- How research data management (RDM) principles can be effectively applied and maintained when working with large and complex datasets.
- How to make RDM as transparent and painless as possible.
- How to deliver hands-on training in a way that is grounded in people’s existing research practice.
During my postgraduate studies in human neuroimaging and postdoctoral career in biological psychiatry in the University of Edinburgh, I have worked extensively with different types of data, including health records, imaging, genetic sequencing, clinical, and behavioural data.
My current role is Research Data Manager for the MRC Institute of Genetics and Cancer at the University of Edinburgh. I work directly with genetic data and support research in a wide range of disciplines including population genetics, disease mechanisms and precision medicine. The institute’s research utilises a variety of data types including genetic and RNA sequencing, imaging, spectroscopy, human, animal and synthetic. Furthermore, I deliver training on good research practices and am always looking for ways to improve our way of working with data.