Resource Description Framework Schema
Developed in Worldwide
Created in 1997
Scope and data types
How to cite this record FAIRsharing.org: RDFS; Resource Description Framework Schema; DOI: https://doi.org/10.25504/FAIRsharing.v9n3gk; Last edited: Sept. 2, 2018, 11:32 a.m.; Last accessed: Nov 19 2018 9:29 p.m.
Record updated: Sept. 2, 2018, 11:32 a.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.v9n3gk' by 'The FAIRsharing Team' at 11:32, 02 Sep 2018 (not approved): 'domains' has been modified: Before: Bioinformatics tools and formats Life Science After: Bioinformatics tools and formats Data standards Life Science Linguistic data Metadata standardization Ontology and terminology Added: Data standards Linguistic data Metadata standardization Ontology and terminology Removed: 'taxonomies' has been modified: Before: All After: Not applicable Added: Not applicable Removed: All 'miriam_id' has been modified: Before: None After: 'related_standards' has been modified: Before: Resource Description Framework Neuroimaging Data Model After: Resource Description Framework Neuroimaging Data Model Web Ontology Language Added: Web Ontology Language Removed:
Edits to 'https://fairsharing.org/FAIRsharing.v9n3gk' by 'The FAIRsharing Team' at 18:11, 19 Sep 2016 (approved): 'contactName' has been modified: Before: After: Dan Brickley Added: Removed:
No guidelines defined
No semantic standards defined
Models and Formats
No identifier schema standards defined
Integration, navigation, visualization, and analysis of gene interaction networks. This record has been marked as "Uncertain" because its homepage no longer exists. If you have any information on the current status of this resource, please contact us via the "Ask Question" button at the top of this page, or contact us through any of the methods described in the footer.
DisGeNET: a database of gene-disease associations
DisGeNET is a discovery platform containing one of the largest collections available of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models, and the scientific literature, and covers the whole landscape of human diseases. The current version (v4.0) contains 429,036 associations, between 17,381 genes and 15,093 diseases, disorders and clinical or abnormal human phenotypes, and 72,870 variant-disease associations between 46,589 SNPs and 6,356 diseases and phenotypes. The data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages, and an R package.
BioPortal is a Web portal that provides access to a library of biomedical ontologies and terminologies developed in Web Ontology Language (OWL), Resource Description Framework (RDF)(S), Open Biological and Biomedical Ontologies (OBO) format, and Protégé frames and Rich Release Format. BioPortal has a service-oriented architecture; the NCBO Web services provide the functionality found in BioPortal and these Web services can be incorporated into other software applications to access and use ontology content. BioPortal groups ontologies by domain to ease finding relevant ontologies and allows users to browse, search and visualize the content of ontologies. BioPortal also provides value-added features like ontology recommendation, text annotation, ontology mapping, and a reference index to resources like PubMed.
The AgroPortal project reuses the biomedical domain’s semantic tools and insights to serve agronomy, but also food, plant, agriculture and biodiversity sciences. We offer a portal that features ontology hosting, search, versioning, visualization, comment, and recommendation; enables semantic annotation; stores and exploits ontology alignments; and enables interoperation with the semantic web. The AgroPortal specifically satisfies requirements of the agronomy community in terms of ontology formats (e.g., SKOS vocabularies and trait dictionaries) and supported features (offering detailed metadata and advanced annotation capabilities). The AgroPortal content is automatically retrieved by FAIRsharing.org (https://fairsharing.org/) and the Agrisemantics Map of Data Standards (http://vest.agrisemantics.org/).
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This record is maintained by rafaelrichards
IBM, New York, NY, USA (Company)
Keio University (University)