东北大学学报(社会科学版) ›› 2020, Vol. 22 ›› Issue (3): 56-63.DOI: 10.15936/j.cnki.1008-3758.2020.03.008

• 政治与公共管理研究 • 上一篇    下一篇

数据生命周期视角下政府跨域协作数据治理及其运行逻辑

李月,曹海军   

  1. (东北大学文法学院,辽宁沈阳110169)
  • 收稿日期:2019-10-16 修回日期:2019-10-16 出版日期:2020-05-25 发布日期:2020-05-25
  • 通讯作者: 李月
  • 作者简介:李月(1991-),女,辽宁铁岭人,东北大学讲师,管理学博士,主要从事电子政务与数据治理研究;曹海军(1975-),男,吉林长春人,东北大学教授,博士生导师,主要从事网络社会治理研究。
  • 基金资助:
    辽宁省社会科学规划基金青年资助项目(L19CZZ001)。

Data Governance and Its Logic in Government Cross-boundary Collaboration from the Perspective of Data Lifecycle

LI Yue, CAO Hai-jun   

  1. (School of Humanities & Law, Northeastern University, Shenyang 110169, China)
  • Received:2019-10-16 Revised:2019-10-16 Online:2020-05-25 Published:2020-05-25
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摘要: 数字政府时代, 高效的数据治理是实现政府跨域协作、解决复杂棘手问题的重要工具。 以数据生命周期理论为视角分析发现, 在政府跨域协作场景下, 数据需求的满足过程与主体内部数据生命周期之间产生矛盾, 使数据规划阶段的前置治理失效,数据采集与处理成本增加, 最终导致数据利用阶段的供给迟滞。 为确保跨域协作中数据的自由流动、全局一致以及安全可靠, 应突破个体层次的数据生命周期模型, 转向面向协作整体的跨域协作数据生命周期治理逻辑,通过数据规划、数据汇聚、数据联通、数据利用以及数据增值五个阶段, 完成数据价值的实现与增长。

关键词: 数据治理, 政府跨域协作, 数据生命周期, 治理逻辑

Abstract: Efficient data governance is of great significance in supporting government cross-boundary collaboration and solving wicked problems. The data lifecycle perspective is used to analyze the data governance problem in the cross-boundary collaboration scenario. It is found that a conflict between the process of providing data and the internal data lifecycle of the subject has rendered the pre-governance of the data planning stage ineffective, caused the cost of data collection and processing to increase, and ultimately led to the supply lag in the data application phase. In order to ensure the free flow, global consistency, security and reliability of data in cross-boundary collaboration, it is proposed to break through the data lifecycle model at individual levels, turn to cross-boundary collaboration-oriented data lifecycle governance logic, and complete the realization and growth of data value through the five phases of data planning, data aggregation, data connectivity, data application, and data exploitation.

Key words: data governance, government cross-boundary collaboration, data lifecycle, governance logic

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