Knowledge-Driven Data Ecosystems Toward Data Transparency

Sandra Geisler, Maria-Esther Vidal, Cinzia Cappiello, Bernadette Farias Lóscio, Avigdor Gal, Matthias Jarke, Maurizio Lenzerini, Paolo Missier, Boris Otto, Elda Paja, Barbara Pernici, Jakob Rehof

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review


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.
Original languageEnglish
Article number3
JournalJournal of Data and Information Quality
Issue number1
Pages (from-to)1-12
Publication statusPublished - 23 Dec 2021


  • Data transparency
  • data ecosystem
  • data quality
  • trustability


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