According to good scientific practice, results of scientific research must be comprehensible, verifiable, and fully documented. This includes in particular the following aspects, which we convey in our training and consulting services:

• Consistent folder structures and file naming conventions
• Readme.txt files, recommended at the top folder level, as well as one per folder
• Comprehensible, detailed documentation of methods, materials and processes in accordance with the respective professional requirements/standards (e.g. in the form of laboratory books, etc.)
• In particular, comprehensive description of work processes/workflows
  • It is recommended to use data flow diagrams for illustration
  • as well as the provision of seamlessly traceable step sequences based on examples for the analysis / re-use of data
• Provision of source code of the employed software or (analysis) scripts
• Provision of suitable data formats (see file formats)
• Documentation of versions and changes of data (records) as implied in the terms Data Curation Profile, Data Lifecycles, or Audit Trails.
  • e.g. use of version management systems like git
• Documentation of used or developed metadata standards or vocabularies (see metadata standards)