GESIS Data Archive Leibniz Institute for the Social Sciences

Overview

The GESIS Data Archive is the central social science data repository of GESIS – Leibniz Institute for the Social Sciences, headquartered in Cologne, Germany. It is one of the most comprehensive archives of its kind in the German-speaking world and holds more than 7,000 national and international studies available for secondary analysis.

History and Founding

The archive traces its origins to 1960, when it was established as the Central Archive for Empirical Social Research (Zentralarchiv für Empirische Sozialforschung) at the University of Cologne. Over subsequent decades it evolved into the data infrastructure arm of GESIS – Leibniz Institute for the Social Sciences. In 2021 the archive was reorganized into two departments: the Department of Data Services for the Social Sciences (DSS) and the Department of Survey Data Curation (SDC).

Collections and Holdings

The archive preserves primarily quantitative social research data, with holdings encompassing survey data, aggregate time series, and digital behavioral data. Flagship datasets include the German Longitudinal Election Study (GLES) and the ALLBUS general social survey series. Collections span intercultural comparative surveys, multimodal data, and longitudinal series dating from the 1960s to the present.

Access and Usage

Data are discoverable through the GESIS Data Search catalogue at search.gesis.org. Most datasets are freely available upon registration. Sensitive data are accessible through the GESIS Secure Data Center in Cologne (for survey data) and a Safe Room in Mannheim (for official statistics). The archive is certified with the CoreTrustSeal as a trustworthy digital repository and follows the Open Archival Information System (OAIS, ISO 14721) standard.

Research Infrastructure

GESIS is Germany's largest infrastructure institute for the social sciences and a member of the Leibniz Association. It supports researchers across the entire research data lifecycle, from study design and data collection through curation, archiving, and long-term preservation. Metadata are made machine-readable and interoperable through international standards, and persistent identifiers (DOIs) are assigned to all archived datasets.