Linguistic Linked Open Data is a topic of emerging importance in the field of natural language processing (NLP). Increasingly, researchers are rendering major linguistic resources, including annotated corpora, lexicons, databases, and ontologies, in a format to enable their exploitation in the Semantic Web. Linking the contents of these resources to each other as well as to common ontologies can enable access to and discovery of detailed linguistic information, which would be otherwise impossible, and which could, in turn, foster a major leap in NLP research and development. At the same time, the movement toward open data is growing in the field of NLP. For years, research has been constrained by limited access to corpora, lexicons, and other language resources due to licensing requirements. Researchers and data holders alike are now seeking ways to provide open access to these data in order to promote unfettered use, reuse, and enhancement of common datasets throughout the field.
EUROLAN 2015 will provide a comprehensive overview of Linguistic Linked Open Data, including introduction to the formalisms for representing linguistic resources using Semantic Web technologies such as the Resource Description Format (RDF) and the Ontology Web Language (OWL), as well as means to extract knowledge from language resources and exploit it using Semantic Web query languages and reasoning capabilities.Specific topics treated in the school include, but are not limited to:
- Introduction to the semantic web, linked data and knowledge graphs
- Extracting and integrating knowledge on the web from text, semi-structured and structured data
- Ontologies and reasoning
- Query systems using SPARQL
- Design of domain specific query languages
- Linguistic annotations as linked data
- Annotation interoperability
- Taxonomy extraction
- BabelNet as linked data
- Lexicographic linked data
