2015.09. - the role of reasoning for rdf validation (semantics 2015)
TRANSCRIPT
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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
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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, …)
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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
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RDF Validator
http://purl.org/net/rdfval-demo
example: disjoint classes
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what is the role reasoning plays for RDF Validation?
why is reasoning beneficial for validation?
how to overcome the major shortcomings when validating?
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(1) reasoning may resolve violations
Book ⊑ author.Person
Book(Huckleberry-Finn)
author(Huckleberry-Finn, Mark-Twain)
→ Person(Mark-Twain)
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(2) reasoning may cause violations
Book ⊑ Publication
Publication ⊑
∃ publisher.Publisher
Book(Huckleberry-Finn)
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(3) reasoning solves redundency
Publication ⊑
∃ publicationDate.xsd:date
Book ⊑ Publication
Conference-Proceeding ⊑ Publication
Journal-Article ⊑ Publication
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for which constraint types reasoning may be performed
prior to validation to enhance data quality?
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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%
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constraint types with reasoning
sub-properties
editor ⊑ creator
editor (A+Journal-Volume, A+Editor)
creator (A+Journal-Volume, A+Editor)
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constraint types with reasoning
property domain
∃ author.⊤ ⊑ Publication
author(Alices-Adventures-In-Wonderland,
Lewis-Carroll)
rdf:type(Alices-Adventures-In-Wonderland,
Publication)
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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
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constraint types without reasoning
allowed values
Book ≡ subject.
{Computer-Science, Librarianship}
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How efficient in terms of runtime
validation is performed with and without reasoning?
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performance in worst case
• computational complexity
• mapping to description logics
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performance in worst case
validation type complexity class
𝑹 PSPACE-Complete
RQL PTIME
RDL N2EXPTIME
PTIME ⊆ PSPACE-Complete ⊆ N2EXPTIME
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for which constraint types validation results differ
(1) if the CWA or the OWA and (2) if the UNA or the nUNA is
assumed?
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• 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
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CWA dependent constraint types
minimum qualified cardinality restrictions
Publication ⊑ ≥1 author.Person
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CWA independent constraint types
disjoint classes
Book ⊓ JournalArticle ⊑ ⊥
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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")
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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)
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• CWA dependent: 56.8%
• UNA dependent: 66.6%
evaluation results on semantics
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Contributions
1. role reasoning plays for validation
2. how reasoning improves data quality
3. efficiency with and without reasoning
4. dependency on different semantics