Reusing existing data sets for new research purposes is becoming more common across all research disciplines.
Research funders and publishers are asking researchers to make data sets produced in their projects available to others. And research institutes are promoting measures to secure the transparency and accessibility of locally produced data sets. To facilitate this, datasets need to be Findable, Accessible, Interoperable and Reusable.
This is what the FAIR principles are all about.
Susanna-Assunta Sansone: ”The FAIRer the data, the higher the return will be in terms of credit, in terms of citation, in terms of discovering your data.”
Barend Mons: “We need FAIR machine-readable data to cross disciplines, because there is a big problem to cross disciplines.”
Susanna-Assunta Sansone: “Be aware and be engaged, that’s what you can do now.”
Barend Mons: “Now we have papers – meant for people - and behind the paper wall there is supplementary data. We have to turn that around and publish the research objects in their own right”.
As Susanna-Assunta Sansone and Barend Mons have said, making your research data Findable, Accessible, Interoperable and Reusable could: