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Validating RDF Data

Author: Jose Emilio Labra Gayo

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 304

ISBN-13: 3031794788

RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange. The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models. At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints. This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications.

Validating RDF Data

Author: Jose Emilio Labra Gayo

Publisher: Morgan & Claypool Publishers

Published: 2017-09-29

Total Pages: 330

ISBN-13: 1681731657

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Learning SPARQL

Author: Bob DuCharme

Publisher: "O'Reilly Media, Inc."

Published: 2013-07-03

Total Pages: 386

ISBN-13: 1449371477

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Gain hands-on experience with SPARQL, the RDF query language that’s bringing new possibilities to semantic web, linked data, and big data projects. This updated and expanded edition shows you how to use SPARQL 1.1 with a variety of tools to retrieve, manipulate, and federate data from the public web as well as from private sources. Author Bob DuCharme has you writing simple queries right away before providing background on how SPARQL fits into RDF technologies. Using short examples that you can run yourself with open source software, you’ll learn how to update, add to, and delete data in RDF datasets. Get the big picture on RDF, linked data, and the semantic web Use SPARQL to find bad data and create new data from existing data Use datatype metadata and functions in your queries Learn techniques and tools to help your queries run more efficiently Use RDF Schemas and OWL ontologies to extend the power of your queries Discover the roles that SPARQL can play in your applications

Practical RDF

Author: Shelley Powers

Publisher: "O'Reilly Media, Inc."

Published: 2003-07-18

Total Pages: 353

ISBN-13: 0596550510

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The Resource Description Framework (RDF) is a structure for describing and interchanging metadata on the Web--anything from library catalogs and worldwide directories to bioinformatics, Mozilla internal data structures, and knowledge bases for artificial intelligence projects. RDF provides a consistent framework and syntax for describing and querying data, making it possible to share website descriptions more easily. RDF's capabilities, however, have long been shrouded by its reputation for complexity and a difficult family of specifications. Practical RDF breaks through this reputation with immediate and solvable problems to help you understand, master, and implement RDF solutions.Practical RDF explains RDF from the ground up, providing real-world examples and descriptions of how the technology is being used in applications like Mozilla, FOAF, and Chandler, as well as infrastructure you can use to build your own applications. This book cuts to the heart of the W3C's often obscure specifications, giving you tools to apply RDF successfully in your own projects.The first part of the book focuses on the RDF specifications. After an introduction to RDF, the book covers the RDF specification documents themselves, including RDF Semantics and Concepts and Abstract Model specifications, RDF constructs, and the RDF Schema. The second section focuses on programming language support, and the tools and utilities that allow developers to review, edit, parse, store, and manipulate RDF/XML. Subsequent sections focus on RDF's data roots, programming and framework support, and practical implementation and use of RDF and RDF/XML.If you want to know how to apply RDF to information processing, Practical RDF is for you. Whether your interests lie in large-scale information aggregation and analysis or in smaller-scale projects like weblog syndication, this book will provide you with a solid foundation for working with RDF.

The Web of Data

Author: Aidan Hogan

Publisher: Springer Nature

Published: 2020-09-09

Total Pages: 689

ISBN-13: 303051580X

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This book’s main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to – and how they have been used thus far on – the “Web of Data”. As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, “Web of Data” provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. “Resource Description Framework (RDF)” describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on “RDF Schema (RDFS) and Semantics” presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter “Web Ontology Language (OWL)” elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In “SPARQL Query Language” a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. “Shape Constraints and Expressions (SHACL/ShEx)” introduces two languages for describing the expected structure of – and expressing constraints on – RDF graphs for the purposes of validation. “Linked Data” discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.

Knowledge Graphs

Author: Aidan Hogan

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 247

ISBN-13: 3031019180

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This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.

Current Trends in Semantic Web Technologies: Theory and Practice

Author: Giner Alor-Hernández

Publisher: Springer

Published: 2019-01-17

Total Pages: 292

ISBN-13: 3030061493

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This book presents innovative and high-quality research regarding the implementation of Semantic Web technologies for knowledge representation and developing intelligent applications in various domains. Semantic Web technologies have inspired many people to create innovative technologies and applications for knowledge representation, Semantic Searches, NLP and Social Networks. The goal of this book is to collect and consolidate novel and high-quality research contributions on Semantic Web technologies and their theoretical and practical application to a range of different domains. In addition to researchers, the book offers a valuable resource for PhD students, master and undergraduate students in IT-related fields such as Computer Science and Information Systems.

Learning SPARQL

Author: Bob DuCharme

Publisher: "O'Reilly Media, Inc."

Published: 2011-07-21

Total Pages: 255

ISBN-13: 1449306594

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"More and more people are using the query language SPARQL (pronounced 'sparkle') to pull data from a growing collection of public and private data. Whether this data is part of a semantic web project or an integration of two inventory databases on different platforms behind the same firewall, SPARQL is making it easier to access this data using both open source and commercial software. In the words of W3C Director and web inventor Tim Berners-Lee, 'Trying to use the Semantic Web without SPARQL is like trying to use a relational database without SQL. SPARQL lets them query information from databases and other diverse sources in the wild, across the Web.'"--Resource description page.

Spatial Data Management

Author: Nikos Mamoulis

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 133

ISBN-13: 3031018842

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Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Table of Contents: Introduction / Spatial Data / Indexing / Spatial Query Evaluation / Spatial Networks / Applications of Spatial Data Management Technology

Using OpenRefine

Author: Ruben Verborgh

Publisher: Packt Publishing Ltd

Published: 2013-09-10

Total Pages: 155

ISBN-13: 1783289090

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The book is styled on a Cookbook, containing recipes - combined with free datasets - which will turn readers into proficient OpenRefine users in the fastest possible way.This book is targeted at anyone who works on or handles a large amount of data. No prior knowledge of OpenRefine is required, as we start from the very beginning and gradually reveal more advanced features. You don't even need your own dataset, as we provide example data to try out the book's recipes.