Best practices for studies using digital data donation

Thijs C. Carrière*, Laura Boeschoten, Bella Struminskaya, Heleen L. Janssen, Niek C. de Schipper, Theo Araujo

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Digital trace data form a rich, growing source of data for social sciences and humanities. Data donation offers an innovative and ethical approach to collect these digital trace data. In data donation studies, participants request a copy of the digital trace data a data controller (e.g., large digital social media or video platforms) collected about them. The European Union’s General Data Protection Regulation obliges platforms to provide such a copy. Next, the participant can choose to share (part of) this data copy with the researcher. This way, the researcher can obtain the digital trace data of interest with active consent of the participant. Setting up a data donation study involves several steps and considerations. If executed poorly, these steps might threaten a study’s quality. In this paper, we introduce a workflow for setting up a robust data donation study. This workflow is based on error sources identified in the Total Error Framework for data donation by Boeschoten et al. (2022a) as well as on experiences in earlier data donation studies by the authors. The workflow is discussed in detail and linked to challenges and considerations for each step. We aim to provide a starting point with guidelines for researchers seeking to set up and conduct a data donation study.

Original languageEnglish
Pages (from-to)389–412
Number of pages24
JournalQuality and Quantity
Volume59
Issue numberSuppl 1
Early online date8 Oct 2024
DOIs
Publication statusPublished - 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Funding

This work is funded by the Dutch Research Council (NWO) Vidi grant (VI.Vidi.195.152; valid measures derived from incidental data) awarded to D. Oberski, and the D3I project (Platform Digital Infrastructure for Social Science & Humanities (PDI-SSH) grant obtained by T. Araujo).

FundersFunder number
Nederlandse Organisatie voor Wetenschappelijk OnderzoekVI.Vidi.195.152

    Keywords

    • Data donation
    • Data quality
    • Digital trace data
    • Local processing
    • Privacy preservation

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