Data science is an interdisciplinary research area where scientists are typically working with data coming from different fields. When using and analyzing data, the scientists implicitly agree to follow standards, procedures, and rules set in these fields. However, guidance on the responsibilities of the data scientists and the other involved actors in a data science project is typically missing. While literature shows that novel frameworks and tools are being proposed in support of open-science, data reuse, and research data management, there are currently no frameworks that can fully express responsibilities of a data science project. In this paper, we describe the Transparency, Accountability, Privacy, and Societal Responsibility Matrix (TAPS-RM) as framework to explore social, legal, and ethical aspects of data science projects. TAPS-RM acts as a tool to provide users with a holistic view of their project beyond key outcomes and clarifies the responsibilities of actors. We map the developed model of TAPS-RM with well-known initiatives for open data (such as FACT, FAIR and Datasheets for datasets). We conclude that TAPS-RM is a tool to reflect on responsibilities at a data science project level and can be used to advance responsible data science by design.
翻译:数据科学是一个跨学科研究领域,科学家们通常与不同领域的数据合作;在使用和分析数据时,科学家们隐含地同意遵守这些领域制定的标准、程序和规则;然而,数据科学项目中数据科学家和其他参与者的责任指导通常缺乏;虽然文献表明,为支持开放科学、数据再利用和研究数据管理,正在提出新的框架和工具,但目前没有任何框架能够充分表达数据科学项目的责任;在本文件中,我们将透明度、问责制、隐私和社会责任矩阵(TAPS-RM)描述为探索数据科学项目的社会、法律和道德方面的框架;TAPS-RM作为工具,向用户提供超越关键结果的对其项目的全面看法,并澄清行为者的责任;我们用众所周知的开放数据倡议(如FACT、FAIR和数据集数据表)绘制了TAPS-RM模型,我们的结论是,TAPS-RM是反映数据科学项目一级责任的工具,可以用来推动负责任的科学设计。