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Browsing Linked Data Catalogs with LODAtlas

  • Emmanuel Pietriga
  • Hande Gözükan
  • Caroline Appert
  • Marie Destandau
  • Šejla Čebirić
  • François Goasdoué
  • Ioana Manolescu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11137)

Abstract

The Web of Data is growing fast, as exemplified by the evolution of the Linked Open Data (LOD) cloud over the last ten years. One of the consequences of this growth is that it is becoming increasingly difficult for application developers and end-users to find the datasets that would be relevant to them. Semantic Web search engines, open data catalogs, datasets and frameworks such as LODStats and LOD Laundromat, are all useful but only give partial, even if complementary, views on what datasets are available on the Web. We introduce LODAtlas, a portal that enables users to find datasets of interest. Users can make different types of queries about both the datasets’ metadata and contents, aggregated from multiple sources. They can then quickly evaluate the matching datasets’ relevance, thanks to LODAtlas’ summary visualizations of their general metadata, connections and contents.

Keywords

Linked Data Catalogs Dataset Search Visualization 

References

  1. 1.
    Abele, A., McCrae, J.P., Buitelaar, P., Jentzsch, A., Cyganiak, R.: Linking Open Data cloud diagram (2017). http://lod-cloud.net
  2. 2.
    Alexander, K., Cyganiak, R., Hausenblas, M., Zhao, J.: Describing Linked Datasets with the VoID Vocabulary. W3C Interest Group Note, March 2011. https://www.w3.org/TR/void/
  3. 3.
    public-lod@w3.org thread datahub.io, February 2018. https://lists.w3.org/Archives/Public/public-lod/2018Feb/0001.html
  4. 4.
    Bach, B., Pietriga, E., Fekete, J.D.: Graphdiaries: animated transitions and temporal navigation for dynamic networks. IEEE Trans. Vis. Comput. Graph. 20(5), 740–754 (2014).  https://doi.org/10.1109/TVCG.2013.254CrossRefGoogle Scholar
  5. 5.
    Beek, W., Rietveld, L., Bazoobandi, H.R., Wielemaker, J., Schlobach, S.: LOD laundromat: a uniform way of publishing other people’s dirty data. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 213–228. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-11964-9_14CrossRefGoogle Scholar
  6. 6.
    Beek, W., Rietveld, L., Schlobach, S., van Harmelen, F.: LOD Laundromat: why the semantic web needs centralization (Even If We Don’T Like It). IEEE Internet Comput. 20(2), 78–81 (2016).  https://doi.org/10.1109/MIC.2016.43CrossRefGoogle Scholar
  7. 7.
    Benedetti, F., Bergamaschi, S., Po, L.: Visual querying lod sources with lodex. In: Proceedings of the International Conference on Knowledge Capture, K-CAP 2015, pp. 12:1–12:8. ACM (2015).  https://doi.org/10.1145/2815833.2815849
  8. 8.
    Berners-Lee, T., et al.: Tabulator: exploring and analyzing linked data on the Semantic Web. In: Proceedings of the 3rd international Semantic Web User Interaction Workshop (2006)Google Scholar
  9. 9.
    Bernstein, A., Hendler, J., Noy, N.: A new look at the semantic web. Commun. ACM 59(9), 35–37 (2016).  https://doi.org/10.1145/2890489CrossRefGoogle Scholar
  10. 10.
    Bostock, M., Ogievetsky, V., Heer, J.: D3: Data-driven documents. IEEE Trans. Vis. Comput. Graph. 17(12), 2301–2309 (2011).  https://doi.org/10.1109/TVCG.2011.185CrossRefGoogle Scholar
  11. 11.
    Čebirić, Š., Goasdoué, F., Manolescu, I.: A framework for efficient representative summarization of RDF graphs. In: ISWC (Posters & Demonstrations) (2017). http://ceur-ws.org/Vol-1963/paper512.pdf
  12. 12.
    Čebirić, Š., Goasdoué, F., Manolescu, I.: Query-Oriented Summarization of RDF Graphs. Research Report RR-8920, INRIA (2017). https://hal.inria.fr/hal-01325900
  13. 13.
    Chen, J., Ludwig, M., Ma, Y., Walther, D.: Zooming in on ontologies: minimal modules and best excerpts. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 173–189. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68288-4_11CrossRefGoogle Scholar
  14. 14.
    Cheng, G., Ge, W., Qu, Y.: Falcons: Searching and browsing entities on the semantic web. In: Proceedings of the International Conference on World Wide Web, pp. 1101–1102. ACM (2008).  https://doi.org/10.1145/1367497.1367676
  15. 15.
    Dadzie, A.S., Pietriga, E.: Visualisation of linked data - reprise. Semant. Web J. 8(1), 1–21 (2017).  https://doi.org/10.3233/SW-160249CrossRefGoogle Scholar
  16. 16.
    Dadzie, A.S., Rowe, M.: Approaches to visualising linked data: a survey. Semant. Web J. 2(2), 89–124 (2011).  https://doi.org/10.3233/SW-2011-0037CrossRefGoogle Scholar
  17. 17.
    d’Aquin, M., Motta, E.: Watson, more than a semantic web search engine. Semant. Web J. 2(1), 55–63 (2011).  https://doi.org/10.3233/SW-2011-0031CrossRefGoogle Scholar
  18. 18.
    Ding, L., et al.: A search and metadata engine for the semantic web. In: Proceedings of the International Conference on Information and Knowledge Management, CIKM 2004, pp. 652–659. ACM (2004).  https://doi.org/10.1145/1031171.1031289
  19. 19.
    Dudáš, M., Svátek, V., Mynarz, J.: Dataset summary visualization with LODSight. In: Gandon, F., Guéret, C., Villata, S., Breslin, J., Faron-Zucker, C., Zimmermann, A. (eds.) ESWC 2015. LNCS, vol. 9341, pp. 36–40. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-25639-9_7CrossRefGoogle Scholar
  20. 20.
    Ermilov, I., Lehmann, J., Martin, M., Auer, S.: LODStats: the data web census dataset. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9982, pp. 38–46. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-46547-0_5CrossRefGoogle Scholar
  21. 21.
    Glaser, H., Millard, I.C., Jaffri, A.: RKBExplorer.com: a knowledge driven infrastructure for linked data providers. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 797–801. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-68234-9_61CrossRefGoogle Scholar
  22. 22.
    Gottron, T., Scherp, A., Krayer, B., Peters, A.: Lodatio: using a schema-level index to support users infinding relevant sources of linked data. In: Proceedings of the International Conference on Knowledge Capture, K-CAP 2013, pp. 105–108. ACM (2013).  https://doi.org/10.1145/2479832.2479841
  23. 23.
    Hayes, P.J., Patel-Schneider, P.F.: RDF 1.1 Semantics (2014). https://www.w3.org/TR/rdf11-mt/
  24. 24.
    Hogan, A., Harth, A., Umbrich, J., Kinsella, S., Polleres, A., Decker, S.: Searching and browsing linked data with SWSE: the semantic web search engine. Web Semant. 9(4), 365–401 (2011).  https://doi.org/10.1016/j.websem.2011.06.004CrossRefGoogle Scholar
  25. 25.
    Holten, D.: Hierarchical edge bundles: visualization of adjacency relations in hierarchical data. IEEE Trans. Vis. Comput. Graph. 12(5), 741–748 (2006).  https://doi.org/10.1109/TVCG.2006.147CrossRefGoogle Scholar
  26. 26.
    Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., Hogan, A.: Observing linked data dynamics. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 213–227. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-38288-8_15CrossRefGoogle Scholar
  27. 27.
    Khatchadourian, S., Consens, M.: ExpLOD: summary-based exploration of interlinking and RDF usage in the linked open data cloud. In: Aroyo, L., et al. (eds.) ESWC 2010. LNCS, vol. 6089, pp. 272–287. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-13489-0_19CrossRefGoogle Scholar
  28. 28.
    Leka, M., Schmidt, H., Blume, T., Vagliano, I., Scherp, A.: Searching for Sources of Data on the Web with LODatio+ (2018). http://lodatio.informatik.uni-kiel.de
  29. 29.
    Mäkelä, E.: Aether – generating and viewing extended VoID statistical descriptions of RDF datasets. In: Presutti, V., Blomqvist, E., Troncy, R., Sack, H., Papadakis, I., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8798, pp. 429–433. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-11955-7_61CrossRefGoogle Scholar
  30. 30.
    Mihindukulasooriya, N., Poveda Villalon, M., Garcia-Castro, R., Gomez-Perez, A.: Loupe - an online tool for inspecting datasets in the linked data cloud. In: Proceedings of the ISWC 2015 Posters & Demonstrations Track (2015). http://ceur-ws.org/Vol-1486/paper_113.pdf
  31. 31.
    Pietriga, E., Bizer, C., Karger, D., Lee, R.: Fresnel: a browser-independent presentation vocabulary for RDF. In: Cruz, I., et al. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 158–171. Springer, Heidelberg (2006).  https://doi.org/10.1007/11926078_12CrossRefGoogle Scholar
  32. 32.
    Romat, H., Appert, C., Bach, B., Henry-Riche, N., Pietriga, E.: Animated edge textures in node-link diagrams: a design space and initial evaluation. In: Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM (2018).  https://doi.org/10.1145/3173574.3173761
  33. 33.
    Tummarello, G., Delbru, R., Oren, E.: Sindice.com: weaving the open linked data. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 552–565. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-76298-0_40CrossRefGoogle Scholar
  34. 34.
    Vandenbussche, P.Y., Atemezing, G.A., Poveda, M., Vatant, B.: Linked open vocabularies (LOV): a gateway to reusable semantic vocabularies on the web. Semant. Web J. 8(3), 437–452 (2016).  https://doi.org/10.3233/SW-160213CrossRefGoogle Scholar
  35. 35.
    Vandenbussche, P.Y., Umbrich, J., Matteis, L., Hogan, A., Buil-Aranda, C.: Sparqles: Monitoring public sparql endpoints. Semant. Web J. 8(6), 1049–1065 (2017).  https://doi.org/10.3233/SW-170254CrossRefGoogle Scholar
  36. 36.
    Wang Baldonado, M.Q., Woodruff, A., Kuchinsky, A.: Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2000, pp. 110–119. ACM (2000). https://doi.org/10.1145/345513.345271

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Emmanuel Pietriga
    • 1
  • Hande Gözükan
    • 1
  • Caroline Appert
    • 1
  • Marie Destandau
    • 1
  • Šejla Čebirić
    • 2
  • François Goasdoué
    • 2
    • 3
  • Ioana Manolescu
    • 2
  1. 1.Univ. Paris-Sud, CNRS, Inria, Université Paris-SaclayOrsayFrance
  2. 2.Inria and École PolytechniquePalaiseauFrance
  3. 3.Univ. Rennes 1RennesFrance

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