An analysis of the quality issues of the properties available in the Spanish DBpedia

An Analysis of the Quality Issues of the Properties Available

in the Spanish DBpedia

Nandana Mihindukulasooriya, Mariano Rico, Raúl García-Castro, and Asunción Gómez-Pérez

Ontology Engineering Group (OEG)Departamento de Inteligencia Artificial

Escuela Técnica Superior de Ingenieros InformáticosUniversidad Politécnica de Madrid

Acknowledgments: 4V (TIN2013-46238-C4-2-R) and LIDER (EU FP7 610782) projects

http://loupe.linkeddata.es

http://loupe.linkeddata.es/

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Collaborative editing in Wikipedia

Ontology Engineering Group, Universidad Politécnica de Madrid

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Spontaneous data model creation


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Can spontaneous data models support us in data quality

assessment?

But, first, what is the quality of such spontaneous data models?


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DBpedia – Exposing Wikipedia’s content as Linked Data


RDF Triplestore

Ren

derin

g

mappings

infobox

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esDBpedia – the Spanish DBpedia chapter


http://es.dbpedia.org/

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Can esDBpedia’s spontaneous data model support us in data quality

assessment?

But, first, what is the quality of the properties of such spontaneous

data model?Ontology Engineering Group, Universidad Politécnica de Madrid

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Quality Dimensions for Datasets

A. Conciseness. A dataset does not contain redundant concepts with different identifiers

B. Consistency. A dataset does not contain conflicting or contradictory data

C. Syntactic Validity. Values belong to the legal value range for the represented domain and do not violate the syntactic rules

D. Semantic Accuracy. Values correctly represent real world facts


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Extraction and inspection of property statistics



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Information extracted about properties


Property statistics template Example DataGeneral information URI http://es.dbpedia.org/property/edad

Local name edadNamespace http://es.dbpedia.org/property/Number of triples 4623

Subject Analysis IRI subject count 4623 (100 %)Extracted domain classes (i.e., ?subject a ?class)

dbpedia-owl:Agent 2611 (56,48 %)schema:Person 1515 (32.77 %)…

Object analysis URI object count 186 (4.02 %)Extracted range classes(i.e., ?object a ?class)

skos:Concept 17 (9.14 %)schema:Place 2 (1.08 %)…

Literal object count 4437 (95.98 %)Numerical object count 2491 (53.88 %)Integer object count 2382 (51.52 %)Average of numerics 3.53Max numeric sample 8.79E11, 1.5E8, 1.5E7, 8.2E6, 8121540Min numeric sample -5, 0, 1, 1.08, 1.2

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Properties in esDBpedia


Property prefix Properties Property values# % # %

http://es.dbpedia.org/property/ 19,885 52.53 18,021,389 10.66

http://dbpedia.org/property/ 17,188 45.40 9,742,710 5.76

http://dbpedia.org/ontology/ 576 1.52 86,602,281 51.21

http://xmlns.com/foaf/0.1/ 12 0.03 8,132,328 4.81

http://www.w3.org/1999/02/22-rdf-syntax-ns#

8 0.02 12,298,451 7.27

http://www.w3.org/2000/01/rdf-schema# 7 0.02 5,366,982 3.17

http://www.w3.org/2002/07/owl# 6 0.02 16,523,751 9.77

http://purl.org/dc/terms/# 4 0.01 4,148,399 2.45

http://www.w3.org/2004/02/skos/core# 4 0.01 1,153,685 0.68

http://purl.org/dc/elements/1.1/ 3 0.01 3,346,874 1.98

http://www.w3.org/ns/prov# 1 0.00 2,853,681 1.69

Other prefixes 163 0.43 911,131 0.54

Total 37,857 100 169,101,662 100

12Ontology Engineering Group, Universidad Politécnica de Madrid

A. Conciseness

• Many redundant properties in esDBpedia• 97.93% are auto-generated

• Causes• Capitalization (857): partidosEnPrimera,partidosenprimera• Synonyms: causaDeMuerte, causaDeFallecimiento• Prepositions: causaDeFallecimiento, causaFallecimiento• Spelling (7,495): apeliido, apelldio, apellid• Singular/plural: apellido, apellidos• Gender: administrador, administradora• Accent usage (1,252): administracion, administración• Parsing (107): altitudMin/máx, residencia/trabajo, idioma/s

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B. Consistency

• OWL properties with IRI and literal values• 3,380 properties• Use of strings and URL interchangeably

• esdbpedia:lugarDeEntierro• "Madrid"@es• http://es.dbpedia.org/resource/Madrid

• Diverse and incorrect domain and range types • esdbpedia:edad has range of type dbo:Place • esdbpedia:lugarmuerte has range of type dbo:Person• esdbpedia:pais has range of type dbo:Actor


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C. Syntactic Validity

• IRIs represented as strings• Many properties with IRI values and very few string values• Common cause:

• IRIs encoded as strings -> “http://...”@es • Numerical values represented as strings

• 3,675 properties with more than 99% integer objects and a very few string literals

• Common cause: • Numerics encoded as strings -> “2^^xsd:integer”


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D. Semantic Accuracy

• Outliers • Numerical values allow an automatic analysis • Properties such as diameter or edad with negative values

• Harder to detect automatically • Our plan is to use data fusion approaches to compare

values from multiple sources


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Conclusions and future work

• DBpedia’s spontaneous data model can support quality assessment

• Errors in DBpedia are introduced in many stages• Crowd-sourced data• Mappings• Extraction framework

• Some errors can be eliminated with pre-processing and cleaning

• Quality assessment currently semi-automatic• Currently working towards its automation

• We plan to investigate if the quality issues are the same in other DBpedia instances


Questions?


An analysis of the quality issues of the properties available in the Spanish DBpedia

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