Dimou, Anastasia

Freudenberg, Markus

Hellman, Sebastian

Kontokostas, Dimitris

Lehmann, Jens

Mannens, Erik

Van de Walle, Rik

Verborgh, Ruben

English

Ghent University Academic Bibliography

  biblio.ugent.be   The UGent Institutional Repository is the electronic archiving and dissemination platform for allUGent research publications. Ghent University has implemented a mandate stipulating that allacademic publications of UGent researchers should be deposited and archived in this repository.Except for items where current copyright restrictions apply, these papers are available in OpenAccess.   This item is the archived peer-reviewed author-version of:   DBpedia Mappings Quality Assessment   Anastasia Dimou, Dimitris Kontokostas, Markus Freudenberg, Ruben Verborgh, Jens Lehmann, ErikMannens, and Sebastian Hellmann   In: Proceedings of the 15th International Semantic Web Conference: Posters and Demos. , 2016.     To refer to or to cite this work, please use the citation to the published version:   Dimou, A., Kontokostas, D., Freudenberg, M., Verborgh, R., Lehmann, J., Mannens, E., andHellmann, S. (2016). DBpedia Mappings Quality Assessment. Proceedings of the 15th InternationalSemantic Web Conference: Posters and Demos.  DBpedia Mappings Quality Assessment?Anastasia Dimou1, Dimitris Kontokostas2, Markus Freudenberg2,Ruben Verborgh1, Jens Lehmann2, Erik Mannens1,Sebastian Hellmann2, and Rik Van de Walle11 Ghent University – iMinds – Data Science Lab, Belgium{firstname.lastname}@ugent.be2 Universitat Leipzig, Institut fur Informatik, AKSW, Germany{lastname}@informatik.uni-leipzig.deAbstract. The root of schema violations for rdf data generated from(semi-)structured data, often derives from mappings, which are repeat-edly applied and specify how an rdf dataset is generated. The dbpediadataset, which derives from Wikipedia infoboxes, is no exception. Tomitigate the violations, we proposed in previous work to validate themappings which generate the data, instead of validating the generateddata afterwards. In this work, we demonstrate how mappings validationis applied to dbpedia. dbpedia mappings are automatically translated torml and validated by rdfunit. The dbpedia mappings assessment can befrequently executed, because it requires significantly less time comparedto validating the dataset. The validation results become available via auser-friendly interface. The dbpedia community takes them into consid-eration to refine the dbpedia mappings or ontology and thus, increasethe dataset quality.Keywords: Linked Data Mapping, Data Quality, dbpedia, rml, rdfunit1 IntroductionAlthough more and more data is published as Linked Data, there are significantvariations in quality [5], commonly conceived as “fitness for use” for a certainapplication or use case. When datasets stem originally from semi-structured for-mats (e.g., csv, xml), the schema is derived from the set of classes and propertiesspecified by the mappings which are applied repeatedly. Consequently, if thosemappings contain inaccuracies, the same violations are repeated over and overin the dataset. Incorporating quality assessment as part of the mapping activ-ity is therefore essential to prevent most recurring schema-based violations. Tothis end, we have proposed a uniform approach for assessing the mappings anddataset quality [1]. We implemented our approach based on the rdfunit valida-tion framework [3] and the rml mapping language [2]. Our solution incremen-tally assesses the quality of an rdf dataset, covering both the mappings and the? This paper’s research activities were funded by Ghent University, iMinds, the Institute forthe Promotion of Innovation by Science and Technology in Flanders, the Fund for ScientificResearch-Flanders and grants from the EU’s 7th & H2020 Programmes for the projects ALIGNED(GA 644055), GeoKnow (GA 318159) and LIDER (GA 610782).2 Anastasia Dimou et al.dataset itself. Since rml mappings are expressed in rdf, the rdfunit validationframework can apply its test cases to rml mappings similarly to how it appliesthem to rdf datasets. Assessing an rdf dataset requires a lot of time, thus itcannot be frequently executed, and, when it happens, the violations’ root is notintuitively detected. On the contrary, directly assessing mappings that generatesa dataset requires significantly less time and the violation root is detected.In this work, we demonstrate how we incorporated our solution in the dbpediavalidation workflow. dbpedia mappings are automatically translated to rml andsubsequently assessed using rdfunit. In this demo, the validation results will beshown via a user friendly interface and users can directly contribute to improvethe dbpedia mappings. Once they update a mapping or the dbpedia ontology,users will be able to trigger a new validation round and immediately see theupdated validation results, without the violation they just corrected.2 Expressing DBpedia Mappings with RMLdbpedia [4] provides a collaborative mapping approach of Wikipedia infoboxesto the dbpedia ontology3. The mappings are maintained and edited through thedbpedia mappings wiki4, using the same wiki markup syntax as Wikipedia todefine the mappings. However, the quality of wikitext-based mappings cannotbe assessed directly, and certainly not in the same way as the resulting dataset.rml covers mappings from sources in different (semi-)structured formats.Furthermore, it is highly scalable towards other structures and formalizations.Taking advantage of this, we introduced wikitext serialisation as a new ReferenceFormulation. A Reference Formulation is used to indicate the grammar which shouldbe used to refer to data of a certain structure and format. 674 distinct mappingdocuments for English, 463 for Dutch and a total of 4,468 for all languagessupported in the dbpedia mappings wiki are translated to rml and are availableat http://mappings.dbpedia.org/server/mappings/en/pages/rdf/.A dbpedia mapping follows for the Infobox Person5:1 {{TemplateMapping2 | mapToClass = Person3 | mappings =4 {{PropertyMapping | templateProperty = name | ontologyProperty = foaf:name }}5 {{PropertyMapping | templateProperty = birth_date | ontologyProperty = birthDate }}6 {{PropertyMapping | templateProperty = birth_place | ontologyProperty = birthPlace }}}}and its corresponding rml mapping, after being translated to rml is 6:1 <http://mappings.dbpedia.org/server/mappings/en/Infobox_person>2 rr:subjectMap [ rr:class dbpedia:Person ; rr:termType rr:IRI ;3 rr:constant "http://dbpedia.org/resource/Template:Infobox_person" ] ;4 rr:predicateObjectMap [ rr:predicate dbpedia:birthPlace ;5 rr:objectMap [ a rr:ObjectMap ; rml:reference "birth_place". ] ] .3 http://wiki.dbpedia.org/Ontology4 http://mappings.dbpedia.org5 http://mappings.dbpedia.org/index.php?title=Mapping_en:Infobox_person&action=edit6 The example is adjusted to improve reading. A full rml transformation can be found at http://mappings.dbpedia.org/server/mappings/en/pages/rdf/Mapping_en%3AInfobox_personContinuous and Automated Assessment of DBpedia Mappings 3Fig. 1. Screenshot of a violations list presented to the dbpedia community. For every violatingmapping, the predicate with the existing rdf term, according to the corresponding dbpediamapping, and the expected value, according to the dbpedia ontology are presented.3 DBpedia Mappings Quality AssessmentSince rml mappings can be processed as rdf documents, and are written fromthe viewpoint of the generated triples, the same set of schema validation patternsnormally applied to the rdf dataset is also applicable to the mappings thatstate how the dataset is generated. rdfunit was extended to also support qualityassessment over rml mappings [1]. Indicatively, instead of validating each triple’spredicate from the final rdf dataset against its subject and object, the predicateis extracted from the Predicate Map, that defines what the triple’s predicate willbe in rml, and is validated against the Term Maps that define how the subjectand object will be generated. The expected value, as derived from the dbpediaontology, is compared to the specified one, as derived from the correspondingmapping. To achieve this, the schemas and their namespaces are retrieved andthe test cases are generated as if they were the actual dataset. For instance,an extracted predicate expects a Literal as object according to the dbpediaontology, but the mapping that defines how the object is generated specifiesthat a resource should be generated instead; in this case a violation is reported.To systematically validate dbpedia mappings and have up-to-date reports,we created a script7 to trigger all dbpedia mappings validation and is executedevery night. The script exports the dbpedia mapping violations as a json filethat, in turn, is visualized (cf. Figure 1) using a user-friendly interface whichis available at http://mappings.dbpedia.org/validation. The assessmentand report generation is automated, streamlined, and frequently executed. Thedbpedia community uses the violations list as feedback to correct violating map-pings or enhance the dbpedia ontology and, thus, improves the dataset’s quality.DBpedia Mappings and Dataset AssessmentWe compared the dbpedia 2014 release assessment to the dbpedia mappings as-sessment. English and Dutch dbpedia mappings as well as dbpedia mappings of7 https://github.com/AKSW/RDFUnit/blob/master/rdfunit-examples/src/main/java/org/aksw/rdfunit/examples/DBpediaMappingValidator.java4 Anastasia Dimou et al.all 27 supported languages were validated. The results show that the quality as-sessment time is significantly reduced when assessing the mappings compared tothe complete rdf dataset. It takes only 11 seconds to assess the English dbpediamappings, while assessing the whole dbpedia dataset takes 16 hours, because thedataset assessment requires examining each triple separately to identify, for in-stance 12M triples violating the range of foaf:primaryTopic. Mapping assessmentrequires only 1 triple to be examined. Indicatively, the evaluation of all mappingsfor all 27 language editions resulted in a total of 1316 domain-level violations.dataset assessment mapping assessmentdataset #triples time #viol. #triples time #viol.DBpEn 62M 16.h 3.2M 115K 11s 160DBpNl 21M 1.5h 815K 53K 6s 124DBpAll – – – 511K 32s 1,316Table 1. For each of the dbpedia dataset and mapping assessment, the number oftriples, evaluation time and total individual violations appear respectively.The latest dbpedia releases rely on results of this work8. We currently in-corporate the rml toolchain in the dbpedia extraction framework9 and planto integrate the mapping validation in the editing step and, thus, prevent thecreation of violating mappings. This will enable the complete assessment and re-finement workflow use [1] to automatically improve the dbpedia dataset quality.References1. A. Dimou, D. Kontokostas, M. Freudenberg, R. Verborgh, J. Lehmann, E. Mannens,S. Hellmann, and R. Van de Walle. Assessing and Refining Mappings to RDF toImprove Dataset Quality. In Proceedings of the 14th International Semantic WebConference, Oct. 2015.2. A. Dimou, M. Vander Sande, P. Colpaert, R. Verborgh, E. Mannens, and R. Van deWalle. RML: A Generic Language for Integrated RDF Mappings of HeterogeneousData. In Workshop on Linked Data on the Web, 2014.3. D. Kontokostas, M. Brümmer, S. Hellmann, J. Lehmann, and L. Ioannidis. NLPdata cleansing based on Linguistic Ontology constraints. In Proc. of the ExtendedSemantic Web Conference 2014, 2014.4. J. Lehmann, R. Isele, M. Jakob, A. Jentzsch, D. Kontokostas, P. N. Mendes, S. Hell-mann, M. Morsey, P. Kleef, S. Auer, and C. Bizer. DBpedia - a Large-scale, Multi-lingual Knowledge Base Extracted from Wikipedia. Sem. Web Journal, 2014.5. A. Zaveri, A. Rula, A. Maurino, R. Pietrobon, J. Lehmann, and S. Auer. QualityAssessment for Linked Data: A Survey. Semantic Web Journal, 2015.8 https://github.com/dbpedia/mappings-tracker/issues/579 https://github.com/dbpedia/dbpedia-gsoc/wiki/2016-Integrating-RML-in-the-DBpedia-extraction-framework

DBpedia mappings quality assessment

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DBpedia mappings quality assessment

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