Research generates significant amounts of data that are used to communicate the results of a particular investigation. However, currently, these data are usually unstructured and highly scattered. As a result, this data can not be used to verify, replicate or reanalyze the findings. Moreover, different standards, annotation practices and data formats for data and metadata (if available) might have been used by other researchers, introducing additional heterogeneity and difficulties in later data integration and interpretation. The use of standards for data management increases the reproducibility and replicability of the results. This is achieved through an appropriate Data Management Plan (DMP) and adherence to FAIR principles that ensure that data can be findable, accessible, interoperable and reusable.