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Article

Quality Metrics for Linked Open Data

Authors:

Behshid Behkamal,

Ebrahim BagheriAuthors Info & Claims

DEXA 2015: Proceedings, Part I, of the 26th International Conference on Database and Expert Systems Applications - Volume 9261

Pages 144 - 152

https://doi.org/10.1007/978-3-319-22849-5_11

Published: 01 September 2015 Publication History

Abstract

The vision of the Linked Open Data LOD initiative is to provide a model for publishing data and meaningfully interlinking such dispersed but related data. Despite the importance of data quality for the successful growth of the LOD, only limited attention has been focused on quality of data prior to their publication on the LOD. This paper focuses on the systematic assessment of the quality of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure and identify these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics.

References

[1]

Hogan, A., Harth, A., Passant, A., Decker, S., Polleres, A.: Weaving the pedantic web. In: 3rd International Workshop on Linked Data on the Web 2010

[2]

Fürber, C., Hepp, M.: Using semantic web resources for data quality management. In: Cimiano, P., Pinto, H. eds. EKAW 2010. LNCS, vol. 6317, pp. 211---225. Springer, Heidelberg 2010

Digital Library

[3]

Behkamal, B., Kahani, M., Paydar, S., Dadkhah, M., Sekhavaty, E.: Publishing Persian linked data; challenges and lessons learned. In: 5th International Symposium on Telecommunications IST, pp. 732---737. IEEE 2010

[4]

Paydar, S., Kahani, M., Behkamal, B.: Publishing data of ferdowsi university of mashhad as linked data. In: Computational Intelligence and Software Engineering 2010

[5]

Zaveri, A., Rula, A., Maurino, A., Pietrobon, R., Lehmann, J., Auer, S.: Quality Assessment for Linked Data: A Survey. Accepted in Semantic Web Journal 2014. http://www.semantic-web-journal.net/content/quality-assessment-linked-data-survey

[6]

Lei, Y., Nikolov, A., Uren, V., Motta, E.: Detecting quality problems in semantic metadata without the presence of a gold standard. In: 5th International EON Workshop at International Semantic Web Conference, pp. 51---60 2007

[7]

Bizer, C., Cyganiak, R.: Quality-driven information filtering using the WIQA policy framework. Web Semant.: Sci., Serv. Agents World Wide Web 7, 1---10 2009

Digital Library

[8]

Brüggemann, S., Grüning, F.: Using ontologies providing domain knowledge for data quality management. In: Pellegrini, T., Auer, S., Tochtermann, K., Schaffert, S. eds. Networked Knowledge - Networked Media. SCI, vol. 221, pp. 187---203. Springer, Heidelberg 2009

[9]

Naumann, F., Leser, U., Freytag, J.C.: Quality-driven integration of heterogeneous information systems. In: 25th International Conference on Very Large Data Bases VLDB 1999, Edinburgh, Scotland, UK, pp. 447---458 1999

Digital Library

[10]

Pipino, L.L., Lee, Y.W., Wang, R.Y.: Data quality assessment. Commun. ACM 45, 211---218 2002

Digital Library

[11]

ISO: ISO/IEC 25012- Software engineering - Software product Quality Requirements and Evaluation SQuaRE. Data quality model 2008

[12]

Peralta, V.: Data freshness and data accuracy: A state of the art. Instituto de Computacion, Facultad de Ingenieria, Universidad de la Republica 2006

[13]

Eppler, M.J., Wittig, D.: Conceptualizing information quality: A review of information quality frameworks from the last ten years. In: 5th International Conference on Information Quality, pp. 83---96 2000

[14]

Behkamal, B., Kahani, M., Bagheri, E., Jeremic, Z.: A Metrics-Driven approach for quality Assessment of Linked open Data. J. Theoritical Appl. Electron. Commer. Res. 9, 64---79 2014

Digital Library

[15]

Bagheri, E., Gasevic, D.: Assessing the maintainability of software product line feature models using structural metrics. Softw. Qual. J. 19, 579---612 2011

Digital Library

Cited By

Nayak ABožić BLongo L(2021)Linked Data Quality Assessment: A SurveyWeb Services – ICWS 202110.1007/978-3-030-96140-4_5(63-76)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1007/978-3-030-96140-4_5
Radulovic FMihindukulasooriya NGarcía-Castro RGómez-Pérez AZaveri AKontokostas DHellmann SUmbrich J(2018)A comprehensive quality model for Linked DataSemantic Web10.3233/SW-1702679:1(3-24)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.3233/SW-170267

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Information & Contributors

Information

Published In

cover image Guide Proceedings

DEXA 2015: Proceedings, Part I, of the 26th International Conference on Database and Expert Systems Applications - Volume 9261

September 2015

546 pages

ISBN:9783319228488

Editors:
Qiming Chen
Hewlett-Packard Enterprise, Sunnyvale, USA
,
Abdelkader Hameurlain
Paul Sabatier University, Toulouse, France
,
Farouk Toumani
Blaise Pascal University, Aubiere, France
,
Roland Wagner
University of Linz, Linz, Austria
,
Hendrik Decker
Universidad Politécnica de Valencia, Valencia, Spain

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 September 2015

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Cited By

Nayak ABožić BLongo L(2021)Linked Data Quality Assessment: A SurveyWeb Services – ICWS 202110.1007/978-3-030-96140-4_5(63-76)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1007/978-3-030-96140-4_5
Radulovic FMihindukulasooriya NGarcía-Castro RGómez-Pérez AZaveri AKontokostas DHellmann SUmbrich J(2018)A comprehensive quality model for Linked DataSemantic Web10.3233/SW-1702679:1(3-24)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.3233/SW-170267

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