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New Trends of Research in Ontologies and Lexical Resources pp 7–25Cite as

Towards Open Data for Linguistics: Linguistic Linked Data

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Abstract

‘Open Data’ has become very important in a wide range of fields. However for linguistics, much data is still published in proprietary, closed formats and is not made available on the web. We propose the use of linked data principles to enable language resources to be published and interlinked openly on the web, and we describe the application of this paradigm to the modeling of two resources, WordNet and the MASC corpus. Here, WordNet and the MASC corpus serve as representative examples for two major classes of linguistic resources, lexical-semantic resources and annotated corpora, respectively.Furthermore, we argue that modeling and publishing language resources as linked data offers crucial advantages as compared to existing formalisms. In particular, it is explained how this can enhance the interoperability and the integration of linguistic resources. Further benefits of this approach include unambiguous identifiability of elements of linguistic description, the creation of dynamic, but unambiguous links between different resources, the possibility to query across distributed resources, and the availability of a mature technological infrastructure. Finally, recent community activities are described.

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Notes

  1. 1.

    The term ‘resource’ is ambiguous here. As understood in this chapter, resources are structured collections of data which can be represented, for example, in RDF. Hence, we prefer the terms ‘node’ or ‘concept’ whenever RDF resources are meant.

  2. 2.

    We provide a SPARQL endpoint under http://monnetproject.deri.ie/lemonsource_query, which provides access to the examples discussed in this chapter.

  3. 3.

    http://www.wordnet.princeton.edu

  4. 4.

    http://www.tagmatica.fr/lmf/LMF_revision_14_In_OWL29october2007.xml

  5. 5.

    http://en.wiktionary.org/

  6. 6.

    www.anc.org/MASC

  7. 7.

    Other domains where the linked data principles have been applied, include, e.g., geography [20], biomedicine [1], cultural history (http://www.europeana.eu) or government data (e.g., http://data.gov and http://data.gov.uk).

  8. 8.

    For example, the W3C Semantic Web Activity reported on developments for Media Resources, Data Provenance and Microdata in the first 2 weeks of February 2012

  9. 9.

    http://www4.wiwiss.fu-berlin.de/bizer/berlinsparqlbenchmark

  10. 10.

    Examples include http://swoogle.umbc.edu, http://www.sindice.net, http://swse.deri.ie, and http://watson.kmi.open.ac.uk.

  11. 11.

    http://linguistics.okfn.org

  12. 12.

    http://wiki.okfn.org/Wg/linguistics

  13. 13.

    http://linguistics.okfn.org/llod

  14. 14.

    http://www.w3.org/community/ontolex

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Acknowledgements

The work of Christian Chiarcos was supported by a postdoc fellowship of the German Academic Exchange Service (DAAD). The work of John McCrae and Philipp Cimiano was developed in the context of the Monnet project, which is funded by the European Union FP7 program under grant number 248458 and the CITEC excellence initiative funded by the DFG (Deutsche Forschungsgemeinschaft). Christiane Fellbaum’s work is supported by a grant from the U.S. National Science Foundation (CNS 0855157). We would also like to thank Nancy Ide and two anonymous reviewers for valuable comments and feedback.

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Authors and Affiliations

  1. Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA

    Christian Chiarcos

  2. Semantic Computing Group, Cognitive Interaction Technology Center of Excellence (CITEC), University of Bielefeld, Bielefeld, Germany

    John McCrae & Philipp Cimiano

  3. Computer Science Department, Princeton University, Princeton, NJ, USA

    Christiane Fellbaum

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  1. Christian Chiarcos
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Correspondence to Christian Chiarcos .

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Editors and Affiliations

  1. Psychology Department, Carnegie Mellon University, Forbes Avenue 5000, Pittsburgh, 15213, Pennsylvania, USA

    Alessandro Oltramari

  2. Faculty of Arts, Language, Cognition and, Vrije University Amsterdam, De Boelelaan 1105, Amsterdam, 1081, Netherlands

    Piek Vossen

  3. Department of Computing, Hong Kong Polytechnic University, PQ806 Mong Man Wai Building, Hong Kong, 999077, Hong Kong SAR

    Lu Qin

  4. Language Technologies Institute, Carnegie Mellon University, Forbes Avenue 5000, Marina Del Rey, 15213, Pennsylvania, USA

    Eduard Hovy

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Chiarcos, C., McCrae, J., Cimiano, P., Fellbaum, C. (2013). Towards Open Data for Linguistics: Linguistic Linked Data. In: Oltramari, A., Vossen, P., Qin, L., Hovy, E. (eds) New Trends of Research in Ontologies and Lexical Resources. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31782-8_2

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