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
Hienert, Daniel, Benjamin Zapilko, Philipp Schaer, and Brigitte Mathiak. 2011. "Web-based multi-view visualizations for aggregated statistics." In 2nd International Workshop on Data Visualization and Integration on the Web (DATAVIEW); Proceedings of the 5th International Workshop on Web APIs and Services Mashups Proceedings (Mashups '11), New York: ACM. doi: https://doi.org/10.1145/2076006.2076019. https://arxiv.org/pdf/1110.3126v1.
Hienert, Daniel, Benjamin Zapilko, Philipp Schaer, and Brigitte Mathiak. 2012. "Vizgr: linking data in visualizations." In Web information systems and technologies : 7th international conference ; revised selected papers, edited by Joaquim Filipe, and José Cordeiro, Lecture notes in business information processing 101, 177-191. Berlin: Springer. https://link.springer.com/chapter/10.1007%2F978-3-642-28082-5_13.
Zapilko, Benjamin, and Brigitte Mathiak. 2011. "Performing statistical methods on linked data." In DC-2011: The Hague proceedings ; Proceedings of the International Conference on Dublin Core and Metadata Applications, https://dcpapers.dublincore.org/index.php/pubs/article/view/3627.
Mathiak, Brigitte. 2011. "Linked Data Cloud." Expertenworkshop „Metadaten zur Qualitätssicherung von Forschungsdaten“.
Hienert, Daniel, Philipp Schaer, Johann Schaible, and Philipp Mayr. 2011. "A novel combined term suggestion service for domain-specific digital libraries." In Research and advanced technology for digital libraries: international conference on theory and practice of digital libraries, TPDL 2011, edited by Stefan Gradmann, Francesca Borri, Carlo Meghini, and Heiko Schuldt, Lecture Notes in Computer Science 6966, 192-203. Springer. http://arxiv.org/abs/1106.1523.
Lipinsky, Anke. 2026. "Geschlechtsbezogene Gewalt in der Wissenschaft: Strukturen, Dynamiken, Konsequenzen." https://www.leuphana.de/einrichtungen/gleichstellung/aktuell/termine/ansicht/2026/03/09/geschlechtsbezogene-gewalt-in-der-wissenschaft-strukturen-dynamiken-konsequenzen.html , Leuphana Universität, 2026-03-09.
Kessling, Philipp, and Felix Victor Münch. 2026. "Riding the Spider: A Network-Sampling Framework for Multi-Platform Data Collections." M&K Medien & Kommunikationswissenschaft 1 (74): 52-70. doi: https://doi.org/10.5771/1615-634x-2026-1-52.
Darius, Philipp, Johannes Breuer, Simon Kruschinski, Felicia Loecherbach, Jasmin Riedl, and Sebastian Stier. 2026. "Election research in the age of regulated data access under the EU Digital Services Act." Internet Policy Review 1 (15): 1-25. doi: https://doi.org/10.14763/2026.1.2080.
Asensio Manjon, Marc, Anna De Castellarnau, Barbara Felderer, Carlos Poses, Lydia Repke, Melanie Revilla, Willem E. Saris, Hannah Schwarz, and Wiebke Weber. 2026. SQP 3.0 data (Version 1.0.0). doi: https://doi.org/10.7802/2968.
Wiltshire, Deborah, Anne van der Kant, Bolton Sharon, Maria Alexandra Rujano, Christian Ohmann, Eugenio Gonzalo Jimenez, Anne-Marie Tuikka, Marcos Casada Barbero, Beate Lichtwardt, and Sharon Bolton. 2025. EOSC-ENTRUST D7.1 Driver validation report of Year 1 EOSC-ENTRUST architectural blueprint including gap analysis. zenodo. doi: https://doi.org/10.5281/zenodo.14988868.
