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DBpedia Mashups

  • Chapter
Semantic Mashups

Abstract

If you see Wikipedia as a main place where the knowledge of mankind is concentrated, then DBpedia—which is extracted from Wikipedia—is the best place to find the machine representation of that knowledge. DBpedia constitutes a major part of the semantic data on the web. Its sheer size and wide coverage enables you to use it in many kind of mashups: it contains biographical, geographical, bibliographical data; as well as discographies, movie metadata, technical specifications, and links to social media profiles and much more. Just like Wikipedia, DBpedia is a truly cross-language effort, e.g., it provides descriptions and other information in various languages. In this chapter we introduce its structure, contents, and its connections to outside resources. We describe how the structured information in DBpedia is gathered, what you can expect from it and what are its characteristics and limitations. We analyze how other mashups exploit DBpedia and present best practices of its usage. In particular, we describe how Sztakipedia—an intelligent writing aid based on DBpedia—can help Wikipedia contributors to improve the quality and integrity of articles. DBpedia offers a myriad of ways to accessing the information it contains, ranging from SPARQL to bulk download. We compare the pros and cons of these methods. We conclude that DBpedia is an unavoidable resource for applications dealing with commonly known entities like notable persons, places; and for others looking for a rich hub connecting other semantic resources.

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Notes

  1. 1.

    Since 2007, see http://stats.wikimedia.org/EN/#see_also.

  2. 2.

    http://dbpedia.org.

  3. 3.

    http://en.wikipedia.org/wiki/Wikipedia:Notability.

  4. 4.

    http://owl.man.ac.uk/factplusplus/.

  5. 5.

    http://www.w3.org/TR/owl-features/.

  6. 6.

    As of August 2012. For more details, see: http://wiki.dbpedia.org/Dataset.

  7. 7.

    http://www.freebase.com/.

  8. 8.

    Metaweb Technologies, Inc. It has been acquired by Google in 2010.

  9. 9.

    Especially the notability test: https://en.wikipedia.org/wiki/Wikipedia:Notability.

  10. 10.

    http://wiki.freebase.com/wiki/WEX.

  11. 11.

    http://www.wikidata.org.

  12. 12.

    http://wiki.dbpedia.org/DBpediaMobile.

  13. 13.

    http://www4.wiwiss.fu-berlin.de/flickrwrappr/.

  14. 14.

    http://graphics.stanford.edu/projects/vispedia/.

  15. 15.

    http://www.iais.fraunhofer.de/contentus.html.

  16. 16.

    For a screencast see: http://www.yovisto.com/labs/vissw2011/.

  17. 17.

    Deutsche Nationalbibliothek—DNB.

  18. 18.

    Personennamendatei—PND.

  19. 19.

    http://swse.deri.org/.

  20. 20.

    http://dbrec.net/.

  21. 21.

    http://revyu.com/.

  22. 22.

    http://stanbol.apache.org/.

  23. 23.

    http://www.opencalais.com/.

  24. 24.

    http://logd.tw.rpi.edu/demo/white-house-visit/search.

  25. 25.

    http://www.ae-info.org/.

  26. 26.

    http://faviki.com/.

  27. 27.

    If you want to do your own research, use Google Scholar and search for “DBpedia: a nucleus for a web of open data” and “DBpedia—a crystallization point for the Web of Data”. The two articles together received a remarkable 1,300 citations to date.

  28. 28.

    http://www.w3.org/TR/rdf-sparql-query/.

  29. 29.

    http://wiki.dbpedia.org/OnlineAccess.

  30. 30.

    http://virtuoso.openlinksw.com/.

  31. 31.

    More precisely it has a free version, besides the enterprise plan.

  32. 32.

    http://www.openlinksw.com/dataspace/dav/wiki/Main/VirtAWSPublicDataSets.

  33. 33.

    See literature on information extraction.

  34. 34.

    http://dbpedia.org/spotlight.

  35. 35.

    http://spotlight.dbpedia.org/gsoc/.

  36. 36.

    In the early stage of Sztakipedia project our team also developed a TinyMCE-based editor, but that is discontinued now.

  37. 37.

    tf-idf is a widely used statistical relevance measure. For details, see [23].

  38. 38.

    http://pedia.sztaki.hu/.

  39. 39.

    UIMA stands for Unstructured Information Management Architecture. It is a modular framework for annotating content. For more details, see http://uima.apache.org/.

  40. 40.

    http://lucene.apache.org.

  41. 41.

    These are the old and new machine interface standards supported by most library systems.

  42. 42.

    http://live.dbpedia.org/.

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Acknowledgements

We are deeply indebted to Domonkos Tikk and Pablo Mendes for their valuable comments on the text. The authors were partially supported by the grant TÁMOP-4.2.2.B-10/1-2010-0009 of the Hungarian National Development Agency (NFÜ).

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  1. Institute for Computer Science and Control (SZTAKI), Hungarian Academy of Sciences (MTA), Budapest, Hungary

    Mihály Héder & Illés Solt

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  1. Mihály Héder
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Correspondence to Mihály Héder .

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    Brigitte Endres-Niggemeyer

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Héder, M., Solt, I. (2013). DBpedia Mashups. In: Endres-Niggemeyer, B. (eds) Semantic Mashups. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36403-7_4

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  • DOI: https://doi.org/10.1007/978-3-642-36403-7_4

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