Data-aware appsChallenges & Opportunities<br />Sagie Davidovich<br />VP R&D<br />
2011 - Web Interoperability is broken<br /><ul><li>APIs:
Too many of them
Not aware of each other
APIs Operate on the keyword level
No standard ontology
Different formats
TOS/rate limits /credibility are notmachine readable
Discovery doesn’t exist (WSDL failed)
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Data aware apps

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What it takes to build data aware applications.
Why Web Interoperability is broken?

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  • We’ve overcome the first two complexity barriers by introducing standard protocols, encoding and formats for representing information.The next step would be establishing an abstraction layer and standards for meaning.Once this is done, web APIs and data sources can exchange information on the meaning level, and do this transparently.Data driven applications are expressed as data flow graphs, and the problem of building these applications is reduced to a path finding problem.
  • A typical data flow, starts from a set of inputs, goes through a transformation &amp; processing flow, and then output as a machine readable, human readable format, persisted or used as a trigger for external applications.Sensors can be for example the user’s GPS coordinates.
  • Personal email: mesagie [at] gmail [dot] com
  • Data aware apps

    1. 1. Data-aware appsChallenges & Opportunities<br />Sagie Davidovich<br />VP R&D<br />
    2. 2. 2011 - Web Interoperability is broken<br /><ul><li>APIs:
    3. 3. Too many of them
    4. 4. Not aware of each other
    5. 5. APIs Operate on the keyword level
    6. 6. No standard ontology
    7. 7. Different formats
    8. 8. TOS/rate limits /credibility are notmachine readable
    9. 9. Discovery doesn’t exist (WSDL failed)
    10. 10. Too few know RDF/OWL/SPARQL
    11. 11. 99.9% of the information on the web is free form text
    12. 12. Web data is partial, noisy, inaccurate, not objective</li></li></ul><li>Abstraction stack - towards data aware apps<br />
    13. 13. A typical data flow<br />Input<br />Process<br />Output<br />XML/<br />JSON<br />Order<br />Search<br />Filter<br />Transform<br />Data aware UI components<br />Interaction<br />Aggregate<br />Format<br />Persist<br />Sensors<br />Generate<br />Compute<br />Augment<br />Stream<br />Trigger<br />
    14. 14. Data aware web - Pragmatic approach<br />Data aware app host<br />Today’s web<br />Semantic Abstraction layer<br />Reasoner & data flow manager<br />Query Enrichment<br />APIs<br />Result refinement<br />Abstractions Library<br />Synthesis<br />Unstructured Web pages<br />Semantic Store<br />Entity & Fact extraction<br />
    15. 15. Abstractions Libraryovercoming the complexity barrier<br />Lunchsuggest = Meals(familynearby), Meals(friendsnearby)<br />Meals(folks) = folks/foodtaste/common/nearByRestaurants/deals<br />FamilyNearby= facebook:connections/filter(family, near)<br />NearMe(object) = |object/location - me:location| < 10km<br />location= sensor:gps<br />family = children, spouse, parents, …<br />
    16. 16. What we’ve done at SemantiNet<br />High performance graph storefor Wikipedia & Linked-data<br />Extensible & Dynamic query enginewith a simple XPath-like query language<br />Semantic abstraction layer over APIsincludes semantic query refinements<br />A complete stack of NLP librariesinteroperable with other APIs<br />Ontology aware contextual disambiguation<br />Templating engine<br />Web development environment for data aware apps<br />
    17. 17. Thank you<br />More coverage on:<br />semanticweb.com/build-data-aware-apps-without-the-hassle_b17465<br />blog.headup.com<br />Sagied [at] semantinet [dot ] com<br />
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