Test-driven Evaluation of Linked Data Quality

Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, Roland Cornelissen, Amrapali Zaveri

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademic

Abstract

Linked Open Data (LOD) comprises of an unprecedented volume of structured data on the Web. However, these datasets are of varying quality ranging from extensively curated datasets to crowd-sourced or extracted data of often relatively low quality. We present a methodology for test-driven quality assessment of Linked Data, which is inspired by test-driven software development. We argue, that vocabularies, ontologies and knowledge bases should be accompanied by a number of test cases, which help to ensure a basic level of quality. We present a methodology for assessing the quality of linked data resources, based on a formalization of bad smells and data quality problems. Our formalization employs SPARQL query templates, which are instantiated into concrete quality test case queries. Based on an extensive survey, we compile a comprehensive library of data quality test case patterns. We perform automatic test case instantiation based on schema constraints or semi-automatically enriched schemata and allow the user to generate specific test case instantiations that are applicable to a schema or dataset. We provide an extensive evaluation of five LOD datasets, manual test case instantiation for five schemas and automatic test case instantiations for all available schemata registered with LOV. One of the main advantages of our approach is that domain specific semantics can be encoded in the data quality test cases, thus being able to discover data quality problems beyond conventional quality heuristics.
Original languageEnglish
Title of host publicationProceedings of the 23rd International Conference on World Wide Web
PublisherInternational World Wide Web Conferences Steering Committee
Pages747-758
Number of pages12
ISBN (Print)978-1-4503-2744-2
DOIs
Publication statusPublished - 2014
Externally publishedYes

Publication series

SeriesWWW '14

Keywords

  • 2014 group_aksw dllearner MOLE sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:lod2 sys:relevantFor:geoknow topic_QualityAnalysis lod2page lehmann kontokostas rdfunit dataquality westphal

Cite this

Kontokostas, D., Westphal, P., Auer, S., Hellmann, S., Lehmann, J., Cornelissen, R., & Zaveri, A. (2014). Test-driven Evaluation of Linked Data Quality. In Proceedings of the 23rd International Conference on World Wide Web (pp. 747-758). International World Wide Web Conferences Steering Committee. WWW '14 https://doi.org/10.1145/2566486.2568002