TAPS Responsibility matrix: a tool for responsible data science by design

Abstract

Data-science is an interdisciplinary research working on data from different fields. When analyzing these data, data scientists implicitly agree to follow the rules governing these fields. However, the responsibilities of the involved actors are not necessarily explicit. While novel frameworks supporting open-science are being proposed, there are currently no frameworks that focus on the responsibilities within 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 is a tool for providing a holistic view of a project beyond key outcomes and to clarify responsibilities of actors. We map TAPS-RM to well-known initiatives for open-data (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.

Keywords

• Responsible data science
• responsibility framework
• transparency
• privacy/confidentiality
• accountability
• societal values