IN ENGLISH!

Manage data

Research data is at the core of all scientific research. It comes in various forms (text, image, sound, video), media (paper, analog, digital), formats (notebooks, cassettes, files, structured databases, etc.), and types (raw, processed, and derived data). The idea of this guide is to provide you with some tips and point out some tools, softwares and human contacts to help you manage your research data, anticipate problems you might encounter and prevent a certain number of risks:

• 404 errors
• programmed obsolescence
• not understanding files left behind by a colleague
• getting stuck in files with nebulous names like "JD-1" "JD-2", initials of a colleague or interviewee, etc.
• not being able to access information because the physical medium has been destroyed
• losing belongings (randomly a USB stick with 10 years of work) in a move, fire, burglary, data theft, etc.
• being confronted with messages more along the lines of "oops, I can't open the file. The format is not supported"
• not being able to use a program because its manufacturer has gone bankrupt… and so much more.
  

How can you ensure the readability of your data over time, from one project to another? How do you satisfy the requirement of funders to provide a data management plan? How should you share your data so that your peers can best understand your research? In short, how do you maximize the impact of your work?

Manage your data according to the FAIR principles: have some flair

Follow the FAIR tips developed by the Force 11 collective, made up of people like you and me: researchers, teachers, librarians, engineers, archivists, publishers, research funders.

Romain Couturier/Cyril Heude
 

4 letters that will serve as your guide:

1. F for easy to find

  A unique, persistent identifier;

  Clearly named, organized and documented files and folders.

2. A for Accessible

  Stored on 2 reliable mediums, 1 of which is remote during the project;

  In a trustworthy dissemination repository;

  Archived in part at the end of the project;

  Focus on data mining and visualisation.

3. I for Interoperable

  Shared, discipline-specific metadata schemes;

  Known, open, documented, shared formats.

4. R for reusable

  Compliance with GDPR, Loi Lemaire and Intellectual Property Law ;

 Dissemination licenses authorizing re-use clearly affixed

  Data paper explaining the implications of the dataset drafted.
The proverb of the day always:

"As open as possible, as closed as necessary" Open in principle, but there are cases where this is not possible.