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Having achieved popularity as a way of publishing and accessing data in different fields of the sciences and for sharing large encyclopaedic datasets such as DBpedia (derived from Wikipedia), linked data is becoming more and more popular in different areas of the humanities. In this course we will present a comprehensive introduction to the creation, publication, and use of linked open data for anyone who wants to work with linguistic datasets – such as lexicons and corpora – and especially for those who come from a linguistic or humanist background. We will look at the basics of linked data and the Semantic Web and introduce the various different standards technologies that make up the Semantic Web stack before focusing on the particular case of linked data language resources. During the course we will study the most important tools, vocabularies, and resources available in the Semantic Web and provide hands-on training for the creation and querying of linguistic linked data. We will look at how Semantic Web technologies can contribute to the creation of FAIR language resources as well as how to publish your resource on the linked open data cloud. We will also show how the Semantic Web query language SPARQL can be a powerful tool for data exploration.
CLARIN, Open Data, Linked Data, FOS: Languages and literature, Training, Linguistics, Research Infrastructures, Linguistic Linked Open Data
CLARIN, Open Data, Linked Data, FOS: Languages and literature, Training, Linguistics, Research Infrastructures, Linguistic Linked Open Data
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |