Enabling global data discovery through structured data markup

Increasing amounts of open data are being made available through a growing number of data repositories. Consequently, it is becoming more challenging for researchers to find relevant data, especially where desired data is dispersed across several repositories. On the other hand, web search tools have almost become a de-facto information and data discovery tool for researchers. This workshop will address the above issue of how to make data discoverable through aggregated search via existing web architecture.

To enable broad discovery and access to research data, some data repositories have begun leveraging data discovery services from commercial search engines like Google, Yahoo, Bing etc., by embedding structured data markup in metadata landing pages using vocabularies such as schema.org, DCAT, and specific extensions. As more data repositories implement this approach, there arise new challenges:

• First, there is a lack of consistent implementation across data repositories, and guidelines for those who would like to pursue this path.
   
• Second, vocabulary adopted or indexed by major web search engines are intentionally minimalistic, there is no evaluation if this minimum set of vocabulary meets the needs for research data. If not, how we can extend it and get extensions accepted.
   
• Thirdly, and most importantly, how can the research data community take advantage of this strategy. For instance, explore new methods for metadata syndication and data discovery via the web architecture with a common set of vocabulary. The research data community can discuss and agree on what can be indexed, linked and build knowledge graphs for new data discovery applications; applications such as aggregated search across resources of a specific domain or related domains relevant to a research need, applications that can support a spectrum of data search needs from free text search, JSON API to SPARQL queries.

This workshop will bring together data repository managers, data managers, developers, and data technologists to exchange experience and lessons learnt from publishing metadata through structured data markup, as well as determining the advantages for this research data infrastructure community to use this data publishing trend.