Introduction to Open Science and FAIR principles

  • Open Science increases transparency in research
  • Publicly funded science should be publicly available
  • FAIR stands for Findable Accessible Interoperable Reusable
  • FAIR assures easy reuse of data underlying scientific findings

Introduction to metadata

  • Metadata provides contextual information so that other people can understand the data.
  • Metadata is key for data reuse and complying with FAIR guidelines.
  • Metadata should be added incrementally through out the project

Tidy (meta)data tables

Working with files

  • A good file name suggests the file content
  • Good project organization saves you time
  • Describe your files organization in PROJECT_STRUCTURE or README including naming convention

Reusable analysis

  • Jupyter Notebooks are useful tools to share analysis with non-programmers
  • One single document can visualise background, results, formulae/code and metadata
  • One single document helps to make your work more understandable, repeatable and shareable

Public repositories

  • Repositories are the main means for sharing research data.
  • You should use data-type specific repository whenever possible.
  • Repositories are the key players in data reuse.

Journey to be FAIR

  • There are simple steps to help make your data more FAIR throughout the research data lifecycle
  • Implement these steps throughout to keep track of your data and changes