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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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