数据正义的缺失及其治理优化路径研究

Research on the lack of Data Justice and its Governance Optimization Path

数据正义已成为大数据时代背景下竞相热议的话题,但相关研究目前仍处于起步阶段。首先,本文对数据正义内涵研究的历史进程进行了梳理,主要有“领域初探“”视域外延“”概念整合”三个阶段;其次,探讨了数据正义实现的阻碍因素,推演出了三类命题,力图厘清数据正义缺失之根由;最后,通过对数据正义缺失三大模块的校正得出通往数据正义的治理优化路径,为政府等数据主体克服数据正义缺失困境及实现数据正义提供了理论借鉴和实践参考。

Data Justice has become a hot topic in the era of big data,but the related research is still in its infancy.First of all,through the study of the historical process of data justice,there are three stages:“Field exploration”,“Horizon extension”,“Concept integration”;Secondly,it discusses the ob-stacles to the realization of data justice,deduces three kinds of propositions,and tries to clarify the rea-sons for the lack of data justice Finally,through correcting the three modules of data justice,we can get the optimal path to data justice,it provides a theoretical and practical reference for the government and other data subjects to overcome the dilemma of data justice and achieve data justice.