Research

GESIS - for a research-based infrastructure

GESIS is a research-based infrastructure institution for the social sciences and conducts its own continuous and interdisciplinary research in four major research areas. The results of our research serve both to gain scientific knowledge and to sustainably improve our offerings for the social sciences.

For GESIS, the quality of data takes center stage. GESIS strives to provide high-quality research data as well as methods and tools that enable users to assess for themselves how high the quality of research data is.

With our research work in the areas of Survey Methodology, Computational Methods, Research Data Management and Substantive Research, we are constantly expanding and optimizing our portfolio of services, with which we support researchers who work with quantitative data on social science issues and make their own contributions to fundamental substantive issues.

Research work at GESIS

  • Dräger, Jascha, Nora Müller, and Klaus Pforr. 2025. "The Keys to the House : How Wealth Transfers Stratify Homeownership Opportunities." Social Science Research 103190: . doi: https://doi.org/10.1016/j.ssresearch.2025.103190.
  • Burger, Axel, Julia Weiß, and Axel Babst. 2025. "Euro-App: A smartphone-based intensive longitudinal data collection in the context of the European Elections 2024." DACH Wahlstudientreffen, University of Lausanne, 2025-03-28.
  • Lipinsky, Anke. 2025. "Geschlechtsbezogene Gewalt in der Wissenschaft." Bundesarbeitsgemeinschaft Wissenschaft, Hochschule und Technologiepolitik (Bündnis90/Die Grünen) , 2025-03-08.
  • Wiltshire, Deborah, James Scott, Simon Parker, Emily Griffiths, Carlotta Greci, Yannis Kotrotsios, Richard Welpton, Arne Wolters, Christine Woods, Olly Butters, John Sanderson, and Amy Tilbrook. 2025. Handbook on Statistical Disclosure Control for Outputs. The Safe Data Access Professionals Working Group. https://securedatagroup.org/wp-content/uploads/2025/03/sdc-handbook-v2.0.pdf.
  • Mathiak, Brigitte, Janete Saldanha Bach, Yudong Zhang, and Peter Mutschke. 2025. "Improving the FAIRness of metadata through FAIR Signposting [Poster]." FAIRfest: Celebrating advancements of FAIR solutions in EOSC, 2025-02-20. https://fair-impact.eu/events/fair-impact-events/fairfest-celebrating-advancements-fair-solutions-eosc.