Use this tool to make decisions about whether the data you are collecting or using meets the FAIR Principles.
When choosing data to reuse or creating your own datasets, keep in mind the FAIR Data principles which help to ensure that data is:
Findable
Step #1 in (re)using data is to find data. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets.
Accessible
Once the user finds the required data, they need the ability to retrieve the data to process and use the information. Is the data publicly available? Do users need to authenticate for access?
Interoperable
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
Reusable
The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.
