The FAIR(ER) Model is an extension of the well-known “FAIR Guiding Principles for scientific data management and stewardship.”
| Concept | Definition | Example |
|---|---|---|
| Findable | Researchers need to find your data to use it. | Globally unique and persistent identifier (e.g., DOI) |
| Accessible | Researchers use data that is clear and easy to obtain. | Use of accessible file formats (e.g., csv) |
| Interoperable | Researchers use data they (and their machines) can understand. | Consistent file naming and internal data formats |
| Reusable | Researchers can’t use a dead dataset. | Documentation of methods of collection and processing in a README file |
| Equitable | All researchers need to be able to use a dataset. | Use colorblind friendly graphics (e.g., symbols to distinguish groups, color vision deficiency palette) |
| Realistic | Researchers use data that connects back to real-world problems. | Publish raw datasets |