The results of a small-scale survey conducted for the Long Tail of Research Data Interest Group found that Dublin Core and DataCite metadata were the most common schemas used and less than half of the respondents were using DOIs. In terms of discovery, most respondents indicated that the metadata was sufficient for users to find the datasets when searching directly in the repository, however, the metadata may not support widespread discovery via search engines or dataset directories.
In Dublin, we discussed strategies to improve discovery of datasets and did some brainstorming about strategies to improving data discoverability. The following practices were mentioned:
- Linking data to related ublication
- Build an extra discovery layer that describes the data
- Link to or attach related Data Management Plans (DMPs) to the data
- DOIs or data citation
- Enable searching in repository to limit to datasets only
- Enable machine readability
- Improve quality and comprehensiveness of metadata (through researcher education or by repository staff)
- Have your repository be harvested by aggregators
I would like to collect some example of these practices, mainly the first three areas.
If you know of good examples, please let me know.
I will post them on the Interest Group website.
co-chair of RDA Interest Group Long Tail of Research Data
Executive Director, Confederation of Open Access Repositories