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Open Science

A new strategic challenge for GESIS is the research on collaborative and participatory models and infrastructures which support open science processes in the social sciences.

Main research areas in the field of open science are:

  • Modelling of collaborative publishing processes in the social sciences
  • Analyses of collaborative information behavior and the development of collaborative retrieval services
  • Tools and infrastructures for social scientists to share their research -- including their code and data -- in order to make research reproducible
  • Alternative metrics (so-called altmetrics) to measure the impact of research output
Name Department Team Email Telephone
Backes, Tobias
Knowledge Technologies for the Social Sciences
Information & Data Retrieval
+49 (0221) 47694-539
Bensmann, Felix
Knowledge Technologies for the Social Sciences
Information Extraction & Linking
+49 (0221) 47694-524
Boland, M.A. Katarina
Knowledge Technologies for the Social Sciences
Information Extraction & Linking
+49 (0221) 47694-513
Breuer, Dr. Johannes
Survey Data Curation
Survey Data Augmentation
+49 (0221) 47694-471
Hienert, Dr. Daniel
Knowledge Technologies for the Social Sciences
Information & Data Retrieval
+49 (0221) 47694-525
Hopt, Oliver
Knowledge Technologies for the Social Sciences
Data & Services Engineering
+49 (0221) 47694-542
Hübbers, Dipl.-Ing. Gerrit
Knowledge Exchange and Outreach
Communications & Web
+49 (0221) 47694-231
Kern, Dr. Dagmar
Knowledge Technologies for the Social Sciences
FAIR Data and Human Information Interaction
+49 (0221) 47694-536
Klas, Dr. Claus-Peter
Knowledge Technologies for the Social Sciences
Data & Services Engineering
+49 (0221) 47694-520
Kohne, Julian
Präsidialbüro
+49 (0221) 47694-222
Krämer, Thomas
Knowledge Technologies for the Social Sciences
Data & Services Engineering
+49 (0221) 47694-201
Lietz, Dr. Haiko
Computational Social Science
Digital Society Observatory
+49 (0221) 47694-223
Mathiak, Dr. Brigitte
Knowledge Technologies for the Social Sciences
FAIR Data and Human Information Interaction
+49 (0221) 47694-510
Mayr, Dr. Philipp
Knowledge Technologies for the Social Sciences
Information & Data Retrieval
+49 (0221) 47694-533
Mutschke, Peter (M.A.)
Knowledge Technologies for the Social Sciences
FAIR Data and Human Information Interaction
+49 (0221) 47694-500
Nugraha, Sigit
Knowledge Technologies for the Social Sciences
Data & Services Engineering
+49 (0221) 47694-528
Saldanha Bach, Dr. Janete
Knowledge Technologies for the Social Sciences
FAIR Data and Human Information Interaction
+49 (0221) 47694-483
Schoch, David
Computational Social Science
Transparent Social Analytics
+49 (0221) 47694-710
Tavakolpoursaleh, Narges
Knowledge Technologies for the Social Sciences
Data & Services Engineering
+49 (0221) 47694-140
Weller, Dr. Katrin
Computational Social Science
Digital Society Observatory
+49 (0221) 47694-472
  • Soldner, Felix, Bennett Kleinberg, and Shane Johnson. 2022. Confounds and Overestimations in Fake Review Detection: Experimentally Controlling for Product-Ownership and Data-Origin. https://osf.io/29euc/?view_only=d382b6f03e1444ffa83da3ea04f1a04a.
  • Schoch, David. 2022. "netrankr: An R package for total, partial, and probabilistic rankings in networks." Journal of Open Source Software 7 (77): 4563. doi: https://doi.org/10.21105/joss.04563.
  • Saldanha Bach, Janete, Brigitte Mathiak, Valentina Hiseni, and Fidan Limani. 2022. Enhancing data findability: how scientists and repositories can improve their data visibility. GESIS – Leibniz Institute for the Social Sciences. doi: https://doi.org/10.5281/zenodo.6900267.
  • Limani, Fidan, Yousef Younes, Valentina Hiseni, Janete Saldanha Bach Estevao, Peter Mutschke, and Brigitte Mathiak. 2021. KonsortSWD Task Area 5 Measure 2 Report Scope: Milestones 1, 2, and 3. https://zenodo.org/record/5901207.
  • Saldanha Bach Estevao, Janete, Claus-Peter Klas, and Peter Mutschke. 2022. "The hurdles of current data citation practices and the adding-value of providing PIDs below study level." In JCDL '22: The ACM/IEEE Joint Conference on Digital Libraries in 2022 Proceedings, edited by Akiko Aizawa, Thomas Mandl, Zeljko Carevic, Annika Hinze, Philipp Mayr, and Philipp Schaer, 41. New York: ACM. https://doi.org/10.1145/3529372.3533293.