The wide use of schema.org to add structured metadata in web pages for use by commercial search engines has attracted the attention of the data management community as a possible mechanism to leverage the robust commercial search engines like Google, Yahoo, Bing etc. to facilitate discovery and access to scientific data. Various projects have been exploring this approach, including the US NSF EarthCube p418 projectGoogle's Dataset Recommendations, BioSchemas, Force11 DCIP, Research Data Australia, DataCite, Harvard Dataverse, NASA’s Distributed Active Archive Center (DAAC) Infrastructure, EOSCpilot, etc. Since schema.org has largely been driven by commercial business use cases, and a loosely governed process for adding and defining resource type, property and vocabulary for research domain, there are gaps and deficiencies that make its application for research data problematic.
Since P11, the RDA Data Discovery Paradigms IG started the task force "Using schema.org for research data discovery". The group has organised sessions at RDA plenaries and online calls to discuss how we research community come together to embrace the advantages of discovering data via web search engines, meanwhile to address gaps and deficiencies. There is a proposal to form a RDA Working Group with a focused scope and set of well-defined priorities/objectives.
The objectives of this work group are twofold:
- to identify and bridge gaps in existing schemas commonly used for research data, by bringing together communities who are working with such vocabularies to document research data and related resources;
- to provide guidelines for those communities whose needs are not addressed by existing metadata schema such as schema.org, and provide guidelines on proposing extensions.
The planned outputs will include:
A generic ‘conceptual data model’ with essential types and properties for research data discovery over the web. The model will be built on bioschemas.org, science-on-schema.org, schema.org, DCAT, DDI-DISCO and SSN schemas from some representative research domains, and data discovery use cases. A research domain can map their schema to the conceptual model when they publish data to the web or exchange metadata between data portals/repositories.
A guideline, illustrated with common patterns, of common patterns for publishing metadata landing pages with structured data markups; and a guideline of how to customise the research schemas for target domains with examples.
- Toolings for making the implementation easier if resources are available. This could include collecting and cataloguing tools that generate, validate and parse schema.org & DCAT markup, etc.
The WG was in maintenance mode in 2022.
Agendas and notes from previous group meetings are accessiable Here.