Knowledge-Driven Data Ecosystems Toward Data Transparency

Author:

Geisler Sandra1ORCID,Vidal Maria-Esther2,Cappiello Cinzia3,Lóscio Bernadette Farias4,Gal Avigdor5,Jarke Matthias6,Lenzerini Maurizio7,Missier Paolo8,Otto Boris9,Paja Elda10,Pernici Barbara11,Rehof Jakob9

Affiliation:

1. Fraunhofer FIT and RWTH Aachen University, Aachen, Germany

2. TIB-Leibniz Information Centre for Science and Technology, Hannover, Gerrmany

3. Politecnico di Milano, Milano, Italy

4. Federal University of Pernambuco, Brazil

5. Technion Israel Institute of Technology, Haifa, Israel

6. RWTH Aachen University and Fraunhofer FIT, Aachen, Germany

7. Sapienza Università di Roma, Roma, Italy

8. Newcastle University, United Kingdom

9. TU Dortmund University and Fraunhofer ISST, Dortmund, Germany

10. IT University of Copenhagen, Copenhagen S, Denmark

11. Politecnico di Milano, Milano,, Italy

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.

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems and Management,Information Systems

Reference35 articles.

1. A Cognitive Model of Human Bias in Matching

2. Structuring Reference Architectures for the Industrial Internet of Things

3. Towards a European-Governed Data Sharing Space;Barbero Martina;https://www.bdva.eu/sites/default/files/BDVA DataSharingSpaces PositionPaper V2_2020_Final.pdf.,2020

4. Data and Information Quality

Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A design theory for data quality tools in data ecosystems: Findings from three industry cases;Data & Knowledge Engineering;2024-09

2. A CONCEPTUAL FRAMEWORK FOR THE GOVERNMENT BIG DATA ECOSYSTEM (‘datagov.eco’);Data & Knowledge Engineering;2024-09

3. Industrial data ecosystems and data spaces;Electronic Markets;2024-08-06

4. Towards FAIR Data Stream Processing Ecosystems;Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems;2024-06-24

5. Towards the Development of Interoperable Open Data Ecosystems: Harnessing the Technical, Semantic, Legal, and Organizational (TSLO) Interoperability Framework;Proceedings of the 25th Annual International Conference on Digital Government Research;2024-06-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3