Journal of Information Resources Management ›› 2024, Vol. 14 ›› Issue (2): 54-67.doi: 10.13365/j.jirm.2024.02.054

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Institute of Information Science, Shanghai Academy of Social Sciences, Shanghai, 200235

Zhang Zhun   

  1. Institute of Information Science, Shanghai Academy of Social Sciences, Shanghai, 200235
  • Online:2024-03-26 Published:2024-04-11
  • About author:Correspondence should be addressed to Zhang Zhun, Email: zhangzhun@sass.org.cn.
  • Supported by:
    This is an outcome of the project "Research on the Paradigm of Data Ownership Allocation in Urban Digitalization Transformation"(2021BTQ004) supported by Shanghai Philosophy and Social Sciences Foundation,and the Major Project "Research on the Theoretical Innovation and Practical Path from Government Information Disclosure to Open Data in China"(22&ZD329) supported by the National Foundation for Philosophy and Social Sciences.

Abstract: The guideline, which includes twenty key measures to build basic systems for data released in December 2022 (referred to as the "Twenty Data Measures"), proposes a structural separation system for data property rights, with "incentivizing data circulation" as its core focus. The rational allocation of the right to hold data resources affects the initial distribution of data benefits, serving as the foundation for achieving the strategic goal of "common use and shared benefits" of data. Under the traditional exclusive property rights mindset, the allocation patterns of the right to hold data resources may exacerbate conflicts of interest among data co-producers. This article suggests allocating the right to hold data resources among data co-producers in a "1+N" model, which means "prior hold data right for a specific data producer + access rights for N other data producers". With the support of tools such as technical governance and transparency governance, it explores a new, fair, and efficient data property rights system that aligns with the developing laws of the data economy.

Key words: The right to hold data resources, Data co-producer, Data property rights, Access right, Transparency

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