In Switzerland, Norway, and France (and…?) the national funding agencies now require a data management plan to be submitted with the grant, and extra money is set aside for implementing this, following the FAIR principles. The hope and idea is, that including a description of the data analysis plan at this early point could lead to the development of better habits in this regard.
Data description of the way the data were processed  Use case for reusability -> show how it can be used in public directory. Funding agency for now only interested the data description and the sustainability. Be part of the data management plan. DMPs referring tools. and then used as metadata. Software management plan? Where to put your metadata (routine production of software)-> referred this method as part of the policies of funding. We provide the place for storing and exposing this metdadata
Metadata more interpretable with biii
Data provenance: workflow engine -> metadata needed on the processing in the standard way
https://www.dtls.nl/fair-data/fair-principles-explained/
- Build a network of developers/scientists working in similar fields / sharing same bioimaging interests
- Filters tools producing / consuming a specific type of data in a given topic (EDAM)
- Suggest a tool that can pre-process or post-process a given data format or type (EDAM)
- Extract some metrics (sorted counts) based on EDAM terms
Figure graph = new result= example two fields are using the same tools; Are we reinventing the wheel?? Starting to be coherent filament tracing