Linked Data as a Cornerstone of Linguistic Data Science

Abstract

At present, we are witnessing incredible advancements in language technologies, natural language processing, and related fields, mostly stimulated by the success of deep learning technologies and the increasing availability of huge amounts of textual data on the Web. Algorithms and models that were commonly used a few years ago are rapidly substituted by newer, more effective ones, with little time for researchers and practitioners to adapt to them. In such an evolving and challenging scenario, what is the role of linguistic data science? We understand linguistic data science as a subfield of data science which focuses on the systematic analysis and study of the structure and properties of linguistic data at a large scale, along with methods and techniques to extract new knowledge and insights from it. To that end, it is necessary to provide a formal basis to the analysis, representation, integration, and exploitation of such data at their different levels (syntax, morphology, lexicon, etc.).