Privacy protection framework for open data: Constructing and assessing an effective approach

IF 2.4 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
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引用次数: 0

Abstract

Open data has revolutionized knowledge-sharing, providing economic and cultural benefits worldwide. However, releasing government, personal, or research data often raises concerns about data security and ethical implications, leading to infringements on privacy and related disputes. The Privacy Protection Framework for Open Data (PPFOD) is proposed to address these challenges. This framework aims to establish clear privacy protection measures and safeguard individuals' privacy rights. Existing privacy protection practices were examined using content analysis, and 36 indicators across five dimensions were developed and validated through an empirical study with 437 participants. The PPFOD offers comprehensive guidelines for data openness, empowering individuals to identify privacy risks, guiding businesses to ensure legal compliance and prevent data leaks, and assisting libraries and data institutions in implementing effective privacy education and training programs, fostering a more privacy-conscious and secure data era.

开放数据的隐私保护框架:构建和评估有效方法
开放数据彻底改变了知识共享,为全世界带来了经济和文化利益。然而,发布政府、个人或研究数据往往会引发对数据安全和道德影响的担忧,导致侵犯隐私和相关纠纷。为应对这些挑战,我们提出了开放数据隐私保护框架(PPFOD)。该框架旨在制定明确的隐私保护措施,保障个人的隐私权。我们利用内容分析法对现有的隐私保护实践进行了研究,制定了五个维度的 36 个指标,并通过对 437 名参与者的实证研究进行了验证。PPFOD 为数据开放提供了全面的指导方针,使个人有能力识别隐私风险,指导企业确保合法合规并防止数据泄露,同时协助图书馆和数据机构实施有效的隐私教育和培训计划,促进建立一个更具隐私意识和更安全的数据时代。
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来源期刊
Library & Information Science Research
Library & Information Science Research INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
4.60
自引率
6.90%
发文量
51
期刊介绍: Library & Information Science Research, a cross-disciplinary and refereed journal, focuses on the research process in library and information science as well as research findings and, where applicable, their practical applications and significance. All papers are subject to a double-blind reviewing process.
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