FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units
FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units
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DOI：
10.3390/publications8020021
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发表时间：
2020-06-01
期刊：
影响因子：
5.2
通讯作者：
Wittenburg, Peter
中科院分区：
文献类型：
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作者：
De Smedt, Koenraad;Koureas, Dimitris;Wittenburg, Peter
数据科学面临以下主要挑战：（1）开发可扩展的跨学科能力，（2）处理不断增加的数据量及其固有的复杂性，（3）构建有助于建立信任的工具，（4）创建在科学断言领域有效运作的机制，（5）将数据转化为可操作的知识单元，以及（6）促进数据互操作性。作为克服这些挑战的一种方法，我们进一步发展了早期互联网先驱提出的数字对象提案，将其作为可通过持久标识符访问的数据和元数据的封装。在过去的十年中，研究数据联盟内的各个团体重新审视了这一概念，并将其置于可查找、可访问、可互操作和可重用数据的公平指导原则的背景下。解释了公平数字对象 (FDO) 作为独立的、类型化的、机器可操作的数据包的基本组件。一项用例调查表明，研究界对 FDO 解决方案越来越感兴趣。我们的结论是，FDO 概念有潜力充当欧洲开放科学云 (EOSC) 等超级基础设施计划的可互操作联邦核心。
Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).