Including Co-Referent URIs in a SPARQL Query
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The document discusses the integration of co-referent URIs in SPARQL queries and explores the challenges of identity resolution within the Open PHACTS drug discovery platform. It analyzes the feasibility of employing a stand-off mapping service and compares different query expansion techniques. The findings suggest that while query expansion is generally slower, stand-off mappings are feasible, and the platform's infrastructure is capable of supporting complex query needs.
![Query Expansion
GRAPH <http://rdf.chemspider.com> {
cw:979b545d-f9a9 cheminf:logd ?logd .
?iri cheminf:logd ?logd .
FILTER (?iri = cw:979b545d-f9a9 ||
?iri = cs:2157 ||
cw:979b545d-f9a9, L
?iri = chembl:1280 || [cw:979b545d-f9a9, 1
cs:2157,
?iri = db:db00945 )
}
Q, L1
Q’
Query Expander
Service
chembl:1280,
db:db00945]
Identity
Mapping Service
(BridgeDB)
Can also be achieved through UNION
Mappings
Profiles
22/10/2013
COLD 2013
13](https://image.slidesharecdn.com/gray-co-ref-131021215712-phpapp01/85/Including-Co-Referent-URIs-in-a-SPARQL-Query-13-320.jpg)
Including Co-Referent URIs in a SPARQL Query
- 1. Including Co-referent URIs in a SPARQL Query Christian Y A Brenninkmeijer, Carole Goble, Alasdair J G Gray, Paul Groth, Antonis Loizou, and Steve Pettifer www.openphacts.org @open_phacts A.J.G.Gray@hw.ac.uk @gray_alasdair
- 2. Multiple Identities Andy Law's Third Law “The number of unique identifiers assigned to an individual is never less than the number of Institutions involved in the study” http://bioinformatics.roslin.ac.uk/lawslaws.html GB:29384 P12047 Are these the same thing? X31045 22/10/2013 COLD 2013 1
- 3. Gleevec® = Imatinib Mesylate Imatinib Imatinib Mesylate Mesylate YLMAHDNUQAMNNX-UHFFFAOYSA-N ChemSpider 22/10/2013 Drugbank COLD 2013 PubChem 2
- 6. Multiple Links: Different Reasons Link: skos:closeMatch Reason: non-salt form 22/10/2013 Link: skos:exactMatch Reason: drug name COLD 2013 6
- 7. Dynamic Equality Strict Relaxed Analysing Browsing skos:exactMatch (InChI) 22/10/2013 COLD 2013 7
- 8. Dynamic Equality Strict Relaxed Analysing Browsing skos:closeMatch (Drug Name) skos:exactMatch (InChI) skos:closeMatch (Drug Name) 22/10/2013 COLD 2013 8
- 9. Open PHACTS Discovery Platform Apps Interactive responses Method Calls Domain API Drug Discovery Platform Production quality integration platform 22/10/2013 COLD 2013 9
- 10. Integration Approach • • • • Data kept in original model Data cached in central triple store API call translated to SPARQL query Query expressed in terms of original data 22/10/2013 COLD 2013 10
- 11. OPS Discovery Platform Core Platform Apps Identity Resolution Service Identifier Management Service “Adenosine receptor 2a” Linked Data API (RDF/XML, TTL, JSON) P12374 EC2.43.4 CS4532 Domain Specific Services Semantic Workflow Engine Chemistry Registration Normalisatio n & Q/C Data Cache (Virtuoso Triple Store) Indexing VoID VoID VoID Nanopub Public Ontologies Db Db 22/10/2013 VoID Nanopub Db Nanopub Db COLD 2013 Public Content VoID Commercial User Annotations 11
- 12. Platform Interaction 1. Resolve user input: – User enters search text – Resolve to a URI for concept 2. Request data for URI – Expand URI to equivalent for each dataset – Run resulting SPARQL query 22/10/2013 COLD 2013 12
- 13. Query Expansion GRAPH <http://rdf.chemspider.com> { cw:979b545d-f9a9 cheminf:logd ?logd . ?iri cheminf:logd ?logd . FILTER (?iri = cw:979b545d-f9a9 || ?iri = cs:2157 || cw:979b545d-f9a9, L ?iri = chembl:1280 || [cw:979b545d-f9a9, 1 cs:2157, ?iri = db:db00945 ) } Q, L1 Q’ Query Expander Service chembl:1280, db:db00945] Identity Mapping Service (BridgeDB) Can also be achieved through UNION Mappings Profiles 22/10/2013 COLD 2013 13
- 14. Experiment Is it feasible to use a stand-off mapping service? • Base lines (no external call): – “Perfect” URIs – Linked data querying • Expansion approaches (external service call): – FILTER by Graph – UNION by Graph 22/10/2013 COLD 2013 14
- 15. “Perfect” URI Baseline WHERE { GRAPH <chemspider> { cs:2157 cheminf:logp ?logp . } GRAPH <chembl> { chembl_mol:m1280 cheminf:mw ?mw . } } 22/10/2013 COLD 2013 15
- 16. Linked Data Baseline WHERE { GRAPH <chemspider> { cs:2157 cheminf:logp ?logp . } GRAPH <chembl> { ?chemblid cheminf:mw ?mw . } cs:2157 skos:exactMatch ?chemblid . } 22/10/2013 COLD 2013 16
- 17. Queries Drawn from Open PHACTS API: 1. Simple compound information (1) 2. Compound information (1) 3. Compound pharmacology (M) 4. Simple target information (1) 5. Target information (1) 6. Target pharmacology (M) 22/10/2013 COLD 2013 17
- 18. Queries Drawn from Open PHACTS API: 1. Simple compound information (1) 2. Compound information (1) 3. Compound pharmacology (M) 4. Simple target information (1) 5. Target information (1) 6. Target pharmacology (M) 22/10/2013 COLD 2013 18
- 19. Datasets and Links Data: 167,783,592 triples 22/10/2013 Mappings: 2,114,584 triples COLD 2013 Lenses: 1 19
- 20. Average execution times 22/10/2013 COLD 2013 20
- 21. 0.018 Average execution times 22/10/2013 COLD 2013 21
- 23. Conclusions • Query expansion slower in general – Due to separate service call – Difference below human perception – UNION faster than FILTER on Virtuoso • Stand-off mappings feasible • Infrastructure can support lenses Strict Relaxed Analysing Browsing 22/10/2013 COLD 2013 29
Editor's Notes
- #2: Each captures a subtly different view of the worldAre they the same? … depends on your point of view
- #3: Example drug:Gleevec Cancer drug for leukemiaLookup in three popular public chemical databasesDifferent resultsData is messy!
- #4: Enter with ChemSpider URI forImatinibThis is not Gleevec
- #7: sameAs != sameAs depends on your point of viewLinks relate individual data instances: source, target, predicate, reason.Links are grouped into Linksets which have VoID header providing provenance and justification for the link.
- #10: A platform for integratedpharmacology data Reliedupon by pharma companiesPublic domain, commercial, and private data sourcesProvidesdomainspecific APIMakingiteasyto build multiple drugdiscoveryapplications:examplesdeveloped in the project
- #11: Step 2 requires expansion of URI to cover those used in data setsPerformed by query expansion service and IMS
- #12: Import data into cacheDomain specific APIAPI calls populate SPARQL queriesQueries expanded by IMS to cover URIs of original datasets
- #13: Step 2 requires expansion of URI to cover those used in data setsPerformed by query expansion service and IMS
- #14: Query with URIsExtract URIsFind equivalentsExpand queryOptimise based on context
- #18: Result size in brackets
- #19: Result size in brackets
- #20: Subset of the OPS data
- #21: Linked data approach performs badly with query 6 due to the query constructionName being bound to the chemical structure returned
- #22: Focus on other queriesIn general expansion is slower than base linesWorst case delta: 0.01842 (under 20ms)Human perception is 0.050 to 0.2
- #29: Focus on query 6No linked data as it performed very poorly on this querySize of result obliterates external call cost