1 Language Resources and Linked Data: A Practical Perspective Jorge Gracia 1( B ) , Daniel Vila-Suero 1 , John P. McCrae 2 , Tiziano Flati 3 , Ciro Baron 4 , and Milan Dojchinovski 5 Ontology Engineering Group, Universidad Polit´ecnica de Madrid, Madrid, Spain {jgracia,dvila}@upm.es 2 CITEC, University of Bielefeld, Bielefeld, Germany jmccrae@cit-ec.uni-bielefeld.de 3 LCL, Sapienza Universit`a di Roma, Roma, Italy flati@di.uniroma1.it 4 AKSW, University of Leipzig, Leipzig, Germany cbaron@informatik.uni-leipzig.de 5 Czech Technical University in Prague, Praha, Czech Republic milan.dojchinovski@fit.cvut.cz Abstract. Recently, experts and practitioners in language resources have started recognizing the benefits of the linked data (LD) paradigm for the representation and exploitation of linguistic data on the Web. The adoption of the LD principles is leading to an emerging ecosystem of multilingual open resources that conform to the Linguistic Linked Open Data Cloud, in which datasets of linguistic data are interconnected and represented following common vocabularies, which facilitates linguistic information discovery, integration and access. In order to contribute to this initiative, this paper summarizes several key aspects of the represen- tation of linguistic information as linked data from a practical perspec- tive. The main goal of this document is to provide the basic ideas and tools for migrating language resources (lexicons, corpora, etc.) as LD on the Web and to develop some useful NLP tasks with them (e.g., word sense disambiguation). Such material was the basis of a tutorial imparted at the EKAW’14 conference, which is also reported in the paper. 1 Introduction Linked data (LD) is a set of best practices for exposing, sharing, and connecting data on the Web [2]. Recently, researchers working on linguistic resources have shown increasing interest in publishing their data as LD [4]. Nowadays, there are many good examples involving important organizations and initiatives that stress the opportunities offered by LD and foster the aggregation of multilingual open resources into the Linked Open Data (LOD) cloud. By interlinking multilingual