Sandra Geisler, Maria-Esther Vidal, C. Cappiello, Bernadette Farias Lóscio, A. Gal, M. Jarke, M. Lenzerini, P. Missier, B. Otto, E. Paja, B. Pernici, J. Rehof
{"title":"Knowledge-Driven Data Ecosystems Toward Data Transparency","authors":"Sandra Geisler, Maria-Esther Vidal, C. Cappiello, Bernadette Farias Lóscio, A. Gal, M. Jarke, M. Lenzerini, P. Missier, B. Otto, E. Paja, B. Pernici, J. Rehof","doi":"10.1145/3467022","DOIUrl":null,"url":null,"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.","PeriodicalId":299504,"journal":{"name":"ACM Journal of Data and Information Quality (JDIQ)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Journal of Data and Information Quality (JDIQ)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3467022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
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.