TAPS Responsibility Matrix: A tool for responsible data science by design

TL;DR

The paper introduces TAPS-RM, a comprehensive framework designed to clarify social, legal, and ethical responsibilities in data science projects, promoting responsible practices by design.

Contribution

It presents the TAPS-RM framework, a novel tool for mapping responsibilities and aligning with open data initiatives to enhance responsible data science.

Findings

TAPS-RM provides a holistic view of project responsibilities.

It aligns with initiatives like FACT, FAIR, and Datasheets.

The framework supports responsible data science by design.

Abstract

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.