A Linked Data Mosaic for Policy-Relevant Research on Science and Innovation: Value, Transparency, Rigor, and Community.

Wan-Ying Chang, Maryah Garner, Jodi Basner, Bruce Weinberg, Jason Owen-Smith
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引用次数: 2

Abstract

This article presents a new framework for realizing the value of linked data understood as a strategic asset and increasingly necessary form of infrastructure for policy-making and research in many domains. We outline a framework, the 'data mosaic' approach, which combines socio-organizational and technical aspects. After demonstrating the value of linked data, we highlight key concepts and dangers for community-developed data infrastructures. We concretize the framework in the context of work on science and innovation generally. Next we consider how a new partnership to link federal survey data, university data, and a range of public and proprietary data represents a concrete step toward building and sustaining a valuable data mosaic. We discuss technical issues surrounding linked data but emphasize that linking data involves addressing the varied concerns of wide-ranging data holders, including privacy, confidentiality, and security, as well as ensuring that all parties receive value from participating. The core of successful data mosaic projects, we contend, is as much institutional and organizational as it is technical. As such, sustained efforts to fully engage and develop diverse, innovative communities are essential.

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科学与创新政策相关研究的关联数据镶嵌:价值、透明度、严谨性和共同体。
本文提出了一个新的框架,用于实现关联数据的价值,将其理解为一种战略资产,并日益成为许多领域决策和研究的必要基础设施形式。我们概述了一个框架,即“数据马赛克”方法,它结合了社会组织和技术方面。在展示了关联数据的价值之后,我们强调了社区开发的数据基础设施的关键概念和危险。我们在科学和创新工作的大背景下具体化这个框架。接下来,我们将考虑将联邦调查数据、大学数据以及一系列公共和专有数据联系起来的新伙伴关系,这是朝着建立和维持有价值的数据马赛克迈出的具体一步。我们讨论了有关关联数据的技术问题,但强调关联数据涉及解决广泛数据持有者的各种问题,包括隐私、机密性和安全性,以及确保各方从参与中获得价值。我们认为,成功的数据拼接项目的核心,既在于技术,也在于制度和组织。因此,持续努力充分参与和发展多样化、创新型社区至关重要。
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