Knowledge-Driven Data Ecosystems Toward Data Transparency
- Sandra Geisler,
- Maria-Esther Vidal,
- Cinzia Cappiello,
- Bernadette Farias Lóscio,
- Avigdor Gal,
- Matthias Jarke
- RWTH Aachen University,
- Fraunhofer Institute for Applied Information Technology,
- TIB-Leibniz Information Centre for Science and Technology,
- Polytechnic University of Milan,
- Federal University of Pernambuco,
- Technion - Israel Institute of Technology
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewPublication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOriginal language
EnglishArticle number
3Pages from-to (Number of pages)
Pages 1-12Journal (Volume, Issue Number)
Journal of Data and Information Quality (Volume 14, Issue 1)Publication milestones
- Published - 23/12/2021
Publication status
Published - 23/12/2021
ISSN
1936-1963Publication IDs
- Scopus: 85124698785
Abstract
A data ecosystem (DE) offers a keystone-player or alliance-driven infrastructure that enables the interaction of different stakeholders and the resolution of interoperability issues among shared data. However, despite years of research in data governance and management, trustability is still affected by the absence of transparent and traceable data-driven pipelines. In this work, we focus on requirements and challenges that DEs face when ensuring data transparency. Requirements are derived from the data and organizational management, as well as from broader legal and ethical considerations. We propose a novel knowledge-driven DE architecture, providing the pillars for satisfying the analyzed requirements. We illustrate the potential of our proposal in a real-world scenario. Last, we discuss and rate the potential of the proposed architecture in the fulfillmentof these requirements.
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