The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study. Table of Contents: List of Figures / Introduction / Principles of Linked Data / The Web of Data / Linked Data Design Considerations / Recipes for Publishing Linked Data / Consuming Linked Data / Summary and Outlook

Linked Data opens up structured data from databases to be searched and queried via the web, and a geographic element is increasingly being used to link to those data. This book helps you understand how to organize and describe data that includes geographic content and how to publish it as Linked Data for the Semantic Web, as well as explaining the benefits of doing so. In easy-to-understand terms, it equips you with the knowledge you need to think about Geographic Information through the lens of the Semantic Web.

This dissertation addresses several problems in the context of publishing and consuming Linked Data. It describes these problems from the perspectives of three stakeholders: the Linked Data provider, developer and scientist. The Linked Data provider is faced with impractical data re-use and costly Linked Data hosting solutions. Developers face difficulties in finding, navigating and using Linked Datasets. Scientists lack the resources and methods to evaluate their work on Linked Data at large. This dissertation presents a number of novel approaches that address these issues, such as: - The LOD Laundromat: a centralized service that re-publishes cleaned, queryable and structurally annotated Linked Datasets. In 2015 the Laundromat was awarded first prize in the Dutch national Linked Open Data competition, and third prize in the European equivalent; - SampLD: A relevance-based sampling algorithm that enables publishers to decrease Linked Data hosting costs; - YASGUI: A feature-rich query editor for accessing SPARQL endpoints; - LOD Lab: An evaluation paradigm that enables scientists to increase the breadth and scale of their Linked Data evaluations. This work provides a unique overview of problems related to publishing and consuming Linked Data. The novel approaches presented here improve the state-of-the-art for Linked Data publishers, developers and scientists, and are a step towards a web of Linked Data that is more accessible and technically scalable.

Resource Description and Access, and Library of Congress s commitment to a new bibliographic framework all point toward opportunities for shared, linked library data. In this issue of Library Technology Reports, Karen Coyle updates readers on the development of fundamental resources such as standards, data elements, and term lists, showing how they fit together. In clear, straightforward language, she introduces common Semantic Web terminology and acronyms, like RDF, triples, SKOS, OWL, and SPARQL, showing readers how to locate defined metadata elements on the Web. Coyle lists and describes 20 sources of general use data elements to use, from ISBD elements to Facebook s Open Graph, also describing numerous examples of topical lists suited to linking with library data, including subject lists, thesauri, and other controlled vocabularies. For developers and programmers, Coyle describes emerging tools that facilitate data element creation, validation of Semantic Web structures, link creation, and linked data searching.

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.

This book examines the recent evolution of the concept of data as an economic and managerial phenomenon. The author first describes and discusses open data and then introduces the concept of linked data, with a focus on assets for reuse. Furthermore, he addresses the main challenges of big data. Value is identified as the main incentive for the adoption of linked data; accordingly, the next two chapters study sources of data value from a macroeconomic and micro economic perspective, respectively. This contributes to the systematization of important issues at the crossroads of enterprise data and data sharing: data ownership, personal data, and data privacy. In turn, the book reveals the role of innovation as a main vehicle for creating value by unifying big, open, and linked data. It studies the ways in which value can be created, transferred, and captured in the form of business models, before the closing chapter verifies the data unification model by combining open and linked geographical data with big data from a major telecom company.

Linked Data Management presents techniques for querying and managing Linked Data that is available on today's Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to L

This book provides a comprehensive overview of core concepts and technological foundations for continuous engineering of Web streams. It presents various systems and applications and includes real-world examples. Last not least, it introduces the readers to RSP4J, a novel open-source project that aims to gather community efforts in software engineering and empirical research. The book starts with an introductory chapter that positions the work by explaining what motivates the design of specific techniques for processing data streams using Web technologies. Chapter 2 briefly summarizes the necessary background concepts and models needed to understand the remaining content of the book. Subsequently, chapter 3 focuses on processing RDF streams, taming data velocity in an open environment characterized by high data variety. It introduces query answering algorithms with RSP-QL and analytics functions over streaming data. Chapter 4 presents the life cycle of streaming linked data, it focuses on publishing streams on the Web as a prerequisite aspect to make data findable and accessible for applications. Chapter 5 touches on the problems of benchmarks and systems that analyze Web streams to foster technological progress. It surveys existing benchmarks and introduces guidelines that may support new practitioners in approaching the issue of continuous analytics. Finally, chapter 6 presents a list of examples and exercises that will help the reader to approach the area, get used to its practices and become confident in its technological possibilities. Overall, this book is mainly written for graduate students and researchers in Web and stream data management. It collects research results and will guide the next generation of researchers and practitioners.

The explosion of information technology has led to substantial growth of web-accessible linguistic data in terms of quantity, diversity and complexity. These resources become even more useful when interlinked with each other to generate network effects. The general trend of providing data online is thus accompanied by newly developing methodologies to interconnect linguistic data and metadata. This includes linguistic data collections, general-purpose knowledge bases (e.g., the DBpedia, a machine-readable edition of the Wikipedia), and repositories with specific information about languages, linguistic categories and phenomena. The Linked Data paradigm provides a framework for interoperability and access management, and thereby allows to integrate information from such a diverse set of resources. The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories. The book includes representative applications from diverse fields, ranging from academic linguistics (e.g., typology and corpus linguistics) over applied linguistics (e.g., lexicography and translation studies) to technical applications (in computational linguistics, Natural Language Processing and information technology). This volume accompanies the Workshop on Linked Data in Linguistics 2012 (LDL-2012) in Frankfurt/M., Germany, organized by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation (OKFN). It assembles contributions of the workshop participants and, beyond this, it summarizes initial steps in the formation of a Linked Open Data cloud of linguistic resources, the Linguistic Linked Open Data cloud (LLOD).

In recent years, an increasing number of organizations and individuals have contributed to the Semantic Web by publishing data according to the Linked Data principles. In addition, a significant body of Semantic Web research exists that studies various aspects of knowledge representation and automated reasoning over collections of such data. However, a challenge that is crucial for achieving the vision of a Semantic Web – but that has not yet been studied to a comparable extent – is to enable automated software agents to operate directly on decentralized Linked Data that is distributed over the WWW. In particular, fundamental questions related to querying this data on the WWW have received very limited research attention. This book contributes towards filling this gap by studying the foundations of declarative queries over Linked Data on the WWW. Our particular focus in this book are approaches to use the SPARQL query language and execute queries by traversing Linked Data live during the query execution process. More specifically, we first provide formal foundations to adapt SPARQL to the given context. Thereafter, we use an abstract machine model to formally show computational feasibility and related properties of the resulting types of SPARQL queries. Additionally, we investigate fundamental properties of applying the traversal-based approach to query execution that is tailored to the use case of querying Linked Data directly on the WWW.