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REST in Practice

Cover of REST in Practice by Ian Robinson... Published by O'Reilly Media, Inc.
  1. REST in Practice
    1. SPECIAL OFFER: Upgrade this ebook with O’Reilly
    2. Foreword
    3. Preface
      1. Should I Read This Book?
      2. Should I Skip This Book?
      3. Resources
      4. What Did You Think About the Book?
      5. Errata
      6. Conventions Used in This Book
      7. Using Code Examples
      8. How to Contact Us
      9. Safari® Books Online
      10. Acknowledgments
    4. 1. The Web As a Platform for Building Distributed Systems
      1. Architecture of the Web
      2. Thinking in Resources
      3. From the Web Architecture to the REST Architectural Style
      4. The Web As an Application Platform
      5. Web Friendliness and the Richardson Maturity Model
      6. GET on Board
    5. 2. Introducing Restbucks: How to GET a Coffee, Web Style
      1. Restbucks: A Little Coffee Shop with Global Ambitions
      2. Toolbox
      3. Here Comes the Web
    6. 3. Basic Web Integration
      1. Lose Weight, Feel Great!
      2. A Simple Coffee Ordering System
      3. URI Templates
      4. URI Tunneling
      5. POX: Plain Old XML over HTTP
      6. We Are Just Getting Started
    7. 4. CRUD Web Services
      1. Modeling Orders As Resources
      2. Building CRUD Services
      3. Aligning Resource State
      4. Consuming CRUD Services
      5. Consuming Services Automatically with WADL
      6. CRUD Is Good, but It’s Not Great
    8. 5. Hypermedia Services
      1. The Hypermedia Tenet
      2. Hypermedia Formats
      3. Contracts
      4. Hypermedia Protocols
      5. Implementing a Hypermedia Service
      6. Building the Ordering Service in Java
      7. Building the Ordering Service in .NET
      8. Ready, Set, Action
    9. 6. Scaling Out
      1. GET Back to Basics
      2. Caching
      3. Making Content Cacheable
      4. Implementing Caching in .NET
      5. Consistency
      6. Extending Freshness
      7. Stay Fresh
    10. 7. The Atom Syndication Format
      1. The Format
      2. Common Uses for Atom
      3. Using Atom for Event-Driven Systems
      4. Building an Atom Service in Java
      5. Building an Atom Service in .NET
      6. Atom Everywhere?
      7. After the Event
    11. 8. Atom Publishing Protocol
      1. Atom Publishing Protocol
      2. Implementing Order Fulfillment Using AtomPub
      3. Implementing AtomPub in .NET
      4. A Versatile Protocol
    12. 9. Web Security
      1. HTTP Security Essentials
      2. Identity and the OpenID Protocol
      3. The OAuth Protocol
      4. Service Hacks and Defenses
      5. Final Thoughts
    13. 10. Semantics
      1. Syntax Versus Semantics
      2. Structure and Representation of Information
      3. The Semantic Web
      4. Microformats
      5. Linked Data and the Web
      6. Guidance
    14. 11. The Web and WS-*
      1. Are Web Services Evil?
      2. SOAP: The Whole Truth
      3. WSDL: Just Another Object IDL
      4. Two Wrongs Don’t Make a Right
      5. Secure, Reliable, Transacted
      6. A Requiem for Web Services?
    15. 12. Building the Case for the Web
      1. No More Silver Bullets
      2. Building and Running Web-Based Services
      3. No Architecture Without Measurement
      4. Selling the Web
      5. Go Forth and Build
    16. Index
    17. About the Authors
    18. Colophon
    19. SPECIAL OFFER: Upgrade this ebook with O’Reilly

Structure and Representation of Information

Throughout this chapter, we distinguish between the structure and representation of information. While the former is about the relationship between the different information pieces that make up the details of a document, concept, or business entity, the latter is about choices in representing that information. The choice of representation might have a significant impact on our ability to share the information in an interoperable manner.

Data, Information, Knowledge

The terms data, information, and knowledge are often encountered in discussions related to semantics. Here we’ll explain what we mean by these terms. Though you may find them used differently elsewhere, we’ve tried to align ourselves with more popular definitions.[120]

We use the term data to refer to the raw, uninterpreted bits that make up a business entity (e.g., an invoice, a receipt, the customer details).[121] We call information the interpretation of data within the context of a particular application domain (e.g., the contents of the <milk> element in a Restbucks order when interpreted as a customer’s choice of milk). Finally, knowledge represents our understanding of a domain after we collect, analyze, and reason over the available data and information.

The result of this reasoning is a set of information facts—knowledge—that we can use to make business decisions. Knowledge can be explicitly recorded, or it can be inferred, or probabilistically assumed, based on analysis ...

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