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This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.

Knowledge representation (Information theory) . --- Natural language processing (Computer science). --- Application software. --- Knowledge based Systems. --- Natural Language Processing (NLP). --- Computer Appl. in Arts and Humanities. --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Representation of knowledge (Information theory) --- Information theory --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Semantic computing. --- Linked data. --- Data, Linked --- Linked open data --- LOD (Linked data) --- Open linked data --- Opendata, Linked --- Metadata --- Semantic Web --- Uniform Resource Identifiers --- Computer science --- Semantics --- Library linked data --- Open data, Linked

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This book constitutes the thoroughly refereed proceedings of the 7th Joint International Semantic Technology Conference, JIST 2017, held in Goldcoast, QLD, Australia, in November 2017.  The 19 full papers and 4 short papers presented were carefully reviewed and selected from 37 submissions. They present applications of semantic technologies, theoretical results, new algorithms and tools to facilitate the adoption of semantic technologies and are organized in topical sections on ontology and data management; ontology reasoning; linked data and query; information retrieval and knowledge discovery; knowledge graphs; and applications of semantic technologies.

Computer science. --- Mathematical logic. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Application software. --- Computer Science. --- Information Storage and Retrieval. --- Artificial Intelligence (incl. Robotics). --- Information Systems Applications (incl. Internet). --- Data Mining and Knowledge Discovery. --- Mathematical Logic and Formal Languages. --- Computer Appl. in Administrative Data Processing. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Informatics --- Computer software --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Database searching --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Science --- Information storage and retrieva. --- Information systems. --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Semantic computing --- Linked data --- Semantic Web --- Data, Linked --- Library linked data --- Linked open data --- LOD (Linked data) --- Open linked data --- Open data, Linked --- Metadata --- Uniform Resource Identifiers --- Computer science --- Semantics

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This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

Linked data. --- Semantic Web. --- Computer science. --- Computers. --- Information storage and retrieval. --- Artificial intelligence. --- Computer Science. --- Models and Principles. --- Artificial Intelligence (incl. Robotics). --- Information Storage and Retrieval. --- Semantic integration (Computer systems) --- Semantic networks (Information theory) --- World Wide Web --- Microformats --- Data, Linked --- Linked open data --- LOD (Linked data) --- Open linked data --- Opendata, Linked --- Metadata --- Semantic Web --- Uniform Resource Identifiers --- Information storage and retrieva. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace