Home » Daniel Vila-Suero
Researcher, Ontology Engineering Group, UPM
Daniel Vila-Suero is a PhD candidate, researcher and developer at the Ontology Engineering Group (OEG), in the Universidad Politecnica de Madrid. He holds MsC in Computer Science from the . His research topics are multilingualism in the Web of Data, digital libraries, methodologies and Linked Data. He participated in the Spanish research projects related to Linked Data and multilingualism datos.bne.es and BabeLData as well as in several standardization groups of the W3C and IFLA. Currently, he is involved in the EU project Lider (http://www.lider-project.eu/).
3LD: Towards high quality, industry-ready Linguistic Linked Licensed Data
The application of Linked Data technology to the publication of linguistic data promises to facilitate interoperability of these data and has lead to the emergence of the so called Linguistic Linked Data Cloud (LLD) in which linguistic data is published following the Linked Data principles. Three essential issues need to be addressed for such data to be easily exploitable by language technologies: i) appropriate machine-readable licensing information is needed for each dataset, ii) minimum quality standards for Linguistic Linked Data need to be defined, and iii) appropriate vocabularies for publishing Linguistic Linked Data resources are needed. We propose the notion of Licensed Linguistic Linked Data (3LD) in which different licensing models might co-exist, from totally open to more restrictive licenses through to completely closed datasets.