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Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
Understanding Linked Data via EAV Model based Structured Descriptions
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Understanding Linked Data via EAV Model based Structured Descriptions

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Multi part series of presentations aimed at demystifying Linked Data via: …

Multi part series of presentations aimed at demystifying Linked Data via:
1. Introducing Entity-Attribute-Value Data Model
2. Exploring how we describe things
3. Referents, Identifiers, and Descriptors trinity .

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  • 1. Demystifying Linked Data Via Entity-Attribute-Value (EAV) Data Model By Kingsley Idehen Twitter ID: @kidehen Founder & CEO, OpenLink Software © 2010 OpenLink Software, All rights reserved.
  • 2. Presentation Goals
    • Demystify Linked Data
    • Demonstrate the unobtrusive nature of Linked Data
    • Explore how Linked Data can Work for You!
    © 2010 OpenLink Software, All rights reserved.
  • 3. Situation Analysis
    • User-generated content is growing exponentially
    • Enterprise & individual connectivity is growing
    • The line between the Individual & the Enterprise is blurring
    • The discovery & exploitation of Data, Information, and Knowledge remain the ultimate critical success factors
    • But there are still only 24 hours in a day!
    © 2010 OpenLink Software, All rights reserved.
  • 4. A Few Definitions
    • What is Data ?
      • How we express observation
    • What is Information?
      • How we use Context to perceive observation
    • What is Knowledge?
      • How we Comprehend what we perceive
    © 2010 OpenLink Software, All rights reserved.
  • 5. Understanding Data
    • What is a Data Item (Datum)?
      • A Unit (or Object) of Observation
    • What is a Structured Data Item?
      • An observation expressed in a manner that makes discernible:
        • the Referent (Unit or Object of Observation)
        • the Characteristics (Attribute=Value Pairs)
    © 2010 OpenLink Software, All rights reserved.
  • 6. Entity-Attribute-Value Model
    • A foundation model for Data
      • In our Heads
      • Very Old
    • Entities (Data Items) have
      • Identifiers
      • Attributes
      • Attribute Values
    © 2010 OpenLink Software, All rights reserved.
  • 7. How We Describe Things
    • The natural process:
      • Something (Referent) catches our attention
      • We Identify/Name the Referent of interest
      • We Identify its Attributes
      • We Assign Values to its Attributes
    • Descriptor Resources bear Descriptions
    © 2010 OpenLink Software, All rights reserved.
  • 8. The Description Process
    • Identify Referent
    • Something grabs our attention
    • We give the Object or Unit of Observation a Name
    • Identify its Attributes
    • We use existing Attribute Names or make new ones.
    • Assign Values To its Attributes
    • Assign values to which may be References (Names) to other Objects
    Repeat the process for each Attribute
    • Draw Conclusions
    • Establish some “Relative Truths” or “Facts” about your observations
  • 9. EAV based Description of a Blog Post Entity Ref. (ID) Attribute Ref. (ID) Value (Literal or Ref.) #PostID #maker #KingsleyIdehen #PostID #subject “ Linked Data” #PostID #type #BlogPost #KingsleyIdehen #type #Person #KingsleyIdehen #Interest #LinkedData
  • 10. © 2008 OpenLink Software, All rights reserved. Description of a Linked Data Space
  • 11. Common Web Page Experience (View Source Pattern) Rendered Page (Markup Presentation) Markup © 2010 OpenLink Software, All rights reserved.
  • 12. Other Aspects of a Web Page (Dark Side – “Page Descriptor”) Page Descriptor Rendered Page Page Markup © 2010 OpenLink Software, All rights reserved.
  • 13. Perceivable Representation (“Sense”) Trinity (Referent, Identifier, and Descriptor) Referent Identifier (e.g. Generic HTTP scheme URI) Descriptor (“Sense”) (@ Address Identified by URL) Description Representation (E-A-V Graph Pictorial) Carries Description Of Access To (De-reference) Identifies (Names) © 2010 OpenLink Software, All rights reserved.
  • 14. Representation Trinity (Referent, Identifier, and Descriptor/Sense) © 2010 OpenLink Software, All rights reserved.
  • 15. Our Perceptions (Context Lens Prisms) What’s Inside This? V E A E V A E A V A © 2010 OpenLink Software, All rights reserved. Structured Data (Lots of E-A-V Records)
  • 16. Lots of Connected Perceptions (Linked Data Spaces) Structured Data Your Data Space My Data Space Their Group Data Space Our Group Data Space Structured Data Structured Data Structured Data © 2010 OpenLink Software, All rights reserved.
  • 17. Gestalt (Our Data Space) Your Data Space Their Data Space My Data Space Lots of Connected Perceptions (Linked Data Spaces)
  • 18. © 2008 OpenLink Software, All rights reserved. Gestalt (Collective Intelligence)
  • 19. Ultimately You Want “To Discover” or “Be Discovered” Seeks Finds Matches Offers Make Sale Linked Data Spaces increase our Serendipitous Discovery Quotient (SDQ)
  • 20. You Only Need a LINK to Add Your Piece To The Puzzle! Structured Data Structured Data Structured Data Structured Data © 2010 OpenLink Software, All rights reserved.
  • 21. Use LINKs to Mesh Your Perceptions with Others Structured Data Structured Data Structured Data Structured Data © 2010 OpenLink Software, All rights reserved.
  • 22. Additional Material
    • Presentation Links
      • Exploiting & Deploying Linked Data
      • Solving Real Problems with Linked Data
      • Linked Data Spaces & Data Portability
      • Meet Charlie (Mr. Enterprise 3.0)
    • Video Demos Links
      • Precision Search & Find
      • Fixing Identity Crisis
      • Linked Data Views over RDBMS Data (Note part 2 )
    © 2010 OpenLink Software, All rights reserved.
  • 23. Contd. Additional Material
    • Live Linked Data Demo Links
      • Various Linked Data Demos
      • Various Linked Data Meshup Demos
      • GeoSpatial oriented Linked Data Meshups
      • eCommerce Related Linked Data Demos
    © 2010 OpenLink Software, All rights reserved.

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