Spotlight on: Paula Ramos-Silva
Every other week, the Thematic DCCs and the Data Steward Interest Group (DSIG) put the spotlight on one research data steward working in the Netherlands to stimulate knowledge exchange and peer-to-peer learning.
What drew you towards the research data management field?
As a researcher, I really enjoyed the simple act of managing data, especially large amounts of it. When I first read about the concepts of reusable and open data, they immediately resonated with me. I wanted to learn more and apply these principles in practice to share and increase the impact of my work. I also appreciate things that are tidy, organized, and clear. Becoming a data steward felt like a natural next step in my career.
What is an activity/task of your role that you find yourself looking forward to?
I always look forward to the next teaching session in my agenda. I enjoy teaching and learning together with the participants as we explore their data challenges. I also have fun designing new courses and workshops, especially hands‑on ones.
What is something unexpected that you can offer help with, if a colleague reaches out to you?
I still have a strong foundation in molecular biology, evolutionary biology, and bioinformatics - library preparations, NGS sequencing workflows, and plenty of other techniques. These skills aren’t part of my daily work anymore, but they can be surprisingly handy.
What do you think your community of research data professionals is missing?
The data stewardship community in the Netherlands is quite solid, with active networks and collaborations between peers. Institution‑wise, however, I think there is room for greater recognition of our work and more visibility for the training and support services we provide.
What is a topic you would want to collaborate on with others?
Reproducibility and Replicability remain key challenges, and they are areas where I would like to collaborate more with others and exchange ideas. How do we promote and implement these two R’s as standard practice across domains? And how do we make them achievable when working with sensitive data?
Could you point us to a resource, learning platform, tool or similar which you find useful or inspirational?
Galaxy Training never ceases to inspire me. They have excellent hands‑on tutorials on FAIR data management: https://galaxyproject.github.io/training-material/topics/fair/#fair-data-workflows-and-research.
Get in touch with Paula Ramos-Silva on: ORCID
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