Mappings of DMP templates to TAPS Responsibility Matrix

The proliferation of digital data across various fields has contributed to an increase in data management practices. Data Management Plans (DMPs), as an important policy mechanism for responsible and ethical handling of data, are often structured as a set of questions that are intended to guide researchers in describing their data management practices. As data science evolves, several DMP templates and and frameworks have emerged to address the new complexities of data handling. However, there are still two main limitations with current DMP templates: 1) Lack of standardization: Several initiatives have improved alignment through shared core requirements and evaluation rubrics, but templates still vary in how they elicit responsibility and how clearly questions map to distinct responsibility components.We examined three widely-used DMP templates from the European Union (EU), the Data Curation Center (DCC), and the Dutch Research Council (NWO) using the TAPS (Transparency, Accountability, Privacy / Confidentiality, Societal values) Responsibility Matrix, a framework designed to address components of responsibility for data science. TAPS distinguishes between four main dimensions of responsibility (transparency, accountability, privacy and confidentiality, and social values) and their application to four main scopes ( actors, objects, processes and impacts). We mapped questions from the three DMP templates to the TAPS matrix to understand which aspects of responsibility are covered by the DMP templates.