{"id":6178,"date":"2025-07-15T11:38:17","date_gmt":"2025-07-15T09:38:17","guid":{"rendered":"https:\/\/leibniz-hbi.de\/?post_type=hbi-publications&p=6178"},"modified":"2025-07-22T10:33:20","modified_gmt":"2025-07-22T08:33:20","slug":"community-data-trust-for-sensitive-data","status":"publish","type":"hbi-publications","link":"https:\/\/leibniz-hbi.de\/en\/hbi-publications\/community-data-trust-for-sensitive-data\/","title":{"rendered":"Community Data Trust for Sensitive Data"},"content":{"rendered":"

How can researchers collect and exchange sensitive social media data for academic research in a way that complies with data protection regulations? Answers to this question are provided by Jan Rau<\/a>, Moritz F\u00fcrneisen<\/a>, and Dr. Gregor Wiedemann<\/a> in their working paper \u201cA Community Data Trust for the Shared Use of Sensitive Data in Communication Science.\u201d<\/p>\n

Together with Nils Jungmann, Pascal Siegers, and Heidi Schulze, they have developed the concept of a community data trust to facilitate the joint creation and use of sensitive data. Using the example of research on right-wing extremist online communication, the authors show how a community data trust can be set up to enable joint data use and optimize data quality.<\/p>\n

\"CoverThe paper has been published in the Working Papers series of the German Data Forum (RatSWD) and is available online.<\/p>\n

Summary of the Article<\/h2>\n

This article discusses the concept of a community data trust (CDT), which was developed to facilitate the collaborative creation and utilization of sensitive data for research on right-wing extremist online communication. This data stewardship model is distinctive in that the steward does not act as a monopolist between data providers and users; rather, the steward involves the users in the creation and maintenance of the dataset. Community data stewardship is useful when consolidating fragmented data sets increases their scientific value. Using research on right-wing extremist online communication as an example, we demonstrate how community data stewardship can be structured to enable shared data use and optimize data quality.<\/p>\n

In online political communication research, actor-based approaches rely on lists of relevant actors and networks. These lists serve as the basis for automated data collection on various online platforms and messenger services. Creating these lists is very time-consuming. By sharing these lists, researchers can significantly reduce their workload and improve the quality of their data. However, due to legal uncertainties and limited incentives for individual researchers, sharing data in sensitive areas remains the exception rather than the rule.<\/p>\n

The CDT addresses these issues by creating a research infrastructure that manages account lists as a shared resource. This resource can be used by the research community according to their own established rules. Data stewardship is based on the principle of reciprocity, meaning researchers accessing the lists for their projects must perform necessary data checks and updates, with an online database providing technical support for this exchange and joint data maintenance. To this end, the CDT implements technical and organizational measures to protect and secure data and provides a structure that (1) promotes the sharing of data, (2) creates trust and legal certainty, (3) improves data quality, and (4) increases the security of researchers.<\/p>\n

Nils Jungmann, Siegers, P., Rau, J. P., F\u00fcrneisen, M., Wiedemann, G. & Schulze, H. (2025). Eine Community-Datentreuhand f\u00fcr die gemeinsame Nutzung sensibler Daten in der Kommunikationswissenschaft<\/span> [A Community Data Trust for the Shared Use of Sensitive Data in Communication Science]. (RatSWD Working Paper 288\/2025). Berlin. German Data Forum (RatSWD). https:\/\/doi.org\/10.17620\/02671.97<\/a><\/p>\n","protected":false},"featured_media":681,"template":"","tags":[398],"class_list":["post-6178","hbi-publications","type-hbi-publications","status-publish","has-post-thumbnail","hentry","tag-miscellaneous"],"acf":[],"yoast_head":"\nCommunity Data Trust for Sensitive Data - Leibniz Institut f\u00fcr Medienforschung | Leibniz Institute for Media Research<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/leibniz-hbi.de\/en\/hbi-publications\/community-data-trust-for-sensitive-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Community Data Trust for Sensitive Data\" \/>\n<meta property=\"og:description\" content=\"How can researchers collect and exchange sensitive social media data for academic research in a way that complies with data protection regulations? 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