With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing a simple mashup or maintaining a high-performance enterprise solution,Programming the Semantic Web provides a standard, flexible approach for integrating and future-proofing systems and data. This book will help you: Learn how the Semantic Web allows new and unexpected uses of data to emerge Understand how semantic technologies promote data portability with a simple, abstract model for knowledge representation Become familiar with semantic standards, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL) Make use of semantic programming techniques to both enrich and simplify current web applications
Author: John Hebeler
Publisher: John Wiley & Sons
Release Date: 2011-02-25
The next major advance in the Web?Web 3.0?will be built on semantic Web technologies, which will allow data to be shared and reused across application, enterprise, and community boundaries. Written by a team of highly experienced Web developers, this book explains examines how this powerful new technology can unify and fully leverage the ever-growing data, information, and services that are available on the Internet. Helpful examples demonstrate how to use the semantic Web to solve practical, real-world problems while you take a look at the set of design principles, collaborative working groups, and technologies that form the semantic Web. The companion Web site features full code, as well as a reference section, a FAQ section, a discussion forum, and a semantic blog.
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.
Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL, Second Edition, discusses the capabilities of Semantic Web modeling languages, such as RDFS (Resource Description Framework Schema) and OWL (Web Ontology Language). Organized into 16 chapters, the book provides examples to illustrate the use of Semantic Web technologies in solving common modeling problems. It uses the life and works of William Shakespeare to demonstrate some of the most basic capabilities of the Semantic Web. The book first provides an overview of the Semantic Web and aspects of the Web. It then discusses semantic modeling and how it can support the development from chaotic information gathering to one characterized by information sharing, cooperation, and collaboration. It also explains the use of RDF to implement the Semantic Web by allowing information to be distributed over the Web, along with the use of SPARQL to access RDF data. Moreover, the reader is introduced to components that make up a Semantic Web deployment and how they fit together, the concept of inferencing in the Semantic Web, and how RDFS differs from other schema languages. Finally, the book considers the use of SKOS (Simple Knowledge Organization System) to manage vocabularies by taking advantage of the inferencing structure of RDFS-Plus. This book is intended for the working ontologist who is trying to create a domain model on the Semantic Web. Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems
In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include: Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran
Author: Liyang Yu
Publisher: Springer Science & Business Media
Release Date: 2011-01-03
Covering the theory, technical components and applications of the Semantic Web, this book’s unrivalled coverage includes the latest on W3C standards such as OWL 2, and discusses new projects such as DBpedia. It also shows how to put theory into practice.
Author: Tom Heath
Publisher: Morgan & Claypool Publishers
Release Date: 2011
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
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
This book constitutes the refereed proceedings of the 5th European Semantic Web Conference, ESWC 2008, held in Tenerife, Canary Islands, Spain, in June 2008. The 51 revised full papers presented together with 3 invited talks and 25 system description papers were carefully reviewed and selected from a total of 270 submitted papers. The papers are organized in topical sections on agents, application ontologies, applications, formal languages, foundational issues, learning, ontologies and natural language, ontology alignment, query processing, search, semantic Web services, storage and retrieval of semantic Web data, as well as user interfaces and personalization.
Author: Matthew A. Russell
Publisher: "O'Reilly Media, Inc."
Release Date: 2013-10-04
You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use of database-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase (column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration
The semantic Web proposes the mark-up of content on the Web using formal ontologies that structure underlying data for the purpose of comprehensive and transportable machine understanding. Semantic Web Services: Theory, Tools and Applications brings contributions from researchers, scientists from both industry and academia, and representatives from different communities to study, understand, and explore the theory, tools, and applications of the semantic Web. Semantic Web Services: Theory, Tools and Applications binds computing involving the semantic Web, ontologies, knowledge management, Web services, and Web processes into one fully comprehensive resource, serving as the platform for exchange of both practical technologies and far reaching research.