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From semantic platforms to semantic apps

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Keynote presentation from Stephane Croisier at the July 11 IKS Workshop on moving from semantic platforms to semantic applications

Keynote presentation from Stephane Croisier at the July 11 IKS Workshop on moving from semantic platforms to semantic applications

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  • Reality from nualabugeye cc by nc sa
  • Courtesy of Billy Cripe (http://www.slideshare.net/billycripe/a-mavens-guide-to-ecm-best-practices)Flicker User: by nicholasjon creative commons attributionhttp://www.flickr.com/photos/nicholasjon/4643200251/sizes/l/in/photostream/
  • Courtesy of Marko Grobelnik (marko.grobelnik@ijs.si)Jozef Stefan Institute (http://www.ijs.si/)Slovenia, EuropeOriginal Slides: http://wims.vestforsk.no/slides/MarkoGrobelnikMladenic-WIMS2011.pptx
  • Courtesy of Billy Cripe (http://www.slideshare.net/billycripe/a-mavens-guide-to-ecm-best-practices)Feature bloatDo it because it canAsking the question “can my Semantic system do X” is not nearly as useful as asking “how can we achieve X with my sem tech ”Flicker User: everywhereisimagined creative commons attributionhttp://www.flickr.com/photos/everywhereisimagined/4688561335/sizes/l/in/photostream/
  • Heroes from videoplacebo is not cc by nc sa
  • Why I'm Going to Work for Zooomr from Thomas Hawk cc by nc
  • Transcript

    • 1. From Semantic Platforms to Semantic Apps
      Time to focus on creatingthe nextgeneration of compellingsemanticexperience
    • 2. By @scroisier
    • 3. Email: scroisier@gmail.com
    • 4. Sponsored by
    • 5. I – 2011 Trends
    • 6. Whatischanging over the last years?
      Massive Explosion of Raw Unstructured Content
    • 7. Email Explosion
    • 8. Document Explosion
    • 9. Social Content Explosion
    • 10. And nowit *REALLY* starts to impact all of us
    • 11. “The volume of information flowing through organizations grows by200% per year”
      “80% of data is unstructured, doubling every month”
      “Fortune 1000 stands to waste at least $2.5 billion per year due to an inability to locate and retrieve information”
      “68% of employees recognize that it is difficult and time consuming to find information needed to do their job.”
    • 12.
    • 13.
    • 14.
    • 15. Infoglut’ssyndroms
      Procrastination
      Unefficiencies
      Overwhelming
      Frustration
    • 16. Have we reached an inflection point?
      Are we assisting to a Search and Information Access Revival?
    • 17. System of Record
      System of Engagement
      System of Access
      Command & Control
      Collaborative
      Curate & Filter
      Transaction-oriented
      Interaction-oriented
      Link-oriented
      Reference-centric
      Data-centric
      User-centric
      Consistency/Relevancy
      is a key issue
      Security is a key issue
      Privacy is a key issue
      Web 3.0
      Web 1.0
      Web 2.0
      Social
      Information Access
      Content Lifecycle
    • 18. II – Problems
    • 19. Where are we in 2011?
      Mobility
      Social
      Cloud
      Semantic
      CMS
      Unlikely Match?
    • 20. Semanticsmeanstoomanydifferentthings for toomanypeople
    • 21. The One Week Reality Check
    • 22.  Monday / TechnicalFragmentation
    • 23. “As of today, there are probably as many architectures as there are vendors in the domain. ”
      Dr Mario Lenz
    • 24.  Tuesday / MarketOpacity
    • 25. “Expect consolidation, in a market with over 50 players, the exact solution for a given business problem might be a moving target for some time yet.”
      John Harney
      - KMWorld
    • 26. Wednesday/ Complexity
    • 27. “Any practical feedback on LSH with Random Projections vs LSH with MinHash for text clustering / duplication detection?”
      Tweetfrom
      Olivier Grisel
      Nuxeo
    • 28. © Billy Cripe
    • 29.  Thursday / Lack of MultilanguageReadiness
      Most semantic technologies are stillonlyavailable in English
    • 30. “Full Multingual Search: Holy Grail and still in a distant future.”
      Prof. Dr. Stefan Gradmann about the «Europeana» project - 2009
    • 31.  Friday / Scalability Issues
    • 32. “The systems that do that today are slow and clunky and don’t scale to the kinds of data sets we do with – they’re not good for 150 million messages a day.”
      Nova Spivack
    • 33. Saturday / Fanatism
    • 34. “A world of exhaustive, reliable metadata would be a utopia. It's also a pipe-dream, founded on self-delusion, nerd hubris and hysterically inflated market opportunities. ”
      Cory Doctorow
    • 35. Overselling
      Sunday / VendorOverselling
      Overexpectations
      Overpromises
    • 36. “You can invest a lot and not get any return.”
      Scott Brinker
      (in Top 10 reasons the Semantic Web is a lot like love)
    • 37. We are still at this stage
    • 38. Whenwe all expectedto bealreadyhere
    • 39. Lots of promises
      But move more slowly than expected
    • 40. Semanticcost+complexity vs user centeredadded value isstilla toofoggy story
      Problems being solved are too theorical
      Practical short-time client deliverables are still confused
      Level of skills required prevent widespread adoption
    • 41. III–From Semantic Platforms
      To Semantic Apps
    • 42. Semantic Platforms vs Semantic Apps
      Smart Email Capabilities
      EnhancedSearchExperience
      DynamicLanding Pages
      RelatedContent Widget
      Contextual Content Discovery Plug-ins
      Personalized Content Feeds
      AdsTargetting
      Latent SemanticAnalysis
      RDF/OWL
      Ontologies
      Entities
      Natural LanguageProcessing
      RESTfulAPI
      Data Schema
      Tripples
    • 43. From the Geek to the Practitioner
    • 44. From a monocultural stack
      To a largerparadigm?
    • 45. How technical research areas are approaching text and semantics?
      Semantics
      Social
      Network
      Analysis
      graphs /
      networks
      Computational
      Linguistics
      Text Mining
      Information
      Retrieval
      Semantic Web
      Machine
      Learning
      Web2.0
      interoperability
      language
      analytics
      statistics
      search
      community
      © Marko Grobelnik – Jozef Stefan Institute
    • 46. How do I approach Semantics?
    • 47. Content & Data Interoperability
    • 48. Content Intelligence
      Middleware
    • 49. Smart Content Apps
    • 50. Smart SEO/Ads
      Personalized Content Delivery
      Smart
      Features
      DynamicTopical Pages
      Intelligent Search
      Etc.
      User interfaces and applications
      Trust
      Proof
      Unifying Logic
      Social
      Intelligence
      Ontologies:
      OWL
      Rules:
      RIF/SWRL
      Querying
      Business
      Intelligence
      Cryptography
      Content Intelligence
      Middleware
      SPARQL
      SQL
      XPATH
      Vector
      Space
      Models
      Taxonomies: RDFS
      Inverted
      Keyword
      Index
      NLP
      Data Interchange
      CMIS
      CMIS
      RDF
      EDI
      Syntax
      CSV
      TXT
      XML
      JSON
      Protocol
      REST
      SOAP
      WEBDAV
      SMTP
      Data
      Interoperability
      Identifier
      PATH
      URI
      Character Set
      UNICODE
      BINARY
      Persistance
      NoSQL DB
      SQL DB
      TrippleStore
    • 51. Content & Data Interoperability
    • 52. RDFa
      Whatisseeingcurrently the mostuse
    • 53. Big Data
      Think Massive Volumes / Lots of Format
    • 54. “RDF might be a very good choice for how to make that available, but it can’t be a religious choice. We have to look at the problem specifically and ask how does RDF or XML or anything else map to it. We’d consider it as a tool in our toolbox.”
      Nova Spivack
    • 55. “The infrastructure needs of intelligent systems are now being met by a combination of Semantic Web, Linked Data, Web Services and Rule-based systems.”
      Jim Hendler - RPI
    • 56. Job in progress.
    • 57. Content Intelligence
      Middleware
    • 58. Why the « Intelligence » layer does not take off?
    • 59. “Ontology is Overrated!”
      Clay Shirky - 2005
      The Ontology Story isstillconfused
      Most usage are still more « expert » systems than generic solutions
    • 60. `
      The «smart» section of the Semantic Web: onlya fraction of the whole story?
    • 61. Emergence of a new « Content Intelligence » industry
    • 62. Content Intelligence
      Social and Behavioural Intelligence
      Business Intelligence
      At the intersection of EntepriseSearch, BI, Analytics, Social and Content Management
    • 63. Embracing the promise of turninganyrawdata into smart content
      Automated Information Clustering
      TextMining
      Content Analytics
      Connections to Linked Data Repo
      Rule-based classification
      Natural LanguageProcessing
      Content Enrichment
      An InfiniteComplexityProblem?
    • 64. The All-Purposed Platform Issue
      Intellectually satisfying, concretely feasible?
    • 65. Content Intelligence Middleware: To be or not to be?
    • 66. Onlyone certainty: Think « Smart Inside » ratherthansimply « Semantic Web Ready »
    • 67. Smart Content Apps
    • 68. And finallywhy are weimplementingthiswholestack?
    • 69. Main Challenge: Finding the next Semantic Killer App
    • 70. “10+ years into its inception, Semantic Web still has no clear killer app. It’s not clear if or when that app will emerge.”
      James KobielusForrester Group
    • 71.
    • 72. “User Interfaces for Semantic Web:
      Do They Have to Be Ugly?”
      Andraz Tori, Zemanta – SemTech 2010
    • 73. Never that any more!
    • 74.
    • 75. “Let’s get serious about
      user experience design. 
      It means utilizing your best engineers
      for more than just coding. “
      Marty Cagan
    • 76. Refocus on enabling the nextSemanticExperience
      Emotional
      Fun-to-use
      User-centered
      Addictive
      Pleasurable
      Contextual
    • 77.
    • 78. “Somehow, I repeatedly run into a situation where some use of Semantic Web technologies that would make a nice end-user application is blocked by the fact that the user interface is the real challenge.”
      OraLassila - 2007
    • 79. Amounts invested in Semantic UX vsSemantic Tech
      Stat source: Gut-feeling of Stephane Croisier
    • 80. MultidiciplinaryTeam Needed
      UX Guru
      Big Data Rock Star
      Semantic Jedi
      Polyglot Analytics Ninja
      MarketLurker and Sniffer
      Content Management Hero
    • 81. IV – Smart CMS
    • 82. MatchingSemantic Technologies
      withInformation Lifecycle and User Experience
    • 83. A few Semantic User Stories braught to you by
      Ongoing Internal R&D Efforts
    • 84. How to empower a CMS…
    • 85. … by bringingnew semantic value added?
    • 86.
    • 87. Analyze your
      Information DNA
      1
      Let the user better know about your content assets
    • 88. Content Enhancements
      Keywords
      Concepts
      Tags
      Categories
      Automatically enrich your unstructured content
    • 89. Automatically enrich your unstructured content
    • 90. Entity Extraction
    • 91. Auto-Classification
      (Common Tags / Concepts / Categories)
    • 92. Or providesemi-automated guidance for editors
    • 93. SearchEngine
      Enhancements
      2
      Let the user findratherthansearch
    • 94. SearchEnhancements &
      Automated SEO calibration
    • 95. Dynamic
      Navigations
      3
      Let the user explore instead of searching
    • 96. Drill-down, Filter and Mine into your information universe
    • 97. Semantic Navigation Components
    • 98. DynamicGlossary
    • 99. URL-FriendlyTopical Landing Pages
    • 100. Conceptual
      Match
      4
      Let the user find what he wants, not type
    • 101. ConceptualMatch
      Get the needles out of the haystack without typing
    • 102. Getrid of keywords limitations
    • 103. Enhanced Search Box
    • 104.
    • 105.
    • 106. Liquid Information
      Discovery
      5
      Let the user stick on your site
    • 107. In-Context Content Discovery
      Contextual Access to Public or PrivateFacingLinkedData Repositories
      Discoveryengine to similar Content in pre-selectedContent Stores
    • 108. « It’s like Augmented Reality
      for browsing the web. »
      Marshall Kirkpatrick, RWW
    • 109. Semantic Intertextualities
    • 110. 6
      Ambiant Findability
      Let the user come back to your site
    • 111.
    • 112. Contextual Similarities
      Access to the information your need right from within your context of use
    • 113. 7
      Surface the best
      Automaticallylearnfromusers and
      provides a personalizedexperience
    • 114. Surface the Best
      Content Recommendations/Predictions according to YOUR interests
    • 115. Let the user favourite, subscribe or « like » items
      To auto-populate its own information DNA
    • 116. And automaticallyget new articles similar to yourinterests…
    • 117. 8
      Curate the rest
      Let userscreate and sharetheirown
      Search-based Application
    • 118. FastGrowth of Semantic-ready and Search-focusedMicro-Sites
    • 119. After the explosion of Blog, Wiki and ActivityStreams,
      the rise of CuratedSearchSpaces?
    • 120. Conclusion
      ( Standardized Data Interop layer
      + Content Intelligence Middleware
      + Smart Features)
      xCompelling User Experience
      _______________________
      Smart Content Apps for Tomorrow
    • 121. Thanks for watching
    • 122. Information
      Most images from www.flickr.com (Image & licensing info in the notes section of slides)
      Presentation licensed: Creative Commons BY-NC-SA
      The presentation can be downloaded from: www.slideshare.net/scroisier
      More information about me: http://www.linkedin.com/in/scroisier