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数据伦理政策的量化研究:基于天文领域的数据管理办法 被引量:7

Quantitative Research on Data Ethics Policy:A Data Management Approach Based on Astronomy
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摘要 我国数字经济已进入自主创新阶段,如何引领开放,消除数字壁垒,值得学术界的广泛研究。数据政策中蕴含了相对固定的伦理规则,在指导科研人员如何有效开放、管理数据方面起着重要作用,挖掘数据政策有助指导图书馆开展数据管理服务。利用量化分析方法,分析71份政策文件的发布主体、伦理规则及伦理主题关系,发现天文数据管理是以科学社群牵头,通过群体层面的伦理要求,作用个体层面的伦理纽带,反向影响群体层面的伦理作用;其中阶段式释放、角色式优先、合作式获取、责任式共享、尊重式使用及发扬式开放为关注的伦理主题。 China’s digital economy has entered the stage of independent innovation.How to lead the open and eliminate digital barriers is worth extensive research in the academic community.Data policies contain relatively constant ethical rules,which plays an important role in guiding researchers on how to effectively open and manage data.Mining data policies can help guiding libraries to develop data management services.With quantitative analysis,this paper analyzed the relationship between the issuing subject,ethical rules and ethical themes of 71 policy documents.It is found that scientific community has played a leading role in astronomical data management,and the ethical requirements at the group level has acted as the ethical bond at the individual level,while influenced the ethical role reversely at the group level.Phasing release,role-style priority,cooperative acquisition,responsible sharing,respectful use and open for developing are concerned themes in Astronomy.
作者 刘金亚 谌悦 章成志 陈新兰 顾立平 Liu Jinya;Chen Yue;Zhang Chengzhi;Chen Xinlan;Gu Liping(National Science Library,Chinese Academy of Sciences,Beijing,100190;Department of Library,Information and Archives Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing,100190;The National Astronomical Observatories of the Chinese Academy of Sciences,Beijing,100012;Department of Information Management,School of Economics and Management,Nanjing University of Science and Technology,Nanjing,210094)
出处 《信息资源管理学报》 CSSCI 2021年第6期63-75,共13页 Journal of Information Resources Management
关键词 政策文本挖掘 数据政策 数据伦理 数据开放 数据管理 量化分析 Policy Text Mining Data Policy Data Ethics Data openness Data management Quantitative Analysis
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