This document discusses the evolution of the web and the concept of the semantic web. It defines the semantic web as a web with meaning where data is interlinked and searchable. The key aspects of the semantic web include using technologies like RDF, OWL and SPARQL to embed relationships and definitions within data to make it more meaningful and accessible to machines. This allows for more personalized searches and access to accurate information. Challenges include developing open standards for ontologies.

1. TAKING ADVANTAGE
OF
SEMANTIC WEB
Sankaranand Balaradjou
www.sankaranand.com

2. WEB 1.0 (1996)
 Read only information
 Encyclopaedia
 HTML
 Forms, Pages and Links
 Directories
 Just Interlinking of Webpages

3. WEB 2.0 (2006)
 Community
 Blogs
 Tagging
 Web Application
 Wikipedia
 Sharing
 RSS and XML

4. WEB 3.0 (???)
 Personalisation
 The Semantic Web
 Artificial Intelligence
 Mobility (Data Portability)

5. DATA, INFORMATION AND CONTENT
 Data is raw. It is numbers and patterns that have no
interpretation
 Processed Data is Information
 Content is digestible form of Information

6. WHAT IS SEMANTIC WEB ?
 Group of methods and technologies
 The Semantic Web = a Web with a meaning
 searching, aggregating and combining of the Web's information
 Access Meaningful and accurate information
 Data are interlinked

7. BUILDING THE RELATIONSHIP
 Siva Kumar is Surya’s Father
 Automated and Manual Relationship

8. IDENTITY

9. DEFINITION
Apple

10. ADVANTAGES OF MACHINES
 They process long and complex computing
 Comparing and indexing large data
 Searching millions of data

11. ADVANTAGES OF HUMANS
 We know the meaning
 Relations
 Logical
 Intelligence

12. MAKING THE EXISTING DATA MEANINGFUL
 Rules or Ontologies
 Semantic Programming Techniques
 Data and Metadata Together

13. LINKED DATA

14. EXAMPLE
 Facebook Graph
 Google Knowledge Graph

15. WHY IT IS IMPORTANT TO BE SEMANTIC ?
 Everyone is smarter now (Google Search )
 The more we know about, the more is the visibility and accuracy
 Personalisation

16. THE SOLUTIONS ?
Top Down
Bottom Up

17. TOP DOWN
Analysis the information
Process Natural Language

18. BOTTOM UP
Embed Core Notations in Information

19. THE TOOLS
 RDF (Resource Description Framework) – Meta Data
 RSS (Rich Site Summary ) – Web Feed
 URI (Uniform Resource Identifiers )
 XML (Extensible Markup Language)
 OWL (Web Ontology Language)

20. RDF EXAMPLE
<?xml version="1.0"?>
<rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:cd="http://www.recshop.fake/cd#">
<rdf:Description
rdf:about="http://raga.com">
<cd:artist>Rahman</cd:artist>
<cd:country>India</cd:country>
<cd:company>Sony</cd:company>
<cd:price>250</cd:price>
<cd:year>2013</cd:year>
</rdf:Description>
</rdf:RDF>

21. SPARQL
 Semantic SQL Language
 Uses WDSL (Web Services Description Language )

22. MICROFORMATS
Ical
Vcard
CSV file
Atom
Hresumes

23. THE CHALLENGES
An Open Standard of Ontology
Or
Standard Microformat

24. NO SELFISHNESS
 Wikipedia and Success
 Teach Machine everything and let it do the work for you

25. GOOGLE KNOWLEDGE SEARCH
Categorise Document
Meaningful tags
Related Document
Recognize known Entities

27. BOOK MY SHOW – FRIEND SEATING

28. THE SEMANTIC INFORMATION

29. FRIENDS REVIEWS

30. SEMANTIC SERVICE-ORIENTED ARCHITECTURE
Scalable Enterprise Application
Watch the video

31. BUILD MEANINGFUL APPLICATIONS
Tight Integration with Other Service Platforms and APIS
Unified Information and Sharing
Portability
No Lack of Content
Easy Adoption
Reusability of Data

32. BUILD YOUR OWN SEMANTIC APP
Storage Layer - Storage
Manipulation Layer - Processing
Representation Layer - View
Choose the Right Tools

33. THANK YOU
Twitter -> @sankaranand