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

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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
  • From semantic platforms to semantic apps

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

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