• Philipp Cimiano
  • Christian Chiarcos
  • John P. McCrae
  • Jorge Gracia


Digital language resources, comprising spoken and written material, are key to many fields, including linguistics research, lexicography, typology, the study of minority or extinct languages, but also to the development of machine-learned models for automated natural language processing (NLP). Language resources are thus an important cultural asset that need not only to be preserved, we need to also make sure that these resources can be reused as much as possible. In particular, a crucial issue is to maximize secondary reuse of language resources, that is ensuring that the data can be used by others for a different purpose than it was originally collected for. However, secondary reuse is in many cases hindered by a number of proprietary choices made by the data collector. Language resources (dictionaries, terminologies, corpora, etc.) developed in the fields of corpus linguistics, computational linguistics and natural language processing (NLP) are often encoded in heterogeneous formats and developed in isolation from one another. This makes their discovery, reuse and integration for both the development of NLP tools and daily linguistic research a difficult and cumbersome task. In order to alleviate such an issue and to enhance interoperability of language resources on the Web, a community of language technology experts and practitioners has started adopting techniques coming from the field of linked data (LD). The LD paradigm emerged as a series of best practices and principles for exposing, sharing and connecting data on the Web.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Semantic Computing GroupBielefeld UniversityBielefeldGermany
  2. 2.Angewandte ComputerlinguistikGoethe-UniversityFrankfurt am MainGermany
  3. 3.Insight Centre for Data AnalyticsNational University of IrelandGalwayIreland
  4. 4.Aragon Institute of Engineering Research (I3A)University of ZaragozaZaragozaSpain

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