FAIR & Open data | Flanders Marine Institute

Flanders Marine Institute

Platform for marine research

FAIR & Open data

Within the Flanders Marine Data Centre (VMDC) we aim at making our data Open and FAIR: we strive to make scientific data accessible to all and its dissemination transparent. FAIR stands for stands for Findable, Accessible, Interoperable, and Re-useable: the FAIR principles are about how research outputs can be organised so they can be more easily accessed, understood, exchanged and reused.  

What does it mean?

  • Findable: This means that digital objects (*) can be found easily because they are placed in a publically-accessible catalogue and are described with accurate and plentiful metadata  
  • Accessible: This means that the data systems that provide access to the (meta)data (catalogues, archives, data portals, etc.) are machine interoperable using standard protocols 
  • Interoperable: This means that the digital objects are standardised – for example, that your data files have non-propriatory file formats, that the data therein are organised in a clear and machine-accessible way, and that standard vocabularies are used so the meaning of everything is clear 
  • Reusable: The digitial objects have a licence indicating the conditions under which they can be used, and they include provenance information so it is clear how the they were created 

(*) A digital object: a dataset, a data file, a publication, a piece of software, a data-visualising tool, and even metadata themselves are all "digital objects".  


The FAIRness of data, publications, and software is becoming an increasingly important aspect of doing scientific research in Europe, and beyond. The FAIR principles are promoted to maximise the integrity and impact of the research carried out within institutes. It is already necessary that any funding proposal includes a data management plan that explains what will be done to ensure the outputs produced by the project are managed in a FAIR way, and these days all (European) data centres and data producers are also expected to strive to make their data, publications, and software FAIR.