EDCTP Data Sharing Toolkit

Regular updates
Category
  • Execute
  • Data management
  • Data sharing and secondary use

The EDCTP Data Sharing Toolkit provides end‑to‑end support for data sharing, from planning a data sharing strategy and clarifying consent language, through preparing anonymised datasets and documentation, to choosing and using an appropriate repository. It is aimed at investigators planning or conducting clinical studies with potentially sensitive information who need clear, operational guidance to move from raw study data to a curated dataset ready for repository deposit.

The landing page is organised into four clearly labelled sections:

  • Data Management Basics: core concepts for working with data, including free version control tools, metadata, file naming, documentation and examples of real‑world data problems in clinical data management.
  • Data Sharing Steps: key stages in depositing data in a repository, from organising and cleaning data, de‑identifying sensitive information and addressing copyright, consent and permissions, through to preparing documentation and submitting data, with practical examples and checklists.
  • Repository Finder: an interactive tool that asks a small number of questions about the study and suggests suitable candidate repositories for health research data, supporting repository selection and data deposit planning.
  • Resources: a large, curated collection of external materials (around 200 items) including guides, recorded seminars and e‑learning on FAIR principles, consent for data sharing, data de‑identification, metadata, data reuse and reproducibility.

Across these sections, the toolkit tackles common practical issues, such as choosing access models (open, controlled or closed), selecting trustworthy repositories, preparing appropriate metadata and documentation (for example README files and file inventories) and deciding which files to include with a data submission. It also links to guidance that aligns with EDCTP expectations on data management plans, data sharing and FAIR data under its funding policies.