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Managing different types of data

In social science research, different types of research data are used, each of which places distinct demands on research data management. Currently, a particular focus is on the challenges of handling new types of data: digital behavioral data, which are obtained from online platforms or sensors, require new, research-based approaches for the archiving, documentation, and provision of data, taking into account legal and ethical frameworks. However, methods for processing and managing survey data are also continuously being developed and improved. Another research area involves linked data, resulting for example from linking survey data with social media data or geospatial data.

Research Output

  • Akdeniz, Esra, Kerrin Borschewski, Johannes Breuer, and Yevhen Voronin. 2023. “Sharing social media data: The role of past experiences, attitudes, norms, and perceived behavioral control.” Frontiers in Big Data 5 (16 January 2023): 971974. doi: 10.3389/fdata.2022.971974. 
  • Bensmann, Felix, Lars Heling, Stefan Jünger, Loren Mucha, Maribel Acosta, Jan Göbel, Gotthard Meinel, Sujit Sikder, York Sure-Vetter, and Benjamin Zapilko. 2020. “An Infrastructure for Spatial Linking of Survey Data.” Data Science Journal 19 (1): 27. doi: 10.5334/dsj-2020-027.  
  • Daikeler, Jessica, Leon Froehling, Indira Sen, Lukas Birkenmaier, Tobias Gummer, Jan Schwalbach, Henning Silber, Bernd Weiß, Katrin Weller, and Clemens Lechner. 2024. “Assessing Data Quality in the Age of Digital Social Research: A Systematic Review.” Social Science Computer Review. online first. doi: 10.1177/08944393241245395.  
  • Kinder-Kurlanda, Katharina E., Katrin Weller, Wolfgang Zenk-Möltgen, Jürgen Pfeffer, and Fred Morstatter. 2017. “Archiving Information from Geotagged Tweets to Promote Reproducibility and Comparability in Social Media Research.” Big Data & Society 4 (2): 1-14. doi: 10.1177/2053951717736336. 
  • Perry, Anja, and Wolfgang Zenk-Möltgen. 2024. “When to use the k-rule? - Criteria for managing uniqueness and de-anonymization risk in social science survey data.” Transactions on Data Privacy 17 (3): 123-46. http://www.tdp.cat/issues21/abs.a507a23.php.