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，科学家通常处理来自不同领域的数据。在使用和分析数据时，科学家默认遵循这些领域设定的标准、流程和规则。然而，关于数据科学家及数据科学项目中其他参与角色的责任指导通常缺失。尽管文献表明，支持开放科学、数据重用和研究数据管理的新型框架和工具正在被提出，但目前尚无框架能完整表达数据科学项目的责任体系。本文描述透明度、问责制、隐私与社会责任矩阵（TAPS-RM）这一框架，用于探究数据科学项目的社会、法律与伦理层面。TAPS-RM作为工具，不仅为用户提供超越关键成果的项目全局视角，还明确了各方角色的责任。我们将TAPS-RM模型与开放数据领域的知名倡议（如FACT、FAIR及数据集数据手册）进行映射。结论表明，TAPS-RM是一种在数据科学项目层面反思责任的工具，可推动实现基于设计的负责任数据科学。