Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

Like this? Share it with your network

Share

Mapping Lo Dto Proton Revised [Compatibility Mode]

on

  • 1,531 views

Presentation at the Ontology Matching Workshop held at ISWC\'2010

Presentation at the Ontology Matching Workshop held at ISWC\'2010

Statistics

Views

Total Views
1,531
Views on SlideShare
1,529
Embed Views
2

Actions

Likes
0
Downloads
9
Comments
0

1 Embed 2

http://www.linkedin.com 2

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Mapping Lo Dto Proton Revised [Compatibility Mode] Presentation Transcript

  • 1. Mapping the Central LOD Ontologies to PROTON Upper- Level Ontology Mariana Damova, Atanas Kiryakov, Kiril Simov, Svetoslav Petrov ISWC’2010
  • 2. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 3. Linking Open Data (LOD) FactForge (http://factforge.net) • a reason-able view of the web of data • the biggest and most heterogeneous body of factual knowledge on which inference is performed • 8 datasets from the LOD cloud (DBPedia, Freebase, UMBEL, CIA World Factbook, MusicBrainz, Wordnet, Lingvoj, Geonames) • an overall of 1,4 billion loaded statements • 2,2 billion stored statements (indexed) • 9,8 billion distinct retrievable statements
  • 4. Access to FactForge Forest Interface - keyword search (for molecules in the RDF graph) - auto-suggestion of URI - SPARQL queries using facts from different datasets (formulating SPARQL queries requires in depth knowledge about the datasets and the schemata in FactForge) - exploration
  • 5. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 6. Current State SELECT * WHERE { ?Person dbp-ont:birthPlace ?BirthPlace ; rdf:type opencyc:Entertainer ; ?BirthPlace geo-ont:parentFeature dbpedia:Germany . } Target State SELECT * WHERE { ?Person prot:birthPlace ?BirthPlace ; rdf:type prot:Entertainer ; ?BirthPlace prot:subRegionOf dbpedia:Germany . }
  • 7. Benefit easier and simpler access to the wealth of data (one needs to know a single ontology instead of learning the vocabularies of multiple datasets) higher degree of interoperability offering only one single schema better integration of the datasets in FactForge (so the schemata of the different datasets are mapped through a single ontology) information from many datasets via a unified vocabulary (a constraint which uses a single predicate from the ontology can match data from different datasets)
  • 8. Applications semantic search and annotation using the entities from FactForge semantic browsing and navigation querying FactForge in natural language many others
  • 9. Solution DBPedia Freebase Geonames PROTON PROTON - a modular, lightweight, upper-level ontology defining about 300 classes and 100 properties DBPedia - the RDFized version of Wikipedia, data-driven ontology, an overall of 592 classes and 720 properties, and about 1 478 000 instances Freebase - a social database, no ontology, hidden class hierarchy in structured predicate names, 19632 predicates Geonames – a geographical database that covers 6 million geographical features with ontology of 5 classes, and 26 properties, and about 645 location denotators
  • 10. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 11. Approaches to Matching Ontologies • syntactic vs. semantic mapping • harmonizing semantics (interlingua ontology) • bidirectional vs. unidirectional • automated vs. manual • OAEI - ontology matching competitions – benchmark with best F-measure result of 80% 2009
  • 12. Ontological Heterogeneity • Semantic matching approaches cannot cope with ontological heterogeneity • The classes and the properties may be described in different unrelated ontologies • The algorithms cannot discover hidden relationships that hold between unrelated entities. FactForge presents exactly such a reality of heterogeneous facts. This makes their automated processing inconvenient.
  • 13. Our Approach unidirectional semantic manual alignment between PROTON and the schema ontologies of the selected datasets of FactForge
  • 14. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 15. Mapping Methods • A series of iterations of enrichments at conceptual and at data levels (a) Subsumption relations for classes (b) Extending PROTON with classes and and properties properties subClassOf FactForge entity PROTON entity (c) Using OWL class and property construction capabilities to represent classes and properties from FactForge and map them to PROTON classes Class restricted from subClassOf PROTON entity FactForge predicates (d) Extending FactForge with instances to account for the conceptual representation of the matching FactForge Instance 2 (new) FactForge Instance 1 FactForge Instance 3 (new)
  • 16. Mapping rules (a) dbp:Place owl:subClassOf proton:Location . (b) dbp-prop:location rdfs:subPropertyOf proton:locatedIn . (c) pfb:Location rdf:type owl:Restriction ; owl:onProperty <http://rdf.freebase.com/ns/type.object.type> ; owl:hasValue <http://rdf.freebase.com/ns/location.location> ; rdfs:subClassOf proton:Location . (d) p <rdf:type> <dbp-ont:PrimeMinister> ---------------------------------------------------- p <proton:hasPosition> j j <proton:hasTitle> <proton:PrimeMinister>
  • 17. Conceptual mismatches Expression matching dbp:Architect rdfs:subClassOf [ rdf:type owl:Restriction ; owl:onProperty proton:hasProfession ; owl:hasValue proton:Architect ] .
  • 18. Multiple Matching DBPedia ontology predicate PROTON predicate DBPedia predicate Freebase predicate dbp:place rdfs:subPropertyOf proton:locatedIn . dbp-prop:location rdfs:subPropertyOf proton:locatedIn . <http://rdf.freebase.com/ns/time.event.locations> rdfs:subPropertyOf proton:locatedIn .
  • 19. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 20. PROTON Extension • Preserve the OntoClean approach in PROTON design • Obtain coverage of the rich data in FactForge • Keep an optimal degree of granularity of the concept hierarchy Proton was split into modules : - 19 modules reflecting the conceptual divisions which surfaced during the analysis of the data, e.g. proton event, proton social abstraction, proton location, proton biological substance, etc.
  • 21. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 22. Statistics • PROTON Extension – 141 new Classes – 3 new Datatype properties – 12 new Object properties • Mapping PROTON to FactForge – 536 subClassOf relations – 36 subPropertyOf relations
  • 23. Outline • Introduction • Problem and Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 24. Experiment Data Loading BigOWLIM – the most scalable OWL Engine http://www.ontotext.com/owlim/ FactForge with FactForge Standard mappings June June 2010 2010 NumberOfStatements 1,782,541,506 2,630,453,334 NumberOfExplicitStatements 1,143,317,531 1,942,349,578 NumberOfEntities 354,635,159 404,798,593
  • 25. FactForge Extension Statistics October 2010 FactForge FactForge with FactForge with IR FactForge with IR, FactForge with Inference Rules and PROTON PROTON and DBP IR, PROTON, mappings DBP mappings and Freebase mappings NumberOfStatements 2,237,550,385 2,237,550,617 2,237,578,643 2,255,543,166 2,375,287,183 NumberOfExplicitStatements 1,357,013,227 2,027,992,627 2,027,995,363 2,027,995,651 2,027,995,750 NumberOfEntities 524,120,454 524,120,465 524,121,955 524,121,996 524,122,009
  • 26. FactForge Extension Statistics Difference between FactForge and Each Adding Iteration October 2010 FactForgeFactForge and FactForge and factForge and factForge and FactForge with FactForge with FactForge with FactForge with Inference Rules IR and IR, PROTON IR, PROTON, PROTON and DBP DBP mappings mappings and Freebase mappings NumberOfStatements 0 232 28,258 17,992,781 137,736,798 NumberOfExplicitStatem ents 0 670,979,400 670,982,136 670,982,424 670,982,523 NumberOfEntities 0 11 1,501 1,542 1,555
  • 27. FactForge Extension Statistics Difference between Each Adding Iteration October 2010 FactForge FactForge and FactForge with FactForge with IR FactForge with FactForge with Inference Rules and PROTON and IR, PROTON and Inference Rules and FactForge FactForge with DBP mappings with IR and IR, PROTON and and FactForge PROTON DBP mappings with IR, PROTON, DBP mappings and Freebase mappings NumberOfStatements 0 232 28,026 17,964,523 119,744,017 NumberOfExplicitStatements 0 670,979,400 2,736 288 99 NumberOfEntities 0 11 1490 41 13
  • 28. Experimentation: PROTON query US non-profit organizations founded after 1950 PREFIX p-ext: <http://proton.semanticweb.org/protonue#> PREFIX ptop: <http://proton.semanticweb.org/protont#> PREFIX dbpedia: <http://dbpedia.org/resource/> SELECT distinct ?s ?date ?l WHERE { ?s a p-ext:Non-ProfitOrganisation . ?s ptop:establishmentDate ?date . ?s ptop:locatedIn ?l . ?l ptop:subRegionOf dbpedia:United_States . FILTER (?date > "1950") }
  • 29. Query: Prime Ministers born in the United Kingdom PREFIX dbp-ont: <http://dbpedia.org/ontology/> PREFIX dbpedia: <http://dbpedia.org/resource/> SELECT ?PrimeMinister WHERE { ?PrimeMinister rdf:type dbp-ont:PrimeMinister . ?PrimeMinister dbp-ont:birthPlace dbpedia:United_Kingdom . } PREFIX pupp: <http://proton.semanticweb.org/protonu#> PREFIX p-ext: <http://proton.semanticweb.org/protonue#> PREFIX dbpedia: <http://dbpedia.org/resource/> PREFIX ptop: <http://proton.semanticweb.org/protont#> SELECT ?PrimeMinister WHERE { ?PrimeMinister ptop:hasPosition ?pos . ?pos pupp:hasTitle dbpedia:British_prime_minister . ?PrimeMinister p-ext:birthPlace dbpedia:United_Kingdom . }
  • 30. Query: Cities around the world which have Modigliani art work PREFIX fb: <http://rdf.freebase.com/ns/> PREFIX dbpedia: <http://dbpedia.org/resource/> PREFIX dbp-prop: <http://dbpedia.org/property/> PREFIX dbp-ont: <http://dbpedia.org/ontology/> PREFIX umbel-sc: <http://umbel.org/umbel/sc/> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX ot: <http://www.ontotext.com/> SELECT DISTINCT ?painting_l ?owner_l ?city_fb_con ?city_db_loc ?city_db_cit WHERE { ?p fb:visual_art.artwork.artist dbpedia:Amedeo_Modigliani ; fb:visual_art.artwork.owners [ fb:visual_art.artwork_owner_relationship.owner ?ow ] ; ot:preferredLabel ?painting_l. ?ow ot:preferredLabel ?owner_l . OPTIONAL { ?ow fb:location.location.containedby [ ot:preferredLabel ?city_fb_con ] } OPTIONAL { ?ow dbp-prop:location ?loc. ?loc rdf:type umbel-sc:City ; ot:preferredLabel ?city_db_loc } OPTIONAL { ?ow dbp-ont:city [ ot:preferredLabel ?city_db_cit ] } }
  • 31. Query: Cities around the world which have Modigliani art work PREFIX dbpedia: <http://dbpedia.org/resource/> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX ot: <http://www.ontotext.com/> PREFIX ptop: <http://proton.semanticweb.org/protont#> PREFIX p-ext: <http://proton.semanticweb.org/protonue#> SELECT DISTINCT ?painting ?owner ?city WHERE { ?p p-ext:author dbpedia:Amedeo_Modigliani ; p-ext:ownership [ ptop:isOwnedBy ?ow ] ; ot:preferredLabel ?painting . ?ow ot:preferredLabel ?owner . ?ow ptop:locatedIn [ rdf:type pupp:City ; ot:preferredLabel ?city]. }
  • 32. Outline • Introduction • Problem • Conceptual Solution • Approaches to Matching Ontologies • Mapping Methods • Proton Extension • Statistics • Experimentation • Future Work
  • 33. Upper Mapping and Binding Exchange Layer A lightweight, subject concept reference structure for the Web Future Work • Two-level intermediary layer to access FactForge mapping PROTON to UMBEL Datasets Dataset1 Dataset2 Dataset3 Dataset4 Ontology 1 Ontology 2 Ontology 3 Ontology 4 Two level Upper Level Ontology 2 Intermediate layer Upper Level Ontology 1 Query ?S P O triples ?S P1 ?O1 ?O1 P2 O2 UMBEL - Upper Mapping and Binding Exchange Layer A lightweight, subject concept reference structure for the Web 20 000 concepts mapped to OpenCyc Strategic partnership Ontotext – Structured Dynamics http://www.ontotext.com/news.html#umb_25oct10
  • 34. Future Work • Official FactForge release with the presented mapping • Publish Proton and mapping as LOD • Cover more datasets from the LOD cloud • Experiment with the balance between the datasets and the ontologies describing them • Extend the property mapping
  • 35. Service available at http://factforge.net (a version with Proton mapping is currently available at http://ldsr4.ontotext.com) Thank you for your attention! Questions? Contact: mariana.damova@ontotext.com