Paper Number
1142
Paper Type
Complete Research Paper
Abstract
Online data donation - the act of voluntarily providing personal information for research without any apparent quid pro quo - is becoming increasingly important for scholars to conduct rigorous research based on timely and comprehensive data. However, no generalisable principles exist that address this type of data disclosure. Therefore, we define data donation through literature and follow a design science approach to formulate principles. Developed from our definition and a qualitative survey study, these principles are further honed and assessed through focus groups and a quantitative study, ensuring donor protection and user-focused perspectives. Social exchange and fairness theories underpin our approach, guiding the development and evaluation of these principles. Our contributions comprise design principles for fair data donation, practical implementation suggestions, and an illustrative model. Thereby, we offer an alternative approach to collecting data while empowering citizens to support science in a fair and privacy-friendly way.
Recommended Citation
Pumplun, Luisa; Wagner, Amina; Koppe, Timo; and Reuter-Oppermann, Melanie, "A Design Science Approach Towards Fair Data Donation" (2024). ECIS 2024 Proceedings. 1.
https://aisel.aisnet.org/ecis2024/track10_dmds_ecosystems/track10_dmds_ecosystems/1
A Design Science Approach Towards Fair Data Donation
Online data donation - the act of voluntarily providing personal information for research without any apparent quid pro quo - is becoming increasingly important for scholars to conduct rigorous research based on timely and comprehensive data. However, no generalisable principles exist that address this type of data disclosure. Therefore, we define data donation through literature and follow a design science approach to formulate principles. Developed from our definition and a qualitative survey study, these principles are further honed and assessed through focus groups and a quantitative study, ensuring donor protection and user-focused perspectives. Social exchange and fairness theories underpin our approach, guiding the development and evaluation of these principles. Our contributions comprise design principles for fair data donation, practical implementation suggestions, and an illustrative model. Thereby, we offer an alternative approach to collecting data while empowering citizens to support science in a fair and privacy-friendly way.
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