Fundamentals of the Semantic Web
by
David Booth
Table of contents
Fundamentals of the Semantic Web
Outline
Acknowledgements
SECTION 0: Expectations
Why It's Hard to Talk About the Semantic Web
What I Hope to Achieve
What I Will Not Address
SECTION 1: Motivation for the Semantic Web
Outline
What is the Semantic Web? (Purpose)
What is the Semantic Web? (Physical View)
Goal: A More Useful Web
How could the Web be more useful?
The Problem of Finding Information
The Problem of Finding Information
The Problem of Sharing Information
The Problem of Combining Information
Summary
SECTION 2: The Semantic Web Concept
Outline
Point Solutions Versus General Solutions
Seeking a General Solution
Why Computers Are Not More Helpful
Analogy: What We Say to Dogs
Analogy: What We Say to Computers
Ways to Enable Machine Processing
Approach 1: Smarter machines
Smarter Machines
Approach 2: Smarter Data
Smarter Data (More Machine Processable)
The Current Web
The Semantic Web - An Extension of the Current Web
How Google Works
Example Use of Machine Processable Information
Summary
SECTION 3: Making the Web More Semantic
Outline
Why is machine processing difficult?
Problem 1: Ambiguity
Kinds of Things to Identify
Unambiguously Identifying Web Resources
Unambiguously Identifying Physical Objects
Unambiguously Identifying Abstract Concepts
Ontology
Dublin Core
One Global Ontology?
Does an Ontology Really Define Meaning?
Ontologies and Web Services
Other Ontology Work
Example of Unambiguous Identification
Summary
SECTION 4: Concepts of RDF
Outline
Key Problems (Revisited)
Problem 2: Complexity of Information Formats
Important Characteristics for a Machine-Processable Format
What Is RDF?
Why a Relational Data Model?
Adapting the Relational Model for the Web
URIs and Database Keys
RDF Triples
Example Triple
Representing Relational Data as Triples
Representing Tables as Triples
Table as Collection of Triples
Joining Triples to Create a Graph
Joining Data from Multiple Sources
Application Integration: XML Versus RDF
Summary
SECTION 5: Conclusions, Example Applications and Demo
Solutions to Key Problems
What information could be machine processable?
Where to put machine-processable information?
Example RDF / Semantic Web Applications
Demo of TAP Semantic Search
What I Hoped to Achieve
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Appendix 1: Trees Versus RDF
Evolving Data: Tree Versus RDF
Version 1.1 adds 2 new features:
Version 1.2 adds 3 more features:
Version 2.0 adds color:
Version n combines printer, scanner, fax:
The Importance of Flexibility
Comparing Data Representations
Appendix 2: Representing Relational Data as RDF Triples
Representing Relational Data as RDF Triples