EventWeb towards Experiential Computing 100927

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The next major change in computing is that it is becoming more experience oriented than information oriented. This talk shows how this is evolving and is natural next major revolution in computing and communication.

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  • DATA MODEL:
    To capture events we need a common event model in order to avoid obfuscating event exploration and event-driven access to media.We used E-Model that introduces 6 facets for events (the circle diagram in the next slide) as the initial basis for our data model. We are currently building the formalizations of our data model which is based on this circle diagram. We are formally defining each facet in our data model. Each facet may involve structures and/or induced sub-graphs in addition to the RDF structure. However this is our future work and we will not talk about that here.

  • Lets show three classes in the world – with middle level containing most. The top has 1.5B people covering US, part of Europe, Australia, HongKong, Singapore, and a few percent in other countries. The middle has about 2.5B that is middle class – uses mobile and has corresponding purchasing and social power. The bottom is poor. We want to address the middle. The technology will slowly get to poor.

    We should show icons/photos in this chart corresponding to the above.

    We should have a chart that shows that Singapore is at the heart of World’s Middle class and has great leadership opportunity – economically-socially-politically.
  • We are excited by the 2 ideas ( of the web embracing real world happenings, and the next billion). We feel that we are uniquely positioned to contribute to various areas of its development.
  • Education networks
    parallel college network
    children learning network
    story sharing network
  • Not just a channel for communication and sharing – but a part of life.
  • EventWeb towards Experiential Computing 100927

    1. 1. © Ramesh JainRoyal Society: Web Science 1 RAMESH JAIN JAIN@ICS.UCI.EDU (FACEBOOK, TWITTER: JAIN49) WITH SEVERAL COLLABORATORS
    2. 2. © Ramesh JainRoyal Society: Web Science 2 ExperiencesLife = (Events)
    3. 3. © Ramesh JainRoyal Society: Web Science 3 The Story of Human Civilization is the Story of Experiential Communication among Humans. Sharing Experiences Re-living Experiences Recording Experiences Learning from Experiences
    4. 4. © Ramesh JainRoyal Society: Web Science 4 Communicating Experiences: History Sharing: Languages Democratization: Moveable Print Instantaneous Remote: Telegraph Across Time: WritingMaking it Portable: Paper Instantaneous Remote: Speech
    5. 5. © Ramesh JainRoyal Society: Web Science 5 Communicating Experiences: History Recording: Visual Live broadcast: Video Digital Processing Electrical Audio Recording Live Broadcast WWW: All in one
    6. 6. © Ramesh JainRoyal Society: Web Science 6 Communicating Experiences: Spatial and Temporal Inventions Application Impact Languages Communicate symbolic experiences Written Languages Record Symbolic experiences (time) Paper Portability (space) Print Mass distribution (time and space) Telegraph Remote narrow communication (space) Telephone Remote analog communication (space) Radio Analog broadcasting of sound (space) Television Combining two senses – media (space) Recording media Photos, audio, video (time) Digital processing Machine enhancement and processing Internet Interactive Multimedia communication Most influential Invention in history so far. Future of Communication
    7. 7. © Ramesh JainRoyal Society: Web Science 7 Computing: Relatively young, but growing faster than anything else, ever.
    8. 8. © Ramesh JainRoyal Society: Web Science 8 Computing 1: Data  Device: Mainframe and workstations  Main applications:  Scientific and engineering  Business  Users:  Sophisticated  Expected to be trained
    9. 9. © Ramesh JainRoyal Society: Web Science 9 Computing 2: Information and Communication  Device: PC and Internet  Main applications:  Information  Communication  Users:  Common people in ‘developed world’  Easy access using keyboards
    10. 10. © Ramesh JainRoyal Society: Web Science 10 Computing 3: Experience  Device: Mobile phones  Main applications:  Experiential communication  Experience management  Users:  Humans  No language issues In 2010, about 75% of World population will use Mobiles.
    11. 11. © Ramesh JainRoyal Society: Web Science 11 Mobile Phone Was an Event Notification Device Has now become an Event Sharing device iReports of gas explosion
    12. 12. © Ramesh JainRoyal Society: Web Science 12 Evolution of Web:  Document created by Humans.  Text, Music, Movies  Data collected by Humans  Photos, Audio, … Documents, Data, Events  Events happen.  Most documents describe events and objects in those.  Most data is collected for events.
    13. 13. © Ramesh JainRoyal Society: Web Science 13 Copernican Revolution in Computing Who is the King: Content (Data) or User?
    14. 14. © Ramesh JainRoyal Society: Web Science 14 Content (Data) is the King.
    15. 15. © Ramesh JainRoyal Society: Web Science 15 Lot of information is there. But, do we get what we want? A terrible airplane crash in Timbuktu. More than 300 casualties. Andrew Strauss hits a Century – England wins. Jay Stanley wins the MVP of the game. Again. Which will be on BBC and all Newspapers? Which News is really important? Jay is my grand-son. Does that change priorities?
    16. 16. © Ramesh JainRoyal Society: Web Science 16 Gutenberg’s influence may be ending.  Personal Media  Personalized News  Personalized Alerts Right Information Right Time Right Place The Web is taking us towards Personalized Experiences
    17. 17. © Ramesh JainRoyal Society: Web Science 17 Desirable: You are the King.
    18. 18. © Ramesh JainRoyal Society: Web Science 18 Events take place in the real world. Events result in Data and Documents
    19. 19. © Ramesh JainRoyal Society: Web Science 19 Tsunami 2004 Experiential Data Reports on the event Visualization using data
    20. 20. © Ramesh JainRoyal Society: Web Science 20 Events are ‘Connectors’ Events create ‘Context’ SpatialCausal Experiential Informational TemporalStructural People Things Places Time Experiences Events
    21. 21. © Ramesh JainRoyal Society: Web Science 21 Facebook and Twitter Massive collection of events. Facebook reports 20 Billion updates – 3 Billion Photos – each month. Reporting events as micro-blogs
    22. 22. © Ramesh JainRoyal Society: Web Science 22 Events are currently just a time- indexed database. Time
    23. 23. © Ramesh JainRoyal Society: Web Science 23 Events usually cause domino effect. Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?
    24. 24. © Ramesh JainRoyal Society: Web Science 24 From Micro Events to Situations FromTweets to Revolutions
    25. 25. © Ramesh JainRoyal Society: Web Science 25 EventWeb: Compositing and Linking Time Atomic and Composite Events
    26. 26. © Ramesh JainRoyal Society: Web Science 26 Lets Consider Three different scenarios  Personal Media Management  Memories for Life; LifeLog, …  Situation Detection and Control  Real Time Web  Middle of the Pyramid  Bringing the digital dividend to all people
    27. 27. © Ramesh JainRoyal Society: Web Science 27 We are in the midst of the greatest Media Explosion.
    28. 28. © Ramesh JainRoyal Society: Web Science 28 Dealing with Photo Explosion  3 Billion Photos uploaded on Facebook – every month.  We know that most people in the world are not yet addicted to the Web, but do take photos.
    29. 29. © Ramesh JainRoyal Society: Web Science 29 Meta Data for photos = Event Data
    30. 30. © Ramesh JainRoyal Society: Web Science 30 You bring 1000 photos from a trip, and upload them, and the system does the rest. <39.25.., 161.256…> <05-25-10:11-05-00> <39.25.., 161.256…> <05-25-10:11-08-23> <39.25.., 161.256…> <05-25-10:11-10-24> <40.32.., 162.256…> <05-26-10:10-05-00> <40.33.., 162.256…> <05-26-10:11-09-03> <40.32.., 162.256…> <05-26-10:11-20-00> <37.11.., 70.256…> <05-30-10:11-05-00> <37.11.., 70.256…> <05-30-10:11-08-00> <37.11.., 70.256…> <05-30-10:11-20-00><person: “p1”> <person: “p2”> … <person: “p1”> … <person: “p1”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … 30 e998 e999e498 e499 e500e99 e100e98e1 e2 ......... <40.32.., 162.256…> <05-26-10:10-05-02> e1001e1000 e1002 E [<05-25-10:11-05-00>, <05-30-10:11-20-00>]  The trip last 6 days 11:05:00 11:08:23 11:10:24 25 26 27 28 29 30 10:05:00 10:05:02 11:09:03 11:20:00 11:05:0010:11:05 10:11:08 31 05-2010 time
    31. 31. © Ramesh JainRoyal Society: Web Science 31 Experiential Composition <39.25.., 161.256…> <05-25-10:11-05-00> <39.25.., 161.256…> <05-25-10:11-08-23> <39.25.., 161.256…> <05-25-10:11-10-24> <40.32.., 162.256…> <05-26-10:10-05-00> <40.33.., 162.256…> <05-26-10:11-09-03> <40.32.., 162.256…> <05-26-10:11-20-00> <37.11.., 70.256…> <05-30-10:11-05-00> <37.11.., 70.256…> <05-30-10:11-08-00> <37.11.., 70.256…> <05-30-10:11-20-00><person: “p1”> <person: “p2”> … <person: “p1”> … <person: “p1”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … 31 <40.32.., 162.256…> <05-26-10:10-05-02> e1001e1000 e1002 E [<05-25-10:11-05-00>, <05-30-10:11-20-00>]  The trip last 6 days e998 e999e498 e499 e500e99 e100e98e1 e2 ......... 11:05:00 11:08:23 11:10:24 25 26 27 28 29 30 10:05:00 10:05:02 11:09:03 11:20:00 11:05:0010:11:05 10:11:08 31 05-2010 time
    32. 32. © Ramesh JainRoyal Society: Web Science 32 Informational Composition <39.25.., 161.256…> <05-25-10:11-05-00> <39.25.., 161.256…> <05-25-10:11-08-23> <39.25.., 161.256…> <05-25-10:11-10-24> <40.32.., 162.256…> <05-26-10:10-05-00> <40.33.., 162.256…> <05-26-10:11-09-03> <40.32.., 162.256…> <05-26-10:11-20-00> <37.11.., 70.256…> <05-30-10:11-05-00> <37.11.., 70.256…> <05-30-10:11-08-00> <37.11.., 70.256…> <05-30-10:11-20-00><person: “p1”> <person: “p2”> … <person: “p1”> … <person: “p1”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … <person: “p1”> <person: “p2”> … 32 <40.32.., 162.256…> <05-26-10:10-05-02> e1001e1000 e1002 05-2010 E [<05-25-10:11-05-00>, <05-30-10:11-20-00>]  The trip last 6 days 6 participants ≤ 68 participants 4 participants ≤ 6 11:05:00 11:08:23 11:10:24 25 26 27 28 29 30 10:05:00 10:05:02 11:09:03 11:20:00 11:05:0010:11:05 10:11:08 31 time 11 participants e998 e999e498 e499 e500e99 e100e98e1 e2 ......... Automatic Event-Based organization
    33. 33. © Ramesh JainRoyal Society: Web Science 33 Urgent Challenge: Real Time Web  Result of exponential growth in connectivity and sensors.
    34. 34. © Ramesh JainRoyal Society: Web Science 34 Micro-blogs: Twitter  Each Tweet:  Used to be: What are you doing  Now it is: What’s happening  Really an event reported by Humans  Can associate experiential data along with information.  Time and location associated with each Tweet
    35. 35. © Ramesh JainRoyal Society: Web Science 35 Micro-events: Sensors detecting and chirping (broadcasting) events  Billions of disparate kinds of sensors being placed everywhere.  Each sensor detects ‘basic events’ and broadcasts it in a simple form.  Develop a system to process these micro- events and make them useful.
    36. 36. © Ramesh JainRoyal Society: Web Science 36 From microevents to situations Thermodynamics provides a framework for relating the microscopic properties of individual atoms and molecules to the macroscopic or bulk properties of materials that can be observed in everyday life.
    37. 37. © Ramesh JainRoyal Society: Web Science 37 Example: Cameras in a city  ‘Chirps’ could be of different types  Define behaviors like:  Heavy traffic  Popular event going on  People leaving X area  Violence starting  . . .  Use for Macro-behvior analysis
    38. 38. © Ramesh JainRoyal Society: Web Science 38 Situation Detection and Control Aggregation and Composition Situation Detection Alerts Queries Inform ation
    39. 39. © Ramesh JainRoyal Society: Web Science 39 Emage: Event Image  Divide space (world) into small Pixels of appropriate size.  Assume that each event is a particle of a specific type. Create a Social Image for specific type of events.  A time-ordered sequence of these emages will be similar to a video representing spatio- temporal changes in events of that type.
    40. 40. © Ramesh JainRoyal Society: Web Science 40 Example Social Image- (iphone)
    41. 41. © Ramesh JainRoyal Society: Web Science 41 iPhone  Spatio temporal variation: Event detection
    42. 42. © Ramesh JainRoyal Society: Web Science 42 Operators
    43. 43. © Ramesh JainRoyal Society: Web Science 43 Important Decisions From Tweets: Where to open the next store?
    44. 44. © Ramesh JainRoyal Society: Web Science 44 Swine flu social image and its segmentation into ‘high’ and ‘low ’activity zones.
    45. 45. © Ramesh JainRoyal Society: Web Science 45 Situational controller •Goal •Macro Situation •Rules Micro event e.g. “Arrgggh, I have a sore throat” (Loc=New York, Date=12/09/10) Macro situation Control Action “Please visit nearest CDC center at 4th St immediately” Date=12/09/10 Alert Level=High Level 1 personal threat + Level 3 Macro threat -> Immediate action Situational Recommendation System
    46. 46. © Ramesh JainRoyal Society: Web Science 46 Dream: Web for the Middle of the Pyramid
    47. 47. © Ramesh JainRoyal Society: Web Science 47
    48. 48. © Ramesh JainRoyal Society: Web Science 48 Middle 3 Billion The World: Technology Perspective Top 1.5 Billion Bottom 2 Billion Middle of the Pyramid (MOP): Ready, BUT … Most attention by Technologists – so far. Not Ready
    49. 49. © Ramesh JainRoyal Society: Web Science 49 Direct the innovation and R&D towards the needs of the World’s middle class – the Middle of the Pyramid (MOP). Expand the Middle to cover the Bottom. Highest Bang for the Buck: Tech for the Middle of the Pyramid
    50. 50. © Ramesh JainRoyal Society: Web Science 50 HEATS Networks Health Education Agriculture Transportation Social For addressing all life elements.
    51. 51. © Ramesh JainRoyal Society: Web Science 51 Situational Control HEATS = + Social Networks Microblogs MicroEvents WWW Situation Detection/ Control Awareness / Education Experiential Comm.
    52. 52. © Ramesh JainRoyal Society: Web Science 52 HEATS Connects People for Symbiotic Life Activities.
    53. 53. © Ramesh JainRoyal Society: Web Science 535 Agriculture expert database Data consolidation unit 1. Sensors collect soil data 2. Consolidate 3. Parse information and retrieve accurate advice 4. Prepare and send SMS in local Language. 5. SMS to farmer in local language mKRISHITM: A Personalized Agro-Advisory Services For Rural Farmers
    54. 54. © Ramesh JainRoyal Society: Web Science 54 Use Mobile Phones – no text – for interactions Provides integrated view of : • Disease Risk (Sensor and Model based), •Actual Symptoms and (Human Observation), •Disease Severity based on Images or by Image processing Expert's ConsoleFarmer's Mobile phone application No Typing required, local language support, images and speech useful for illiterate rural masses Used by more than 5,000 Farmers in remote areas in India. Developed by TCS.
    55. 55. © Ramesh JainRoyal Society: Web Science 55 Expert Console Voice query Picture Info specific to crop From public website Ready references for expert Sensor data – if applicable
    56. 56. © Ramesh JainRoyal Society: Web Science 56 Future of the Web: Personalized Experiences for Everybody  Event Based  Experience Centric  Centered around YOU  No Country Left Behind
    57. 57. © Ramesh JainRoyal Society: Web Science 57 Thanks for your time and attention. For questions: jain@ics.uci.edu

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