Analysis on the Connotation, Context and Main Issues of Government Data Governance

  • Xia Yikun
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  • Center for the study of information resources, Wuhan University, Wuhan 430072

Received date: 2017-11-28

  Revised date: 2018-02-02

  Online published: 2018-05-05

Abstract

[Purpose/significance] The research on government data governance is a hotspot in the field of government information management, it has important theoretical meaning and practical value to connect and promote the key issues of government information management, such as government information disclosure, open data and public information reuse. [Method/process] By the methods of literature review, concept comparison, background analysis and logical reasoning, this paper focused on the connotation of government data governance and its constituent elements, pointed out the necessity of its concept generation from the aspects of data driven administration, economic development, social governance and data risk prevention. [Result/conclusion] In this paper, the main content and procedure of government data governance are introduced and analyzed from three different perspectives of macroscopic, midscopic and microscopic. Then, it further presents four fundamental characters of government data governance:architecture integrity, management orderly, governance of structural interaction and the urgency of risk response. At last, it analyzes the main problems and challenges faced by government data governance which produce during it integrates with IT technology, internal and external governance systems and different data values, and then, puts forward some countermeasures.

Cite this article

Xia Yikun . Analysis on the Connotation, Context and Main Issues of Government Data Governance[J]. Library and Information Service, 2018 , 62(9) : 21 -27 . DOI: 10.13266/j.issn.0252-3116.2018.09.003

References

[1] DAWES S S, HELBIG N. Information strategies for open government:challenges and prospects for deriving public value from government transparency[C]//WIMMER M A, CHAPPELET J L, JANSSEN M, et al. Electronic government EGOV 2010.Berlin:Springer, 2010:50-60.
[2] THOMPSON N, RAVINDRAN R, NICOSIA S. Government data does not mean data governance:lessons learned from a public sector application audit[J]. Government information quarterly,2015,32(3):316-322.
[3] 黄璜.美国联邦政府数据治理:政策与结构[J].中国行政管理,2017(8):47-56.
[4] PHANSE K. Data governance using SAP MDM[EB/OL].[2016-12-05].http://www.sdu.sap.com/irj/sdn/go/portal/prtroot/docs/library/uuid/600022998-5dd17-2b10-dbaa-8e3ab357fa55.
[5] KORHONEN J J, MELLERI I, HIEKKANEN K, et al. Designing data governance structure:an organizational perspective[J]. GSTF journal on computing,2013,2(4):11-19.
[6] DAMA International. The DAMA guide to the data management body of knowledge (DAMA-DMBOK)[M].USA:Technics Publications, LLC, 2009.
[7] FU X, WOJAK A, NEAGU D, et al. Data governance in predictive toxicology:a review[J]. Journal of cheminformatics, 2011,3(1):1-16.
[8] British Academy and the Royal Society. Data management and use:governance in the 21st century[R/OL].[2017-12-13].https://royalsociety.org/topics-policy/projects/data-governance/.
[9] BARRETT K, GREENE R.The causes, costs and consequences of bad government data[EB/OL].[2017-10-09].http://www.governing.com/topics/mgmt/gov-bad-data.html.
[10] GRUEN N, HOUGHTON J, TOOTH R. Open for business:how open data can help achieve the G20 growth targe[EB/OL].[2017-07-05]. http://www.omidyar.com/sites/default/files/file_archive/insights/ON%20Report_061114_FNL.pdf.
[11] State of the Union:data and analytics in government[EB/OL].[2017-08-20].http://coriniumintelligence.com/chiefdataofficergovernment.
[12] 摩根索.国家间政治[M].孙芳,译.北京:北京大学出版社,2005:156.
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