A Research Roadmap to Advance Data Collaboratives Practice as a Novel Research Direction

Iryna Susha, T. Pardo, M. Janssen, N. Adler, S. Verhulst, Todd Harbour
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引用次数: 11

Abstract

An increasing number of initiatives have emerged around the world to help facilitate data sharing and collaborations to leverage different sources of data to address societal problems. They are called “data collaboratives”. Data collaboratives are seen as a novel way to match real life problems with relevant expertise and data from across the sectors. Despite its significance and growing experimentation by practitioners, there has been limited research in this field. In this article, the authors report on the outcomes of a panel discussing critical issues facing data collaboratives and develop a research and development agenda. The panel included participants from the government, academics, and practitioners and was held in June 2017 during the 18th International Conference on Digital Government Research at City University of New York (Staten Island, New York, USA). The article begins by discussing the concept of data collaboratives. Then the authors formulate research questions and topics for the research roadmap based on the panel discussions. The research roadmap poses questions across nine different topics: conceptualizing data collaboratives, value of data, matching data to problems, impact analysis, incentives, capabilities, governance, data management, and interoperability. Finally, the authors discuss how digital government research can contribute to answering some of the identified research questions.
推进数据协作实践作为一个新的研究方向的研究路线图
世界各地出现了越来越多的倡议,以帮助促进数据共享和合作,利用不同的数据来源来解决社会问题。他们被称为“数据协作者”。数据协作被视为一种将现实生活中的问题与各个部门的相关专业知识和数据相匹配的新方法。尽管它的重要性和越来越多的实践者的实验,在这一领域的研究是有限的。在本文中,作者报告了一个小组讨论数据协作面临的关键问题的结果,并制定了一个研究和发展议程。该小组包括来自政府、学术界和实践者的参与者,于2017年6月在纽约城市大学(美国纽约州史坦顿岛)举行的第18届数字政府研究国际会议期间举行。本文首先讨论数据协作的概念。然后在小组讨论的基础上制定研究问题和研究路线图的主题。研究路线图提出了九个不同主题的问题:数据协作的概念化、数据的价值、数据与问题的匹配、影响分析、激励、能力、治理、数据管理和互操作性。最后,作者讨论了数字政府研究如何有助于回答一些已确定的研究问题。
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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