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

Publikation: Artikel i tidsskrift og konference artikel i tidsskriftTidsskriftartikelForskningpeer review

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.
OriginalsprogEngelsk
Artikelnummer3
TidsskriftJournal of Data and Information Quality
Vol/bind14
Udgave nummer1
Sider (fra-til)1-12
ISSN1936-1963
DOI
StatusUdgivet - 23 dec. 2021

Emneord

  • Data transparency
  • data ecosystem
  • data quality
  • trustability

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