The Live Web #SCITDA11 Keynote
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The Live Web #SCITDA11 Keynote

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The web is moving from the Dynamic Query/Static Data model that has characterized Web 2.0 sites to a Dynamic Data/Static Query model that characterizes many of today's most interesting Internet ...

The web is moving from the Dynamic Query/Static Data model that has characterized Web 2.0 sites to a Dynamic Data/Static Query model that characterizes many of today's most interesting Internet interactions. What does this mean for your organization and how can you take advantage of this shift?

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  • \n
  • Web is an amazing place\n\n
  • \n
  • Life events. \nbusiness.utah.gov\n
  • Life events, not agencies\nOne place, not multiple places\nAdd payment and personal information only once\nSecure and trustworthy environment\n“online” not “in line”\n
  • Life events, not agencies\nOne place, not multiple places\nAdd payment and personal information only once\nSecure and trustworthy environment\n“online” not “in line”\n
  • Life events, not agencies\nOne place, not multiple places\nAdd payment and personal information only once\nSecure and trustworthy environment\n“online” not “in line”\n
  • \n
  • Tightly coupled vs. loosely coupled \nNumber of connections and interactions is staggering\nWhy many home automation plays have failed to take hold\n
  • Adding a network changes anything\n
  • Do demo here!!!\n
  • \n
  • \n
  • book on wishlist or maybe you just looked at it. \n
  • book on wishlist or maybe you just looked at it. \n
  • Have your phone guide you to the empty parking slot nearest your desitnation\n
  • Food that notifies you when it’s about to go out of date\n
  • \n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • I book a flight and hotel and forward the details to TripIt. Expensify responds to the TripIt event and watches for an airline transaction and creates a report for my trip that was just scheduled. I check into Foursquare at the airport, Expensify responds to that event and automatically begins tracking all of my expenses. While I am on my trip, Expensify continues to respond to events from Foursquare. If there is a transaction that matches a checkin it adds a comment to the transaction noting who I was with at the venue (i.e., dinner with Sam, Doc). After I check back into my home airport again Expensify continues to monitor transactions for a few more hours and then generates a report for me and emails it.\n
  • \n
  • Very different than tightly coupled interactions\n
  • Very different than tightly coupled interactions\n
  • Very different than tightly coupled interactions\n
  • Very different than tightly coupled interactions\n
  • Live Web is more personal, more flexible, more dynamic, more purposeful (less about place), more service-oriented (less about functions)\n
  • Live Web is more personal, more flexible, more dynamic, more purposeful (less about place), more service-oriented (less about functions)\n
  • Live Web is more personal, more flexible, more dynamic, more purposeful (less about place), more service-oriented (less about functions)\n
  • Live Web is more personal, more flexible, more dynamic, more purposeful (less about place), more service-oriented (less about functions)\n
  • \n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • On the Web the client-server model predominates.\nusers, like honeybees, go from site to site, gathering information and maintaining the context of those visits in their heads.\n
  • The most important feature for this discussion is that each Web site is a silo. The location metaphor works fine when what you want to do is confined to that silo. But what happens when you need information from multiple places to accomplish your task?\n
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  • \n
  • \n
  • Fortunately there’s a way to make it easier. \nThe best apps will not be mere clients for a single API. \n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • In the evented web, after an initial subscription, information flows to the user without compulsory means. \nloosely coupled\n
  • \n
  • \n
  • \n
  • when you follow someone on twitter, you are creating a static query against the river of tweets\nwe’ve create a rule language, KRL, to work in this new model. \nTell me when someone mentions my company on Twitter. \nTell me when someone checks into the same place I am.\nTell me when one of my Facebook friends posts an update on their blog.\nTell me when someone calls my customer service line after visiting the customer service page on my company’s Web site.\n \n
  • \n
  • A platform for building Live Web applications would have certain properties. \n
  • A platform for building Live Web applications would have certain properties. \n
  • A platform for building Live Web applications would have certain properties. \n
  • A platform for building Live Web applications would have certain properties. \n
  • A platform for building Live Web applications would have certain properties. \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • 1.) Simpler schema for an event than a request (more standard)\n2.) Generators don’t know who’ll process an event\n3.) No need for specific processing instructions in the event\n4.) Adding and removing components requires less overall coordination\n
  • \n
  • Open source platform for processing events raised by endpoints and taking action based on results\n
  • \n
  • call out the abstract in this expression\n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • Send me email for access to the book. \n\n
  • \n
  • \n
  • Influencers\nDevelopers\nPartners\n\n

The Live Web #SCITDA11 Keynote The Live Web #SCITDA11 Keynote Presentation Transcript

  • The Live WebUsing Event Driven ArchitecturesPhillip J. Windley, Ph.D.Chief Technology OfficerKynetxwww.kynetx.com
  • The Williams Family Life Event: Moving to Utah
  • The Williams Family Life Event: Moving to Utah Change of address Register car Register to vote Enroll child in school Busing City services Child safety Check the commute Tax information
  • The Williams Family Life Event: Moving to Utah Change of address Utilities Register car Housing Register to vote Banking Healthcare Enroll child in school Busing City services Child safety Check the commute Tax information
  • The Live Web
  • A few more...
  • Your DVD’s available here!!!
  • Expensify
  • Expensify
  • Expensify
  • Expensify
  • Expensify
  • What do these scenarios all have in common?
  • Clients working on behalf of the user
  • Clients working on behalf of the userAccess to data through APIs
  • Clients working on behalf of the userAccess to data through APIsReal-time events and alerts
  • Clients working on behalf of the userAccess to data through APIsReal-time events and alertsContext
  • Document Web 1994
  • Document Web Web 1.0 1994 1996
  • Document Web Web Web 1.0 2.0 1994 1996 2002
  • Document Web Web Live Web 1.0 2.0 Web 1994 1996 2002 now
  • Static Data & Dynamic Queries
  • go and get
  • location
  • purpose
  • Successfulapplications willuse many APIs - Sam Ramji
  • Is filtering enough?
  • Rules
  • Dynamic Data & Static Queries
  • do and know
  • Event-driven
  • Event-drivenEntity-centric & controlled
  • Event-drivenEntity-centric & controlledExtensible
  • Event-drivenEntity-centric & controlledExtensibleScalable
  • Event-drivenEntity-centric & controlledExtensibleScalableUniversal
  • events vs requests
  • “this happened” vs “do this”
  • An Example:Anonymous Offers
  • Events are autonomous
  • Event-driven systemsexhibit lower coupling
  • Flow control isreceiver driven
  • Complex Event Patterns
  • select when web pageview “/support/(d+)” setting(issue_num) before (phone phone inboundcall or email received subj.match(re/issue_num/) )
  • Static Web Live Web
  • Static Web Live WebInterface Request-response Events
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semantic
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semanticOntology By prior agreement Self describing(interpretation)
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semanticOntology By prior agreement Self describing(interpretation)Interaction Direct Brokered
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semanticOntology By prior agreement Self describing(interpretation)Interaction Direct BrokeredEvaluation Explicit Emergent(sequencing)
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semanticOntology By prior agreement Self describing(interpretation)Interaction Direct BrokeredEvaluation Explicit Emergent(sequencing)Behavior Planned Reactive
  • Static Web Live WebInterface Request-response EventsBinding Early, static Late, dynamic Pattern-based,References Procedure call, named semanticOntology By prior agreement Self describing(interpretation)Interaction Direct BrokeredEvaluation Explicit Emergent(sequencing)Behavior Planned ReactiveCoordination Centrally Managed Distributed
  • Sign up for a free developer accountat http://www.kynetx.com Come to lunch every Friday (it’s free)
  • The Live Web Contact info: pjw@kynetx.com www.windley.com @windley White paper: http://bit.ly/kntxwpStartup: http://www.windley.com/tags/startup