally by creating longitudinal profiles, and store meta-data to offer an instant overview of the available information. As we aim to create a gigantic set of anonymized data, researchers will obtain a unique opportunity to (a) develop norms and descriptive statistics per instrument based on very large sample sizes, (b) test the factor structure and other psychometric properties of measures using very large sample sizes and across time, (c) combine multiple measures that are typically studied in isolation and explore possible commonalities or factor structure, e.g., in personality science, one could explore whether measures of traits (e.g., personality, intelligence) or motives have a common factor structure, and (d) test general relationships, e.g., the link between personality and work performance across many languages and cultures. As an essential part of the GIGAPsych, we developed regulatory legal documents that solve data management and privacy issues. Specifically, the database is fully compliant with the GDPR. In this way, we make sure that the entire psychology community can leverage on big data without the data being proprietary or under embargo restrictions and without individual researchers having to think about privacy violations or data management issues themselves.