Advancing Biomedical Data Science Careers

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About this Repository

This repository is created for the Advancing Biomedical Data Science Careers (ABDC) project, funded by the Medical Research Council and jointly led by The Alan Turing Institute and EMBL-EBI.

Vision and Mission

• Vision: Documenting skills, roles and team science approaches to foster the recognition and advancement of data science careers in biomedical research.
• Mission: By engaging with a wide range of stakeholders, including universities, research institutes, government departments, healthcare providers, and health-related industry organisations in biomedical data science and beyond, this project aims to empower cross-domain collaboration, enabling team science approaches to shape the future of biomedical research.

About

Data and data science are transforming the world and data science expertise is in extremely high demand. As highlighted in the recent MRC Strategic Review (2022), there is an urgent need in biomedical research for a shared framework of data science careers — one that enables skills mobility and recognises the value of biomedical data science roles and team-based approaches across different settings. To address this gap, the ABDC project was established as a collaboration between two global leaders in biomedical data science — The Alan Turing Institute and EMBL’s European Bioinformatics Institute (EMBL-EBI). Drawing on our extensive experience and working in partnership with a diverse network of existing and new collaborators, this project will deliver outputs that help organisations embed data science expertise into their teams, while fostering a shared understanding of the language, skills, and career pathways essential to this evolving field.

Roadmap & Milestones

Goals: - To evaluate skills gaps and identify priority areas for developing knowledge, skills and behaviours across the biomedical data science ecosystem. - To better understand roles, career pathways and team science approaches within the biomedical data science community and how these can improve access, resourcing and career offers. - To evaluate and recommend innovative approaches and ways of working that will drive forward capacity building and improve quality and standards in biomedical data science.

Outcomes: - WP1 - Skill requirements evaluation. We will describe and evaluate the data competencies and training landscape, which is an initial fundamental step to advance biomedical data science careers, by finding, analysing and mapping relevant existing competency frameworks and professional standards. - WP2 - Understanding roles & career pathways. We will document examples of successful implementation of diverse data science roles and teams across different types and scales of organisations. Through workshops, interviews and surveys, we will document these examples at three levels: 1) how these roles and teams are established and implemented at an organisational level to better understand resourcing and advocacy for new roles; 2) how collaborative team science has been successfully approached and managed in teams; 3) career pathway examples at an individual level to foster a diverse set of role models that have successfully navigated this space. - WP3 - Recommendations to fill the gaps. Drawing on the information collected in WP1 and 2, we will recommend innovative and equitable approaches to increase the inclusion, quality and recognition of data science within biomedical research.

The Team

• Emma Karoune, Project lead - The Alan Turing Institute
• Vera Matser, Project co-lead - The Alan Turing Institute
• Catherine Brooksbank, Project co-lead EMBL-EBI
• Kim Gurwitz, Project co-lead - EMBL-EBI
• Ali Marsh, Project Manager - The Alan Turing Institute
• Denise Bianco, Senior Research Community Manager - The Alan Turing Institute
• Daria Sokolova, Scientific Project Officer - EMBL-EBI
• Giulia Tomba, Daphne Jackson Fellow - The Alan Turing Institute

Acknowledgement

• This repository uses the template created and maintained by The Turing Way team members and shared under CC-BY 4.0 for reuse: https://github.com/alan-turing-institute/reproducible-project-template.

Contact

• Reach Out: For any project-related queries or concerns, you can directly reach out to team by emailing advancing-biomed-data-sci-careers@turing.ac.uk