myneData: Towards a Trusted and User-controlled Ecosystem for Sharing Personal Data

  • Personal user data is collected and processed at large scale by a handful of big providers of Internet services. This is detrimental to users, who often do not understand the privacy implications of this data collection, as well as to small parties interested in gaining insights from this data pool, e.g., research groups or small and middle-sized enterprises. To remedy this situation, we propose a transparent and user-controlled data market in which users can directly and consensually share their personal data with interested parties for monetary compensation. We define a simple model for such an ecosystem and identify pressing challenges arising within this model with respect to the user and data processor demands, legal obligations, and technological limits. We propose myneData as a conceptual architecture for a trusted online platform to overcome these challenges. Our work provides an initial investigation of the resulting myneData ecosystem as a foundation to subsequently realize our envisioned data market via the myneData platform.

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Author:Roman Matzutt, Dirk Müllmann, Eva-Maria Zeissig, Christiane Horst, Kai Kasugai, Lidynia Sean, Simon WieningerGND, Jan Henrik Ziegeldorf, Gerhard GuderganGND, Indra Spiecker gen. Döhmann, Klaus Wehrke, Martina ZiefleORCiDGND
Parent Title (German):Lecture Notes in Informatics (LNI)
Place of publication:Bonn
Editor:Maximilian Eibl, Martin Gaedke
Document Type:Conference Proceeding
Language:German
Date of Publication (online):2023/11/14
Date of first Publication:2017/09/25
Release Date:2024/05/31
Tag:Data Protection Laws; Personal Information Management; Personal User Data; Platform Design; Privacy Enhancing Technologies
GND Keyword:PrivacyGND; Data ProfilingGND
Note:
This work has been funded by the German Federal Ministry of Education and Research (BMBF) under funding reference numbers 16KIS0443 to 16KIS0447. The responsibility for the content of this publication lies with the authors.
FIR-Number:SV6868
Institute / Department:FIR e. V. an der RWTH Aachen
Business Transformation
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften