Summary and Examples of Practices for Improving the Discoverability of Research Datasets
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, participants in the Interest Group meeting on March 28, 2014 discussed how to improve discovery of datasets and did some brainstorming about strategies to improving data discoverability. These strategies are listed below along with brief description and link to examples provided by working group members.
Strategies fall into 6 categories (with quite a bit of overlap between these categories), which are linked to further pages that provide examples. Please feel free to add other examples. Also if you have other strategies that are not listed, please let me know and I can add them.
Please also see the slides from the Dublin meeting for further examples: https://rd-alliance.org/group/long-tail-research-data-ig/wiki/profiles-managing-long-tail-presentations-dublin-meeting-2014