{"doi":"10.7490/f1000research.1113119.1","title":"Bioschemas: structured data for life science using schema.org","abstract":"<ns3:p>ELIXIR explicitly supports the FAIR Principles – Findable, Accessible, Interoperable, Reusable – for its data, software, tools, events and training resources. “Finding” has the significant challenge of effective discovery and indexing of web-based resources across all ELIXIR information providers – this is an issue because there has been no agreement within ELIXIR about how to expose such resources in order to make them discoverable. One solution to this problem is to adopt Schema.org mark-up. Schema.org is a community initiative supported by four major search-engine providers: Google, Bing, Yahoo and Yandex. It provides a simple way to publish data in a standard format. If websites publishing life-science training materials, data, tools, profiles etc. were to use Schema.org mark-up, then their websites could be crawled, and the data could be indexed and exposed in searchable portals. However, this approach has challenges. Bioschemas is a newly formed community group in the life sciences to address these challenges, aiming to make the adoption of Schema.org part of a powerful way to discover and collect life-science information. It produces specifications, one for each information type (‘Training Course’, ‘Event’, 'Sample Data', 'Ontology Term', 'Tool', etc.). Each specification lists the Schema.org minimum properties expected, and the constraints for each property: for example, the ‘Events’ specification that the property ‘topic’ should be an EDAM ontology topic. The specifications are developed openly and are available on GitHub, with the support of existing communities of domain experts. Bioschemas also identifies the types or properties that are needed in the life sciences but not present in Schema.org, and works with the community to encourage the adoption of these types and properties into Schema.org.</ns3:p>","journal":"Faculty of 1000 Research Ltd","year":2016,"id":5560,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0457,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2016-09-12","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":2538,"name":"Mélanie Courtot","orcid":"0000-0002-9551-6370","position":1,"is_corresponding":false},{"id":595,"name":"Rafael C. 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