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Do good: strategies for leading an inclusive collaborative data science and RSE teams

Year: 2024

Type: article

Abstract: Leading a collaborative data science or research software engineering (RSE) team in an academic environment can have many challenges including institutional infrastructure, funding, and technical expertise. Even in the most challenging environment, however, leading such a team with inclusive practices can be rewarding for the leader, the team members, and collaborators. We describe nine leadership and management practices that are especially relevant to the dynamics of such teams and an academic environment: ensuring people get credit, making tacit knowledge explicit, establishing clear performance review processes, championing career development, empowering team members to work autonomously, learning from diverse experiences, supporting team members in navigating power dynamics, having difficult conversations, and developing foundational management skills. Active engagement in these areas will help those who lead data science or RSE groups – whether faculty or staff, regardless of title – create and support inclusive teams.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.13942632

Authors: Maimone, Christina, Sharp, Julia, Schwartz-Soicher, Ofira, Beltran, Lencia, Oliver, Jeffrey

Institutions: Northwestern University, National Institute of Standards and Technology, Princeton University, Cornell University, University of Arizona

Language: English

Topic: Software Engineering Techniques and Practices

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6892927232

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