skip to main content
10.1145/3308560.3317075acmotherconferencesArticle/Chapter ViewAbstractPublication PageswwwConference Proceedingsconference-collections
research-article

Is the LOD cloud at risk of becoming a museum for datasets? Looking ahead towards a fully collaborative and sustainable LOD cloud

Published:13 May 2019Publication History

ABSTRACT

The Linked Open Data (LOD) cloud has been around since 2007. Throughout the years, this prominent depiction served as the epitome for Linked Data and acted as a starting point for many. In this article we perform a number of experiments on the dataset metadata provided by the LOD cloud, in order to understand better whether the current visualised datasets are accessible and with an open license. Furthermore, we perform quality assessment of 17 metrics over accessible datasets that are part of the LOD cloud. These experiments were compared with previous experiments performed on older versions of the LOD cloud. The results showed that there was no improvement on previously identified problems. Based on our findings, we therefore propose a strategy and architecture for a potential collaborative and sustainable LOD cloud.

References

  1. Keith Alexander, Richard Cyganiak, Michael Hausenblas, and Jun Zhao. 2011. Describing Linked Datasets with the VoID Vocabulary. W3C Interest Group Note. World Wide Web Consortium.Google ScholarGoogle Scholar
  2. Ahmad Assaf, Raphaël Troncy, and Aline Senart. 2015. What’s up LOD Cloud? - Observing the State of Linked Open Data Cloud Metadata. In The Semantic Web: ESWC 2015 Satellite Events - ESWC 2015 Satellite Events Portorož, Slovenia, May 31 - June 4, 2015, Revised Selected Papers(Lecture Notes in Computer Science), Fabien Gandon, Christophe Guéret, Serena Villata, John G. Breslin, Catherine Faron-Zucker, and Antoine Zimmermann (Eds.). Vol. 9341. Springer, 247–254.Google ScholarGoogle Scholar
  3. Tim Berners-Lee. 2006. Linked Data – Design Issues. https://www.w3.org/DesignIssues/LinkedData.html. Accessed: 2017-12-15.Google ScholarGoogle Scholar
  4. Sarven Capadisli, Sören Auer, and Axel-Cyrille Ngonga Ngomo. 2015. Linked SDMX Data: Path to high fidelity Statistical Linked Data. Semantic Web 6, 2 (2015).Google ScholarGoogle ScholarCross RefCross Ref
  5. Sarven Capadisli and Amy Guy. 2017. Linked Data Notifications. W3C Recommendation. World Wide Web Consortium (W3C).Google ScholarGoogle Scholar
  6. J. Debattista, S. Auer, and C. Lange. 2016. Luzzu – A Methodology and Framework for Linked Data Quality Assessment. Data and Information Quality 8, 1 (Oct. 2016). Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Jeremy Debattista, Christoph Lange, and Sören Auer. 2014. Representing dataset quality metadata using multi-dimensional views. In Proceedings of the 10th International Conference on Semantic Systems, SEMANTICS 2014, Leipzig, Germany, September 4-5, 2014, Harald Sack, Agata Filipowska, Jens Lehmann, and Sebastian Hellmann (Eds.). ACM, 92–99. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Jeremy Debattista, Christoph Lange, Sören Auer, and Dominic Cortis. 2018. Evaluating the quality of the LOD cloud: An empirical investigation. Semantic Web 9, 6 (Sep 2018), 859–901.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Pascal Hitzler and Krzysztof Janowicz. 2013. Linked Data, Big Data, and the 4th Paradigm. Semantic Web 4, 3 (2013), 233–235. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Aidan Hogan, Andreas Harth, Alexandre Passant, Stefan Decker, and Axel Polleres. 2010. Weaving the Pedantic Web. In Proceedings of the WWW2010 Workshop on Linked Data on the Web, LDOW 2010, Raleigh, USA, April 27, 2010(CEUR Workshop Proceedings), Christian Bizer, Tom Heath, Tim Berners-Lee, and Michael Hausenblas (Eds.). Vol. 628. CEUR-WS.org. http://ceur-ws.org/Vol-628/ldow2010_paper04.pdfGoogle ScholarGoogle Scholar
  11. Aidan Hogan, Jürgen Umbrich, Andreas Harth, Richard Cyganiak, Axel Polleres, and Stefan Decker. 2012. An empirical survey of Linked Data conformance. Web Semantics: Science, Services and Agents on the World Wide Web 14 (jul 2012), 14–44. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Fadi Maali, John Erickson, and Phil Archer. 2014. Data Catalog Vocabulary (DCAT). W3C Recommendation. World Wide Web Consortium. http://www.w3.org/TR/vocab-dcat/Google ScholarGoogle Scholar
  13. John P. McCrae, Andrejs Abele, Paul Buitelaar, Richard Cyganiak, Anja Jentzsch, and Vladimir Andryushechkin. 2019. Linked Open Data Cloud. http://lod-cloud.netGoogle ScholarGoogle Scholar
  14. Kash Mehdi. 2017. 4 Data Governance Best Practices to Kickstart your Data Governance Program. Blog Post. https://www.collibra.com/blog/4-data-governance-best-practicesLast Accessed: 2019-01-24.Google ScholarGoogle Scholar
  15. Ciro Baron Neto, Dimitris Kontokostas, Amit Kirschenbaum, Gustavo Correa Publio, Diego Esteves, and Sebastian Hellmann. 2017. IDOL: Comprehensive & Complete LOD Insights. In Proceedings of the 13th International Conference on Semantic Systems, SEMANTICS 2017, Amsterdam, The Netherlands, September 11-14, 2017, Rinke Hoekstra, Catherine Faron-Zucker, Tassilo Pellegrini, and Victor de Boer (Eds.). ACM, 49–56. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Open Knowledge Foundation. {n. d.}. The Open Definition. http://opendefinition.org. Accessed: 2017-12-15.Google ScholarGoogle Scholar
  17. Silvio Peroni. 2016. Media type as Linked Open Data. http://www.sparontologies.net/mediatype/.Google ScholarGoogle Scholar
  18. Victor Rodriguez-Doncel, Serena Villata, and Asuncion Gomez-Perez. 2014. A dataset of RDF licenses. In Legal Knowledge and Information Systems - JURIX 2014: The Twenty-Seventh Annual Conference, Jagiellonian University, Krakow, Poland, 10-12 December 2014(Frontiers in Artificial Intelligence and Applications), Rinke Hoekstra (Ed.). Vol. 271. IOS Press, 187–188.Google ScholarGoogle Scholar
  19. Max Schmachtenberg, Christian Bizer, and Heiko Paulheim. 2014. Adoption of the Linked Data Best Practices in Different Topical Domains. In 13th Int. Semantic Web Conf.(Lecture Notes in Computer Science), Peter Mika, Tania Tudorache, Abraham Bernstein, Chris Welty, Craig A Knoblock, Denny Vrandecic, Paul T Groth, Natasha F Noy, Krzysztof Janowicz, and Carole A Goble (Eds.). Vol. 8796. Springer, 245–260. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Is the LOD cloud at risk of becoming a museum for datasets? Looking ahead towards a fully collaborative and sustainable LOD cloud
        Index terms have been assigned to the content through auto-classification.

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          WWW '19: Companion Proceedings of The 2019 World Wide Web Conference
          May 2019
          1331 pages
          ISBN:9781450366755
          DOI:10.1145/3308560

          Copyright © 2019 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 13 May 2019

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate1,899of8,196submissions,23%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format .

        View HTML Format