2015.09. - The Role of Reasoning for RDF Validation (SEMANTiCS 2015)

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11th International Conference on Semantic Systems (SEMANTiCS 2015)

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2015.09. - The Role of Reasoning for RDF Validation (SEMANTiCS 2015)

  1. 1. The Role of Reasoning for RDF Validation Thomas Bosch, Gesis - Leibniz Institute for the Social Sciences Erman Acar, University of Mannheim Andreas Nolle, Albstadt-Sigmaringen University Kai Eckert, Stuttgart Media University
  2. 2. RDF Validation • high data quality • XML validation • RDF Validation Workshop • working groups – W3C Data Shapes Working Group – DCMI RDF Application Profiles Task Group • existing constaint languages (ShEx, OWL 2, DSP, ReSh, SPIN, SPARQL, …)
  3. 3. Constraint Types http://purl.org/net/rdf-validation • database of 81 requirements on RDF validation • based on findings of WGs and case studies • from case studies to solutions and back • requirements correspond to constraint types
  4. 4. RDF Validator http://purl.org/net/rdfval-demo example: disjoint classes
  5. 5. what is the role reasoning plays for RDF Validation? why is reasoning beneficial for validation? how to overcome the major shortcomings when validating?
  6. 6. (1) reasoning may resolve violations Book ⊑  author.Person Book(Huckleberry-Finn) author(Huckleberry-Finn, Mark-Twain) → Person(Mark-Twain)
  7. 7. (2) reasoning may cause violations Book ⊑ Publication Publication ⊑ ∃ publisher.Publisher Book(Huckleberry-Finn)
  8. 8. (3) reasoning solves redundency Publication ⊑ ∃ publicationDate.xsd:date Book ⊑ Publication Conference-Proceeding ⊑ Publication Journal-Article ⊑ Publication
  9. 9. for which constraint types reasoning may be performed prior to validation to enhance data quality?
  10. 10. constraint types with and without reasoning • 𝑹: set of constraint types with reasoning – 43.2% – RQL: OWL 2 QL reasoning – RDL: OWL 2 DL reasoning – determine if reasoning should be performed on different levels • 𝑹: set of constraint types without reasoning – 56.8%
  11. 11. constraint types with reasoning sub-properties editor ⊑ creator editor (A+Journal-Volume, A+Editor) creator (A+Journal-Volume, A+Editor)
  12. 12. constraint types with reasoning property domain ∃ author.⊤ ⊑ Publication author(Alices-Adventures-In-Wonderland, Lewis-Carroll) rdf:type(Alices-Adventures-In-Wonderland, Publication)
  13. 13. constraint types without reasoning literal pattern matching ISBN a rdfs:Datatype ; owl:equivalentClass [ a rdfs:Datatype ; owl:onDatatype xsd:string ; owl:withRestrictions ([ xsd:pattern "^d{9}[d|X]$" ])] . Book ⊑  identifier.ISBN
  14. 14. constraint types without reasoning allowed values Book ≡  subject. {Computer-Science, Librarianship}
  15. 15. How efficient in terms of runtime validation is performed with and without reasoning?
  16. 16. performance in worst case • computational complexity • mapping to description logics
  17. 17. performance in worst case validation type complexity class 𝑹 PSPACE-Complete RQL PTIME RDL N2EXPTIME PTIME ⊆ PSPACE-Complete ⊆ N2EXPTIME
  18. 18. for which constraint types validation results differ (1) if the CWA or the OWA and (2) if the UNA or the nUNA is assumed?
  19. 19. • reasoning and validation assume different semantics – reasoning: OWA + nUNA – validation: CWA + UNA • different semantics lead to different validation results • does the constraint type depend on the CWA? • does the constraint type depend on the UNA? semantics
  20. 20. CWA dependent constraint types minimum qualified cardinality restrictions Publication ⊑ ≥1 author.Person
  21. 21. CWA independent constraint types disjoint classes Book ⊓ JournalArticle ⊑ ⊥
  22. 22. UNA dependent constraint types functional properties funct(title) title(The-Adventures-of-Huckleberry-Finn, "The Adventures of Huckleberry Finn") title(The-Adventures-of-Huckleberry-Finn, "Die Abenteuer des Huckleberry Finn")
  23. 23. UNA independent constraint types literal value comparison birthDate(Albert-Einstein, "1955-04-18") deathDate(Albert-Einstein, "1879-03-14") birthDate(Albert_Einstein, "1879-03-14") deathDate(Albert_Einstein, "1955-04-18") owl:sameAs(Albert-Einstein, Albert_Einstein)
  24. 24. • CWA dependent: 56.8% • UNA dependent: 66.6% evaluation results on semantics
  25. 25. Contributions 1. role reasoning plays for validation 2. how reasoning improves data quality 3. efficiency with and without reasoning 4. dependency on different semantics

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