Learning SPARQL

Learning SPARQL

by Bob DuCharme

Paperback(Second Edition)

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Product Details

ISBN-13: 9781449371432
Publisher: O'Reilly Media, Incorporated
Publication date: 07/12/2013
Edition description: Second Edition
Pages: 386
Sales rank: 445,785
Product dimensions: 6.90(w) x 9.10(h) x 1.00(d)

About the Author

Bob DuCharme (http://www.snee.com/bob) is a solutions architect at TopQuadrant, a provider of software for modeling, developing, and deploying semantic web applications. He came to TopQuadrant from Innodata Isogen, where he did system and architecture analysis and design for a wide range of global publishing clients as well as cochairing the 2008 Linked Data Planet conference in New York City. Earlier in his career, he oversaw SGML and XML development at Moody's Investors Service and then moved on to LexisNexis, where he did data and systems architecture as they made the transition to XML-based systems.

In the XML.com newsletter, editor Kendall Clark once wrote “Does anyone write tech prose as clear as Bob?” Bob is the author of Manning Publications’ “XSLT Quickly,” Prentice Hall’s “XML: The Annotated Specification” and “SGML CD,” and McGraw Hill’s “Operating Systems Handbook.” He's written over 70 pieces for XML.com and has contributed to Dr. Dobb’s Journal, IBM developerWorks, Nodalities, DevX, perl.com, XML Magazine, XML Journal, XML Developer, O’Reilly Books’ “XML Hacks,” and Prentice Hall’s “XML Handbook.” Bob received his BA in Religion fromColumbia University and his Master’s in Computer Science from New York University. He lives in Charlottesville, Virginia, with his wife Jennifer and their daughters Madeline and Alice.

Table of Contents

Preface;
Why Learn SPARQL?;
Organization of This Book;
Conventions Used in This Book;
Documentation Conventions;
Using Code Examples;
Safari® Books Online;
How to Contact Us;
Acknowledgments;
Chapter 1: Jumping Right In: Some Data and Some Queries;
1.1 The Data to Query;
1.2 Querying the Data;
1.3 More Realistic Data and Matching on Multiple Triples;
1.4 Searching for Strings;
1.5 What Could Go Wrong?;
1.6 Querying a Public Data Source;
1.7 Summary;
Chapter 2: The Semantic Web, RDF, and Linked Data (and SPARQL);
2.1 What Exactly Is the “Semantic Web”?;
2.2 URLs, URIs, IRIs, and Namespaces;
2.3 The Resource Description Framework (RDF);
2.4 Reusing and Creating Vocabularies: RDF Schema and OWL;
2.5 Linked Data;
2.6 SPARQL’s Past, Present, and Future;
2.7 The SPARQL Specifications;
2.8 Summary;
Chapter 3: SPARQL Queries: A Deeper Dive;
3.1 More Readable Query Results;
3.2 Data That Might Not Be There;
3.3 Finding Data That Doesn’t Meet Certain Conditions;
3.4 Searching Further in the Data;
3.5 Searching with Blank Nodes;
3.6 Eliminating Redundant Output;
3.7 Combining Different Search Conditions;
3.8 FILTERing Data Based on Conditions;
3.9 Retrieving a Specific Number of Results;
3.10 Querying Named Graphs;
3.11 Queries in Your Queries;
3.12 Combining Values and Assigning Values to Variables;
3.13 Creating Tables of Values in Your Queries;
3.14 Sorting, Aggregating, Finding the Biggest and Smallest and...;
3.15 Querying a Remote SPARQL Service;
3.16 Federated Queries: Searching Multiple Datasets with One Query;
3.17 Summary;
Chapter 4: Copying, Creating, and Converting Data (and Finding Bad Data);
4.1 Query Forms: SELECT, DESCRIBE, ASK, and CONSTRUCT;
4.2 Copying Data;
4.3 Creating New Data;
4.4 Converting Data;
4.5 Finding Bad Data;
4.6 Asking for a Description of a Resource;
4.7 Summary;
Chapter 5: Datatypes and Functions;
5.1 Datatypes and Queries;
5.2 Functions;
5.3 Extension Functions;
5.4 Summary;
Chapter 6: Updating Data with SPARQL;
6.1 Getting Started with Fuseki;
6.2 Adding Data to a Dataset;
6.3 Deleting Data;
6.4 Changing Existing Data;
6.5 Named Graphs;
6.6 Summary;
Chapter 7: Query Efficiency and Debugging;
7.1 Efficiency Inside the WHERE Clause;
7.2 Efficiency Outside the WHERE Clause;
7.3 Debugging;
7.4 Summary;
Chapter 8: Working with SPARQL Query Result Formats;
8.1 SPARQL Query Results XML Format;
8.2 SPARQL Query Results JSON Format;
8.3 SPARQL Query Results CSV and TSV Formats;
8.4 Summary;
Chapter 9: RDF Schema, OWL, and Inferencing;
9.1 What Is Inferencing?;
9.2 SPARQL and RDFS Inferencing;
9.3 SPARQL and OWL Inferencing;
9.4 Using SPARQL to Do Your Inferencing;
9.5 Querying Schemas;
9.6 Summary;
Chapter 10: Building Applications with SPARQL;
10.1 Applications and Triples;
10.2 SPARQL and Web Application Development;
10.3 SPARQL Processors;
10.4 SPARQL and HTTP;
10.5 Summary;
Chapter 11: A SPARQL Cookbook;
11.1 Themes and Variations;
11.2 Exploring the Data;
11.3 Creating and Updating Data;
11.4 Summary;
Glossary;
Colophon;

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Learning SPARQL 5 out of 5 based on 0 ratings. 2 reviews.
albertgoldfain on LibraryThing 23 days ago
A comprehensive introduction to SPARQL tools, queries, and endpoints. The examples are illustrative and well-thought out. Some of the Fuseki material is stale already, but there is plenty here to incorporate SPARLQ into linked-data web solutions.
LazyPredicate More than 1 year ago
I have every book on semantic web technologies and the introduction to RDF/OWL is one of the easiest and best out there. I would recommend this book for anyone who wants to get a concise and painless summary of RDF/OWL. Since the book's title is 'Learning SPARQL', I guess I should get to that. DuCharme does a great job explaining SPARQL and, as important, how to use SPARQL in real-world applications. Overall, a great book and highly recommended.