Use cases:

Support bioinformatician and data steward.

My background

My name is Christos Christou. I studied Molecular Biology at university as an undergraduate and went on to do PhD in Bioinformatics. I am interested in large scale high-throughput analysis of omics data and I have expertise in R and Python.

Main duties

• Data management support for departmental research staff, facilitating the publication of life science data in FAIR public repositories
• Data analysis support for departmental staff
• Development of data workflow
• Training of staff and students in data analysis and data management including writing DMPs

Common data problems I encounter

• What are the data retention policies for my country?
• Where can data be stored during the project? (considering size of data and who has access rights)
• Where should data be archived once the project is complete? (considering size of data and who has access rights)
• In which public respository should I deposit my data?
• What metadata and community standards (controlled vocabularies and ontologies) need to be captured to enable me to FAIR-publish in public repositories?
• How to I best capture those processes involved in creating and processing my data (workflow and analysis pipelines)?
• What DM tools should/could be used for the different stages during the RDM life cycle (including the management of metadata)?
• What are suitable compute resources for analysing my data?
• What DMP templates and tools could be used for my project?
• How do I know if my data is sensitive/personal and how would I work with data of this type?

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