GIGAPsych: An Open Database for Data Sharing

In this database, researchers can submit (pseudonymized) survey-based data at the item level (e.g., personality, intelligence tests, work performance), which will be automatically merged with existing data from other researchers. When the data contain a unique participant ID (e.g., from popular online recruitment panels), it would further be possible to (a) merge data from the same participants who have completed multiple studies measuring constructs that are typically studied in isolation and (b) test longitudinal designs, for instance, when participants have completed the same measures multiple times. The more data containing unique IDs are donated to the platform, the more the chances that there will be some overlap of the same individuals across different studies. Furthermore, through the database interface, researchers will be able to perform online analyses (e.g., calculate average scores and correlation matrices) and request the merged (pseudo-anonymized) data for download.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-13
DOI
https://doi.org/10.5281/zenodo.18632572
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.00
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article

GIGAPsych: An Open Database for Data Sharing

Antonis Koutsoumpis, Jan Luca Pletzer, Jacek Buczny, GIULIANA SPADARO et al.
Zenodo (CERN European Organization for Nuclear Research)
Personality Traits and Psychology
article

GIGAPsych: An Open Database for Data Sharing

Antonis Koutsoumpis, Jan Luca Pletzer, Jacek Buczny, GIULIANA SPADARO, Wieslaw Kopec, Reinout E. de Vries
article en

Abstract

In this database, researchers can submit (pseudonymized) survey-based data at the item level (e.g., personality, intelligence tests, work performance), which will be automatically merged with existing data from other researchers. When the data contain a unique participant ID (e.g., from popular online recruitment panels), it would further be possible to (a) merge data from the same participants who have completed multiple studies measuring constructs that are typically studied in isolation and (b) test longitudinal designs, for instance, when participants have completed the same measures multiple times. The more data containing unique IDs are donated to the platform, the more the chances that there will be some overlap of the same individuals across different studies. Furthermore, through the database interface, researchers will be able to perform online analyses (e.g., calculate average scores and correlation matrices) and request the merged (pseudo-anonymized) data for download.

Zenodo (CERN European Organization for Nuclear Research)
Polish-Japanese Academy of Information Technology (PL), Vrije Universiteit Amsterdam (NL), Erasmus University Rotterdam (NL)
Openalex Percentile: Top 21%
Personality Traits and Psychology
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