TAPS Responsibility Matrix

• DOI: 10.48550/arxiv.2302.01041
• Publication Date: 2024-12-02
• Authors: Visara Urovi; Remzi Celebi; Chang Sun; Parveen Kumar; Linda Rieswijk; Michael Erard; Arif Yilmaz; Kody Moodley; Michel Dumontier
• Keywords: transparency; Technological innovations. Automation; FOS: Computer and information sciences; Computer Science - Artificial Intelligence; responsibility framework; HD45-45.2; 02 engineering and technology; Responsible data science; I.2.1; privacy/confidentiality; Computer Science - Computers and Society; societal values; Artificial Intelligence (cs.AI); accountability; Computers and Society (cs.CY); 0202 electrical engineering, electronic engineering, information engineering

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.