D
Dimitris Kontokostas
Researcher at Leipzig University
Publications - 50
Citations - 3981
Dimitris Kontokostas is an academic researcher from Leipzig University. The author has contributed to research in topics: Linked data & RDF. The author has an hindex of 16, co-authored 50 publications receiving 3202 citations. Previous affiliations of Dimitris Kontokostas include Aristotle University of Thessaloniki.
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Journal ArticleDOI
DBpedia - A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia
Jens Lehmann,Robert Isele,Max Jakob,Anja Jentzsch,Dimitris Kontokostas,Pablo N. Mendes,Sebastian Hellmann,Mohamed Morsey,Patrick van Kleef,Sören Auer,Sören Auer,Christian Bizer +11 more
TL;DR: An overview of the DBpedia community project is given, including its architecture, technical implementation, maintenance, internationalisation, usage statistics and applications, including DBpedia one of the central interlinking hubs in the Linked Open Data (LOD) cloud.
Proceedings ArticleDOI
Test-driven evaluation of linked data quality
Dimitris Kontokostas,Patrick Westphal,Sören Auer,Sebastian Hellmann,Jens Lehmann,Roland Cornelissen,Amrapali Zaveri +6 more
TL;DR: This work presents a methodology for test-driven quality assessment of Linked Data, which is inspired by test- driven software development, and argues that vocabularies, ontologies and knowledge bases should be accompanied by a number of test cases, which help to ensure a basic level of quality.
Book ChapterDOI
Crowdsourcing Linked Data Quality Assessment
TL;DR: The results show that the two styles of crowdsourcing are complementary and that crowdsourcing-enabled quality assessment is a promising and affordable way to enhance the quality of Linked Data.
Proceedings ArticleDOI
User-driven quality evaluation of DBpedia
Amrapali Zaveri,Dimitris Kontokostas,Mohamed Ahmed Sherif,Lorenz Bühmann,Mohamed Morsey,Sören Auer,Jens Lehmann +6 more
TL;DR: This study aims to assess the quality of this sample of DBpedia resources and adopt an agile methodology to improve the quality in future versions by regularly providing feedback to the DBpedia maintainers.
Book ChapterDOI
TripleCheckMate: A Tool for Crowdsourcing the Quality Assessment of Linked Data
TL;DR: This paper presents a methodology for assessing the quality of linked data resources, which comprises of a manual and a semi-automatic process, and describes the methodology, quality taxonomy and the tools’ system architecture, user perspective and extensibility.