Short Web 3 0 Yke 09 30 09


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Presentation by Yana Kane-Esrig at theIxDA Northern NJ / NNJ UX Meetup on September 30, 2009

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Short Web 3 0 Yke 09 30 09

  1. 1. “Web 3.0” Yana Kane-Esrig September 30, 2009 Defining Web 3.0 Web 1.0: access to information Linked text, search engines Web 2.0: Web 1.0 + : Social networking, User Generated Content, multimedia, entertainment, mash-up applications Broadband, Internet as platform ( “read-write web”: pages or screens that the user can edit and re-shape, browser-based applications), communication, interoperability (APIs), collaboration tools Web 3.0: Web 2.0 + “collective intelligence” infrastructure and culture Not one capability, but many separate, yet overlapping and synergistic trends Federation of knowledge creation (knowledge mash-ups?) 2 | “Web 3.0” | October 2009 1
  2. 2. Web 3.0 Themes Crowdsourcing and open sourcing becoming mainstream: large scale distributed production of information, knowledge and culture Contextual / implicit web: user gets action and information that they need when they need it delivered to them Semantic web: knowledge based use of information Social graph: filter the web for end user, filter end users for marketers Measurable web: measure effectiveness of ads, segment users, quantify “sentiment” “Internet of things”: sensors allow linking “physical world” and “cyber world” Mobile web Separate, yet overlapping and synergistic trends that enable: Greater variety of models for monetizing the web Better user experience on the web and enabled by the web 3 | “Web 3.0” | October 2009 Crowdsourcing and Open Sourcing Becoming Mainstream Crowdsourcing: task outsourced to community via open call. Open sourcing: activity initiated by community UGC: user creates content and makes it publicly available Variety of project types, business models, areas of application Competition, competitive collaboration, “divide and conquer”, collaboration , collaborative filtering, prediction markets Commercial use of crowdsourcing: P&G, IBM, Threadless, istock, current TV, Marketocracy R&D, product design, software design and development, stock photos, citizen journalism, journalism scientific research, investment research investment… Crowdsourcing & open sourcing are both enabled by and are an enabler of “Web 3.0” Creating semantic web content and metadata (tagging) Helping machines use sensor readings (e.g., marking up or tagging visual data) 4 | “Web 3.0” | October 2009 2
  3. 3. Crowdsourcing and Open Sourcing - Development of Infrastructure Emergence of “reputation economy”: Reviews, recommendations, discussions of products drive purchasing Credibility, reputation, position on “leader board”, connectedness is “coin of the realm” Companies specializing in crowdsourcing platforms Examples: IBM IdeaJam, InnoCentive, TopCoder, Chaordix, Amazon Mechanical Turk Academic research into crowdsourcing project life-cycle and management “The Metropolis Model” The Model “Ultra Large Scale” systems 5 | “Web 3.0” | October 2009 Contextual / Implicit web “Get rid of pages” – user gets action and information that they need when they need it delivered to them Based on user’s own behavior and behavior of their “social graph” User gets value from having their behavior tracked and recorded Extreme form of “personalization” and “recommendation” Browser or application “guesses” the user’s intent and acts as a proactive intelligent agent (e.g., finds, formats and displays relevant information) 6 | “Web 3.0” | October 2009 3
  4. 4. Semantic Web “Semantic web” seems to refer to three inter-related, but different things: 1) Formal descriptions of concepts and relationships in a knowledge domain; 2) Tools and knowledge repositories to enable specification and use of metadata about concepts and object: describing /tagging them, specifying relationships among them and the types of inferences that can be made 3) Changes in online user experience enabled by combining this knowledge about resources available to serve the user with insight into the user’s intent Users interact not with “web pages” and bits of text but with “conceptual objects”/concepts. Data becomes independent of application and can be reused across the web Can build applications to displace routine tasks done by humans: e.g., automate routine searches and scanning of documents to find the relevant bits, compute answers by combining multiple bits of data “on the fly” 7 | “Web 3.0” | October 2009 Social Graph Vocabulary: Friend of A Friend (FOAF) FOAF: machine-readable (and human readable) ontology describing people, the links between them and the things they create and do ((e.g. photos, calendars, weblogs) The FOAF “grass roots” project is creating a Web of machine-readable page Anyone can use FOAF to describe him or herself. Some social networking site profiles can be used to generate a FOAF (e.g., Facebook has a tool for that) FOAF allows groups of people to describe social networks (create their social graphs) without the need for a centralized database. FOAF makes social graph portable across applications / social networks FOAF makes it possible to find people who “have something in common” (common friend, common interest, etc.) 8 | “Web 3.0” | October 2009 4
  5. 5. Social Graph Vocabulary Use Case Example: Aardvark ( – currently uses Facebook. Promises to expand to other social networks 9 | “Web 3.0” | October 2009 Measurable web Measurable web: derive (and monetize) knowledge from behavior of users and from web content Improve customer experience in a variety of verticals Improve web itself (e.g., refine search algorithms, web site design) To monetize web it is necessary to measure and analyze real-time user behavior Measure ROI, adjust ad campaigns Brand management: sentiment tracking Ad targeting based on “faces, not places” Identify, build relationships with “influencers” Managing customer experience in real time is becoming the norm Identifying and defusing complaints. Preemptive information dissemination 10 | “Web 3.0” | October 2009 5
  6. 6. Internet of Things Objects an people cast “information shadow” in the cyberworld Sensors linking “physical world” and “cyber world” Location, orientation /movement of device, speech/sound recognition, image/video, touchscreens Examples: Gracenote: music recognition. Layar: augmented reality enhanced mobile browser Other sensors (e.g., energy consumption of device, health monitors) One type of application: smart grid to reduce energy consumption Combining sensor data with user intent, profile, behavior, context Coordination of speech recognition and location in search Voice search initiated based on gesture Google iPhone search app Image recognition is easier if know where you are and when 11 | “Web 3.0” | October 2009 Mobile Web Smartphones, Netbooks adoption rapidly growing Devices equipped with multiple sensors iPhone applications downloads went from 1 billion to 1.5 billion in 3 months 15 Adopters of smartphones and laptops equipped with cellular Internet different from non-adopters on a wide range of technology and economic activity behaviors (greater difference than due to demographics) Game devices, book readers (Kindle) impacting usage patterns, business model expectations Switch from “mobile-specific web to “full web mobile specific web” full web” However, user interface does need to be mobile-specific Users expect the same capabilities and content on mobile as they get on PC. Users expect performance similar to what they get on fixed broadband. Distinction between “on-deck” and “off deck” content losing importance 12 | “Web 3.0” | October 2009 6
  7. 7. Let’s Discuss! Do any of the themes impact your current or future activities (work-related or personal)? What do you see as the key emerging themes in the online/communications world? Why do you consider them important? How are they likely to impact you at work and/or in your personal life? Is there any type of tool or service that you wish was around to help you make better use of existing or emerging capabilities of the online/communications world? 13 | “Web 3.0” | October 2009 7