Proceedings of the LREC 2020 7th Workshop on Linked Data in Linguistics

Past years have seen a growing interest in the application of knowledge graphs and Semantic Web technologies to language resources, and their publication as linked data on the Web. As of today, a large amount of language resources were either converted or created natively as linked data on the basis of data models specifically designed for the representation of linguistic content. Examples are wordnets, dictionaries, corpora, culminating in the emergence of a Linguistic Linked Open Data (LLOD) cloud (http://linguistic-lod.org/).
Since its establishment in 2012, the Linked Data in Linguistics (LDL) workshop series has become the major forum for presenting, discussing and disseminating technologies, vocabularies, resources and experiences regarding the application of semantic technologies and the Linked Open Data (LOD) paradigm to language resources in order to facilitate their visibility, accessibility, interoperability, reusability, enrichment, combined evaluation and integration. The LDL workshops contribute to the discussion, dissemination and establishment of community standards that drive this development, most notably the OntoLex-lemon model for lexical resources, as well as standards for other types of language resources still under development.
The workshop series is organized by Open Linguistics, founded 2010 as a Working Group of the Open Knowledge Foundation with close involvement of related communities, such as W3C Community Groups, and international research projects. It takes a general focus on LOD-based resources, vocabularies, infrastructures and technologies as means for managing, improving and using language resources on the Web. As technology and resources increasingly converge towards a LOD based ecosystem, this year we particularly encouraged submissions on Linked-Data Aware Tools and Services and Linked Language Resources Infrastructure, i.e. managing, curating and applying LLOD technologies and resources in a reliable and reproducible way for the needs of linguistics, NLP and digital humanities.