NCBO SPARQL Endpoint
•Transferir como PPT, PDF•
0 gostou•458 visualizações
Tutorial from ICBO 2013.
Recomendados
Mais conteúdo relacionado
Mais procurados
Mais procurados (20)
Semelhante a NCBO SPARQL Endpoint
Semelhante a NCBO SPARQL Endpoint (20)
Mais de Trish Whetzel
Mais de Trish Whetzel (20)
Último
Último (20)
NCBO SPARQL Endpoint
- 1. NCBO SPARQL Endpoint Trish Whetzel Outreach Coordinator THE NATIONAL CENTER FOR BIOMEDICAL ONTOLOGY
- 3. BioPortal SPARQL Content • All ontologies from BioPortal – Original ontology format (OBO, OWL, UMLS/RRF) transformed into RDF – Updated daily – Latest version only • Statistics – 393 ontologies – 4.2M terms – 2419 different predicates – 80M triples
- 4. Resource Description Framework – A collection of RDF statements represents a labeled, directed multi-graph – RDF is modeled as a set of triples – Triples are in the form (subject, predicate, object) where: • Subjects and predicates are URIs • Objects are either URIs or Literals • Literals can be typed and have a language tag – Blank nodes (bnodes) or anonymous resources are nodes that do not have a URI or literal – RDF is not XML, there are different serializations, e.g. N3, turtle, rdf/xml
- 5. RDF – Turtle format – Prefixes are allowed and statements can be grouped by subject – Specific constructions to represent lists and blank nodes – Least verbose and best human readable format, easy to serialize and good performance for parsing
- 6. RDF – N3 format – One line per triple, no prefixes, not grouped by subject – More verbose, easy to serialize, best performance for parsing
- 7. RDF – RDF/XML format – Extremely verbose, worst human readable format – Worst performance for parsing
- 8. SPARQL – W3C standard query language for RDF – Structure
- 9. BioPortal Metadata • Virtual ontology identifier – Stable identifier across all versions of the ontology – All versions of an ontology are linked via this ID • Ontology version identifier – Unique for each ontology version – Most metadata linked directly to the ontology version
- 13. All ontologies updated since DATE
- 14. Find term in all ontologies
- 15. Select all terms from the ABA Adult Mouse Anatomy
- 16. Select URI and preferred label from all terms
- 17. Get parent of given term
- 18. Select all terms and their parent
- 20. Select properties for term
- 21. Count terms in SNOMED
- 22. Performance Tips and Tricks – Completely unbound patterns (?g ?s ?p ?o) are not allowed – To optimize queries, use UNIONS instead of FILTERS – If using FILTER on literals it is better if the filter is not applied to millions of rows – To prevent combinatorial explosions of results, consider use CONSTRUCT or DESCRIBE (any M-N relationship can provoke this)
- 23. SPARQL Code Repository • https://github.com/ncbo/sparql-code-examples
- 24. BioPortal SPARQL Endpoint • Documentation: http://www.bioontology.org/wiki/index.php/SPA RQL_BioPortal • Query interface: http://sparql.bioontology.org/ • Example queries: http://sparql.bioontology.org/examples • Sample code: https://github.com/ncbo/sparql-code- examples
Notas do Editor
- Multi-graph – edges that have the same end nodes
- We can use an unbound GRAPH to find in which ontology a pattern is satisfied.
- Our backend has subPropertyOf reasoning to help to retrieve preferable labels, synomyns and definitions. Use skos:prefLabel for preferable labels, skos:altLabel for synonyms and skos:definition for definitions.
- One can think of optional as a left outer join. The pattern in the optional will be matched if possible or empty slot will be returned.
- Our backend relies on predicate indexing mostly. and most likely queries with unbound ?p will run slow.