The document discusses the concept of linked data and its importance in enhancing the visibility and ranking of web content in search engines. It differentiates between structured, unstructured, and semi-structured data and emphasizes the need for semantic markup to create meaningful relationships between entities. Additionally, it highlights the role of linked data in enterprise search, underlining the challenges businesses face in leveraging knowledge across different departments.

1. Ravish Bhagdev
The Invisible Web of
Linked Data

2. WWW Web of Our Role
Linked Data

3. World Wide Web
HTTP, URL, HTML

4. WWW as we know
A global repository of
Web Page X interconnected documents
Text Text Text Text Text Text
Link Text Describing Page Y Documents linked by hyperlinks
Text Text Text Text Text Text
Text Text Text Text Text Text – Implicit meaning assigned to links
with a few words or pictures
– Anyone can link a new page to any
other available page
Web Page Y
– Links can also be made to specific
Text Text Text Text Text Text sections of a page (anchor tags)
Text Text Text Text Text Text
Text Text Text Text Text Text
Text Text Text Text Text Text

5. WWW as we know

6. Search Engines and power of links
• Use links between web-pages to rank
results
• Each search performed results in
generation of a new page with more
hyperlinks
• Click-through relevance information
• Redundancy of information
• Focus on the most useful and relevant page
• Freshness
• Links are the key

7. Web of Linked Data
Linking more than just pages

8. Structured vs Unstructured Data
Structured Simply defined as
Data that can be parsed
XML DB and processed by
machines to automate
operations like matching,
CSV RDF classification, querying etc.
Unstructured
Data that cannot be parsed
HTML Doc in this manner without loss
of information or
requirement of input from
PDF PPT external agents

9. Semi-Structured Data
Most however is semi-
XML DB structured
– HTML (HEAD, TITLE, BODY etc)
CSV RDF – Email (Header vs Body)
– DBs with free text fields
– Forms with descriptive fields
– CSVs, Spreadsheets
HTML Doc – Some more structured than
others
– Not possible to express
PDF PPT everything in structured form

10. Web: Giant Data Shredder
Web Page
DBs (HTML)

11. Creating Links at Level of Entities
Requires Semantic Markup
– Uniquely Identify Entities in a
Name:
<String> Document (URIs)
John Smith
– Make Relations Between
Entities Explicit
– Shared Vocabulary
Person:
<Person> (schema.org, FOAF, SKOS,
Person3456 GoodRelations etc.)
Residence: Age:
<Country> <Integer> – Reuse existing vocabularies
UK 24 instead of inventing new ones
– Both with-in the same
document and with other
Entities in other Documents

12. Integrated Data Across Applications
 Where should I go on vacation?
 How do I get the best fare?
what
 What is it like there?
how
Travel
Travel where
Services
Interests
(FB) who Places
to go  Where should I stay?
People who (lonely planet) what
have been there
(foursquare)  What do I need to know about it?
Photos, blogs, news stories

13. How Search Engines Use Linked Data

14. How Search Engines Use Linked Data

15. Our Role
Why I think we should engage in Linked Data Initivatives

16. We Build Web Apps
» That publish content
» We want the content to be
» Visible to next generation apps
» Ranked High by Search Engines
» Presented clearly and unambiguously
(think price comparision websites)
» All the big players are doing it
» Including most governments

17. The Visible Web
Is Dominated by Marketing
– The web is seen through the lense of Search Engines and Social
Networks
– Not every relevant page can appear on first page of search results
– Paid, Targetted advertising
– Affiliate Programs and Contracts
– Popularity overrides quality of matches
– What is popular is decided by sites that are already popular
– Visible web is more and more biased

18. Emerging marketing tactics, circa 2010

19. Creating Linked Data (How?)
» Implicitly
» Integrating Linked Data Standards with
Publishing tools (CMS!), apps, gadgets,
Entity P
• Entity A • Entity X
social networks etc.
• Entity B • Entity Q • Entity Y
» Minimize the effort while maximizing • Entity R
the return
Entity C Entity Z
» Every time you add a new friend on FB
or follow someone on twitter, you create
linked data

21. Linking of information creates
Insights
Enterprise Search & KM
Linked Data is even more relevant in the
context of enterprise search because
Raw Data: symbols and chars these data don’t even have simple
hyperlinks
Informaton: Data in usable form
Knowledge: Information Enriched Popularity of a document is not always
with Semantics the most important factor
Wisdom: Understanding,
Hindsight, Experience Large companies struggle to make use of
knowledge and information across
departments and silos
Timly linking of data across these silos
can have a big impact

22. ? Questions?
@RavBhagdev
Theres more: Information Extraction, Social Search, Knowledge Capture etc.

23. What’s Your Message?
Thanks!