Knowledge-Driven Data Ecosystems Toward Data Transparency

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
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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.
面向数据透明的知识驱动数据生态系统
数据生态系统(DE)提供了一个关键参与者或联盟驱动的基础设施,支持不同涉众之间的交互,并解决共享数据之间的互操作性问题。然而,尽管在数据治理和管理方面进行了多年的研究,但由于缺乏透明和可追溯的数据驱动管道,可信性仍然受到影响。在这项工作中,我们关注de在确保数据透明度时面临的需求和挑战。需求来源于数据和组织管理,以及更广泛的法律和道德考虑。我们提出了一种新的知识驱动DE体系结构,为满足所分析的需求提供了支柱。我们将在现实场景中说明我们的建议的潜力。最后,我们讨论并评价了在实现这些需求方面所提出的体系结构的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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