| Engineering Sector: | Wind Energy |
|
Community preferences: |
Matlab Python Catia Latex Solid-Works |
| Overall FAIRness: | ORANGE |
| F | No |
| A | Partially |
| I | Partially |
| R | Partially |
Overall FAIRness visualisation:
Context:
Understanding and controlling of aerodynamic flows, wind energy, and flight performance of e.g. aircraft’s is part of aerospace engineering research. Wind Energy data have an experimental nature and its volume changes over time: the raw data usually comes in several TB, doubles during the processing stage, and is condensed to hundreds of GB in the final stage. Although this research type does not handle sensitive or personal data, it is concerned with confidential data due to collaboration with industry and third parties. Non Disclosure Agreements play a major role in data dissemination and open access possibilities.
Insight:
The researchers in this case study, from the discipline of Aerodynamics, mainly make use of commercially available software to create raw data, apply autocat-based design software to process this data, and utilise commonly used visualisation software for the condensed and publication related data. Researchers in Aerodynamics usually only publish their data in relation to a publication, and find data created by others via project websites and publisher databases. With regards to re-usability / verification of work, it is the analysed data (as opposed to the raw data) that is most important for aerodynamics research. Overall, there is a positive attitude towards FAIR data and data publication, pointing out the need for more rewards for FAIR data publications.
Highlight:
In order to reuse the data, having all three stages of data (raw/processed/condensed) is a nice thing to have; however, NOT having the condensed brings troubles in verification of work with it.
Having the data connected to a peer-reviewed publication increases the trust-worthiness of the data.
