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Linked data --- Semantic Web --- Semantic computing --- Data, Linked --- Linked open data --- LOD (Linked data) --- Open linked data --- Opendata, Linked --- Metadata --- Uniform Resource Identifiers --- Computer science --- Electronic data processing --- Semantics --- Library linked data --- Open data, Linked

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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 addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and “standard” data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.

Computer science. --- Management information systems. --- Data mining. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Data Mining and Knowledge Discovery. --- Information Systems Applications (incl. Internet). --- Business Information Systems. --- Knowledge representation (Information theory) --- Linked data. --- Data, Linked --- Linked open data --- LOD (Linked data) --- Open linked data --- Opendata, Linked --- Representation of knowledge (Information theory) --- Metadata --- Semantic Web --- Uniform Resource Identifiers --- Artificial intelligence --- Information theory --- Artificial Intelligence. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- 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 --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Communication systems --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrir̈e, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zinn.

Language and languages --- Linked data. --- Study and teaching. --- Research. --- Data, Linked --- Linked open data --- LOD (Linked data) --- Open linked data --- Opendata, Linked --- Metadata --- Semantic Web --- Uniform Resource Identifiers --- Foreign languages --- Languages --- Anthropology --- Communication --- Ethnology --- Information theory --- Meaning (Psychology) --- Philology --- Linguistics --- Foreign language study --- Language and education --- Language schools --- Open data, Linked --- Library linked data --- Language and languages Study and teaching --- Study and teaching --- open source --- open data --- open knowledge --- open access --- open science --- Language data and metadata --- Linguistic Linked Open Data --- research data management --- sustainability --- interoperability --- language acquisition --- linguistic annotation --- multilingualism --- communities of practice --- data-intensive research --- CHILDES --- Data Transcription and AnalysisTool --- digital curation --- preservation --- and scholarship --- knowledge infrastructure --- linguistic ontology --- linked data cloud --- metadata interchange --- metatagging --- morphosyntax --- multimedia --- Open Linguistics Working Group --- phonological development --- RDF --- standards --- stewardship --- TALKBANK --- terminology --- under-resourced languages

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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