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首页> 外文期刊>Data science journal >Rethinking Data Sharing and Human Participant Protection in Social Science Research: Applications from the Qualitative Realm
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Rethinking Data Sharing and Human Participant Protection in Social Science Research: Applications from the Qualitative Realm

机译：对社会科学研究中的数据共享和人类参与者保护的重新思考：质性领域的应用

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p class="p1"While data sharing is becoming increasingly common in quantitative social inquiry, qualitative data are rarely shared. One factor inhibiting data sharing is a concern about human participant protections and privacy. Protecting the confidentiality and safety of research participants is a concern for both quantitative and qualitative researchers, but it raises specific concerns within the epistemic context of qualitative research. Thus, the applicability of emerging protection models from the quantitative realm must be carefully evaluated for application to the qualitative realm. At the same time, qualitative scholars already employ a variety of strategies for human-participant protection implicitly or informally during the research process. In this practice paper, we assess available strategies for protecting human participants and how they can be deployed. We describe a spectrum of possible data management options, such as de-identification and applying access controls, including some already employed by the Qualitative Data Repository (QDR) in tandem with its pilot depositors. Throughout the discussion, we consider the tension between modifying data or restricting access to them, and retaining their analytic value. We argue that developing explicit guidelines for sharing qualitative data generated through interaction with humans will allow scholars to address privacy concerns and increase the secondary use of their data./p
机译：class =“ p1”>尽管数据共享在定量社会查询中变得越来越普遍，但定性数据却很少被共享。阻碍数据共享的一个因素是对人类参与者保护和隐私的关注。定量研究和定性研究者都需要保护研究参与者的机密性和安全性，但是在定性研究的认识论背景下，它却引起了特殊的关注。因此，必须仔细评估来自定量领域的新兴保护模型的适用性，以应用于定性领域。同时，定性学者已经在研究过程中采用了多种隐性或非正式地保护人类参与者的策略。在本实践文件中，我们评估了保护人类参与者的可用策略以及如何部署它们。我们描述了一系列可能的数据管理选项，例如取消标识和应用访问控制，其中包括定性数据存储库（QDR）已经与试点存储者一道使用的一些选项。在整个讨论中，我们考虑了修改数据或限制对它们的访问与保留其分析价值之间的紧张关系。我们认为，开发明确的准则以共享通过与人类互动而生成的定性数据的共享准则，将使学者们能够解决隐私问题并增加其数据的二次使用。

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