What does this mean?
Identifiers and rich metadata descriptions alone will not ensure ‘findability’ on the internet. Perfectly good data resources may go unused simply because no one knows they exist. If the availability of a digital resource such as a dataset, service or repository is not known, then nobody (and no machine) can discover it. There are many ways in which digital resources can be made discoverable, including indexing. For example, Google sends out spiders that ‘read’ web pages and automatically index them, so they then become findable in the Google search box. This is great for most ordinary searchers, but for scholarly research data, we need to be more explicit about indexing. Principles F1-F3 will provide the core elements for fine-grained indexing by some current repositories and future services.
Examples
- The metadata of FAIR Datasets that are published on FAIR Data Points can be used for indexing by the DTL Search Engine.
- It may be that registries of FAIR datasets emerge over time by repositories or groups that have interest in specialised topical domains.
Links to Resources