Assessing and Refining Mappingsto RDF to Improve Dataset Quality

  • Anastasia DimouEmail author
  • Dimitris Kontokostas
  • Markus Freudenberg
  • Ruben Verborgh
  • Jens Lehmann
  • Erik Mannens
  • Sebastian Hellmann
  • Rik Van de Walle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9367)


rdf dataset quality assessment is currently performed primarily after data is published. However, there is neither a systematic way to incorporate its results into the dataset nor the assessment into the publishing workflow. Adjustments are manually –but rarely– applied. Nevertheless, the root of the violations which often derive from the mappings that specify how the rdf dataset will be generated, is not identified. We suggest an incremental, iterative and uniform validation workflow for rdf datasets stemming originally from (semi-)structured data (e.g., csv, xml, json). In this work, we focus on assessing and improving their mappings. We incorporate (i) a test-driven approach for assessing the mappings instead of the rdf dataset itself, as mappings reflect how the dataset will be formed when generated; and (ii) perform semi-automatic mapping refinementsbased on the results of the quality assessment. The proposed workflow is applied to diverse cases, e.g., large, crowdsourced datasets such as dbpedia, or newly generated, such as iLastic. Our evaluation indicates the efficiency of our workflow, as it significantly improves the overall quality of an rdf dataset in the observed cases.


Linked data mapping Data quality rml r2rml rdfunit 


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  1. 1.
    Acosta, M., Zaveri, A., Simperl, E., Kontokostas, D., Auer, S., Lehmann, J.: Crowdsourcing linked data quality assessment. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., Janowicz, K. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 260–276. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  2. 2.
    Bischof, S., Decker, S., Krennwallner, T., Lopes, N., Polleres, A.: Mapping between RDF and XML with XSPARQL. Journal on Data Semantics 1(3), 147–185 (2012)CrossRefGoogle Scholar
  3. 3.
    Bizer, C., Cyganiak, R.: Quality-driven information filtering using the WIQA policy framework. Web Semant. 7(1), 1–10 (2009)CrossRefGoogle Scholar
  4. 4.
    Boehm, B.W.: Software Engineering Economics. Prentice Hall PTR (1981)Google Scholar
  5. 5.
    Cyganiak, R., Bizer, C., Garbers, J., Maresch,O., Becker, C.: The D2RQ Mapping Language. Technical report, March 2012Google Scholar
  6. 6.
    Das, S., Sundara, S., Cyganiak, R.: R2RML: RDB to RDF Mapping Language. Working Group Recommendation W3C, September 2012Google Scholar
  7. 7.
    De Vocht, L., Van Compernolle, M., Dimou, A., Colpaert, P., Verborgh, R., Mannens, E., Mechant, P., Van de Walle, R.: Converging on semantics to ensure local government data reuse. In: Proceedings of the 5th workshop on Semantics for Smarter Cities (SSC14), 13th International Semantic Web Conference (ISWC) (2014)Google Scholar
  8. 8.
    Debattista, J., Lange, C., Auer, S.: Representing dataset quality metadata using multi-dimensional views. In: Proceedings of the 10th International Conference on Semantic Systems, pp. 92–99 (2014)Google Scholar
  9. 9.
    Dimou, A., Vander Sande, M., Colpaert, P., De Vocht, L., Verborgh, R., Mannens, E., Van de Walle, R.: Extraction & semantic annotation of workshop proceedings in HTML using RML. In: Sem. Publ. Challenge of 11th ESWC (2014)Google Scholar
  10. 10.
    Dimou, A., Vander Sande, M., Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: RML: a generic language for integrated RDF mappings of heterogeneous data. In: Workshop on Linked Data on the Web (2014)Google Scholar
  11. 11.
    Flemming, A.: Quality characteristics of linked data publishing datasources. Master’s thesis, Humboldt-Universität of Berlin (2010)Google Scholar
  12. 12.
    Fürber, C., Hepp, M.: Using semantic web resources for data quality management. In: Cimiano, P., Pinto, H.S. (eds.) EKAW 2010. LNCS, vol. 6317, pp. 211–225. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  13. 13.
    Fürber, C., Hepp, M.: Using SPARQL and SPIN for data quality management on the semantic web. In: Abramowicz, W., Tolksdorf, R. (eds.) BIS 2010. LNBIP, vol. 47, pp. 35–46. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  14. 14.
    Guéret, C., Groth, P., Stadler, C., Lehmann, J.: Assessing linked data mappings using network measures. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 87–102. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  15. 15.
    Hert, M., Reif, G., Gall, H.C.: A comparison of RDB-to-RDF mapping languages. In: I-Semantics 2011, pp. 25–32. ACM (2011)Google Scholar
  16. 16.
    Heyvaert, P., Dimou, A., Verborgh, R., Mannens, E., Van de Walle, R.: Semantically annotating CEUR-WS workshop proceedings with RML. In: Semantic Publishing Challenge of the 12th ESWC (2015)Google Scholar
  17. 17.
    Hogan, A., Harth, A., Passant, A., Decker, S., Polleres, A.: Weaving the pedantic web. In: Linked Data On the Web (2010)Google Scholar
  18. 18.
    Hyland, B., Atemezing, G., Villazón-Terrazas, B.: Best Practices for Publishing Linked Data. Working Group Note, W3C, January 2004Google Scholar
  19. 19.
    Juran, J., Gryna, F.: Juran’s Quality Control Handbook. Industrial engineering series. McGraw-Hill (1988)Google Scholar
  20. 20.
    Kontokostas, D., Brümmer, M., Hellmann, S., Lehmann, J., Ioannidis, L.: NLP data cleansing based on linguistic ontology constraints. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 224–239. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  21. 21.
    Kontokostas, D., Westphal, P., Auer, S., Hellmann, S., Lehmann, J., Cornelissen, R., Zaveri, A.: Test-driven evaluation of linked data quality. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 747–758 (2014)Google Scholar
  22. 22.
    Langegger, A., Wöß, W.: XLWrap – querying and integrating arbitrary spreadsheets with SPARQL. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 359–374. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  23. 23.
    Lehmann, J.: DL-learner: Learning concepts in description logics. Journal of Machine Learning Research 10, 2639–2642 (2009)MathSciNetzbMATHGoogle Scholar
  24. 24.
    Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., Kleef, P., Auer, S., Bizer, C.: DBpedia - a Large-scale, Multilingual Knowledge Base Extracted from Wikipedia. Sem. Web Journal (2014)Google Scholar
  25. 25.
    Mendes, P.N., Mühleisen, H., Bizer, C.: Sieve: linked data quality assessment and fusion. In: EDBT/ICDT Workshops, pp. 116–123. ACM (2012)Google Scholar
  26. 26.
    O’Connor, M.J., Halaschek-Wiener, C., Musen, M.A.: Mapping master: a flexible approach for mapping spreadsheets to OWL. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part II. LNCS, vol. 6497, pp. 194–208. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  27. 27.
    Prud’hommeaux, E., Labra Gayo, J.E., Solbrig, H.: Shape expressions: an RDF validation and transformation language. In: Proceedings of the 10th International Conference on Semantic Systems, pp. 32–40. ACM (2014)Google Scholar
  28. 28.
    Schmachtenberg, M., Bizer, C., Paulheim, H.: Adoption of the linked data best practices in different topical domains. In: Mika, P., Tudorache, T., Bernstein, A., Welty, C., Knoblock, C., Vrandečić, D., Groth, P., Noy, N., Janowicz, K., Goble, C. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 245–260. Springer, Heidelberg (2014) Google Scholar
  29. 29.
    Zaveri, A., Rula, A., Maurino, A., Pietrobon, R., Lehmann, J., Auer, S.: Quality assessment for linked data: A survey. Semantic Web Journal (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Anastasia Dimou
    • 1
    Email author
  • Dimitris Kontokostas
    • 2
  • Markus Freudenberg
    • 2
  • Ruben Verborgh
    • 1
  • Jens Lehmann
    • 2
  • Erik Mannens
    • 1
  • Sebastian Hellmann
    • 2
  • Rik Van de Walle
    • 1
  1. 1.iMinds - Multimedia LabGhent UniversityGhentBelgium
  2. 2.Institut Fur Informatik, AKSWUniversitat LeipzigLeipzigGermany

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