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The Future of the Web - Its all about Data - Product Image

The Future of the Web - Its all about Data

  • ID: 1343423
  • Report
  • July 2010
  • Region: Global
  • 118 Pages
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The web is now a major part of consumer daily activities and is radically altering usages. It is also a major market on its own, with revenues coming from online advertising and e-commerce. But the future web could reach a different order of magnitude with the advanced exploitation of data. This report examines the current status of the web, the upcoming disruptive trends and their impacts for the whole ecosystem.

Key questions
- A lot of Web services are now popular, but do they all generate enough revenues?
- What are the key disruptive trends for the future Web?
- How will they impact the current business models?
- How Google, Facebook, Amazon and other players position themselves on the major Web innovations?
- Who is going to benefit the most from the future Web?
- Why data collection has become central in Internet giants business models and activities?
- Will privacy change the landscape of future Web services?
-- Social Graph, Data Web, Semantic Web, Real-time Web, 3D Web, Internet of things
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1. Executive Summary
1.1. The Web is already transforming very rapidly, around a few services and players
1.2. There are three major radical trends that will shape the Future Web
1.3. It's all about the data
2. The State of the Web
2.1. Usage
2.1.1. Widening range of services used by ever more people
2.1.2. Searching remains most popular activity on Internet
2.1.3. Communication: Email and Instant Messaging
2.1.4. E-Commerce
2.1.5. Digital Content and Entertainment
2.1.6. Emerging trends: Video, Social Networking and UGC
2.1.7. Video sharing, a major Web 2.0 trend
2.1.8. Social Networking, the rise of social media
2.1.9. UGC
2.2. Market
2.2.1. Advertising: main Web business
2.2.2. Paid services: only a complementary source of revenues
2.2.3. E-commerce: not to be neglected
3. Main innovations on the Web
3.1. Social graph
3.1.1. An open network of social networks
3.1.2. Data portability, a link between platforms
3.1.3. Platform interoperability
3.1.4. Reaching fully functioning social graph is long-term process
3.1.5. Potential business models to make most of social graph
3.2. Data Web
3.2.1. Data-driven Web, the concept
3.2.2. Applications
3.2.3. Market landscape
3.3. Semantic Web
3.3.1. What is the Semantic Web?
3.3.2. Technological roadmap
3.3.3. The Next Gen Search?
3.3.4. Monetising the Semantic Web
3.3.5. Key players
3.4. Other trends
3.4.1. Real-time Web
3.4.2. Mobile Web
3.4.3. 3D Web
3.4.4. Internet of Things
4. Impacts on the ecosystem
4.1. Data wars
4.1.1. Radical trends focus on data
4.1.2. New approaches for data control
4.1.3. Future business models
4.2. Impacts of privacy and data regulation
4.2.1. The types of personal data collected and their uses
4.2.2. Current regulation on personal data
4.2.3. Google
4.2.4. Facebook
4.3. Impacts of Future Web for online service players
4.3.1. Current positioning of Internet giants
4.3.2. Internet giants fighting for dominance
4.4. Impacts for media players
4.5. Impacts for telcos
4.5.1. Impacts on the network
4.5.2. Telcos assets
4.5.3. Telcos opportunities

Table 1: French online video market growth, Sep 2008 - Sep 2009
Table 2: New modes of communication
Table 3: US UGC consumers by content type in 2008
Table 4: Main online advertising models
Table 5: Breakdown of the global online advertising market by format, 2008-2012
Table 6: The global online advertising market, 2008-2012
Table 7: Revenue per user, December 2008
Table 8: Examples of premium services marketed by Websites
Table 9: Breakdown of major Internet player revenue in 2008
Table 10: Overall Web trends
Table 11: Major existing platforms on the Internet
Table 12: Data portability and platform interoperability solutions
Table 13: Comparison of the different approaches to the Semantic Web
Table 14: Examples of Semantic Web applications
Table 15: Example of companies positioned on semantic advertising
Table 16: Trends with mobile Internet services compared to fixed services
Table 17: Definitions of the opt-in and opt-out personal data collection modes

Figure 1: Evolution towards Web 3.0
Figure 2: Correspondence between offline and online services
Figure 3: Evolution of the Internet penetration from 2007 to 2009
Figure 4: Trends in time spent online in Europe and comparison with time spent watching TV
Figure 5: Internet activities in Europe in 2008
Figure 6: Trends in monthly number of searches, August 2007 - July 2009
Figure 7: US search market share, November 2009
Figure 8: Asia-Pacific search market share, September 2009
Figure 9: Webmail users in the world, early 2009
Figure 10: IM market share in US, France and China, July 2008
Figure 11: Penetration of different communication platforms
Figure 12: Part of e-commerce in the retail market
Figure 13: Part of online users who already bought online in the US and Europe
Figure 14: Products most commonly purchased online in the US in 2008
Figure 15: Content and entertainment activities in Europe in 2008
Figure 16: Global Internet activities in the world in 2008
Figure 17: Number of videos viewed online in the US, 2007-2009
Figure 18: Number of unique visitors to video sites in the US, 2007-2009
Figure 19: Percentage of US Internet users who have watched a video online, 2007-2009
Figure 20: Average time spent watching online videos in the US per viewer, 2007-2009
Figure 21: Leading video sites in the US by number of unique visitors, October 2009
Figure 22: Social networking growth by worldwide region
Figure 23: Monthly unique visitors on major social networks in the US
Figure 24: Reasons why US Internet users use social networking sites
Figure 25: US UGC creators and consumers (% of Internet users)
Figure 26: Percentage of Internet users, ages 16 to 54, who have ever done one of these activities, in selected countries, 2006-2008
Figure 27: Percentage of participatory visits compared to all Website visits in the US, May 2007
Figure 28: Typology of French 15-29 Internet users, May 2008
Figure 29: The social techno-graphic profile of US online adults, Q2 2008
Figure 30: B2C e-commerce revenues, 2006-2012
Figure 31: Social graph representations
Figure 32: Web users manage different separate identities online
Figure 33: OpenID, a single online identity
Figure 34: Facebook Connect
Figure 35: Description of MySpaceID
Figure 36: Social graph platform wars
Figure 37: Technical description of OpenSocial
Figure 38: Top applications and developers on Facebook in February 2010
Figure 39: Yahoo! Updates API
Figure 40: Example of a Dopplr member's personal page
Figure 41: The Open Stack
Figure 42: Description of the Google Social Graph API
Figure 43: MySpace Interaction Ad
Figure 44: Examples of Facebook's ad initiatives to tape into its social graph
Figure 45: Traditional Amazon recommendations
Figure 46: What if Amazon implemented Facebook Connect?
Figure 47: Data-driven Web and cloud computing
Figure 48: Example of scene completion application
Figure 49: Searching the deep Web
Figure 50: DPI overview
Figure 51: Google MapReduce and GFS principles
Figure 52: Comparison of Amazon bandwidth consumption
Figure 53: Yahoo!'s Internet-scale private cloud services
Figure 54: Microsoft Azure Services Platform
Figure 55: Evolution of the Web
Figure 56: From the Web of documents to the Semantic Web
Figure 57: Semantic Web Architecture
Figure 58: The RDF triple concept
Figure 59: Newssift search result page
Figure 60: Dynamic advertising based on semantic analysis
Figure 61: Example of structured information in Yahoo! search results
Figure 62: Information diffusion and impact
Figure 63: Twitter growth by age group
Figure 64: Mobile Internet active user penetration
Figure 65: Value chain and positioning of major players
Figure 66: Virtual world segmentation by average user age and number of active visitors
Figure 67: Example of brand engagement in the virtual world Habbo
Figure 68: Value chain for virtual worlds designed to be a source of revenue
Figure 69: Principles of the Internet of Things
Figure 70: Maturity for RFID and Internet of Things by vertical market
Figure 71: Evolution towards Web 3.0
Figure 72: Overall strategy for monetisation
Figure 73: Google Dashboard
Figure 74: Example of a Beacon update appearing in the News Feeds of a Facebook member's contacts after she rated a video on the Blockbuster site
Figure 75: The ‘like' button by Facebook on Levi's
Figure 76: Managing privacy settings on Facebook (May 2010)
Figure 77: Availability of personal data by default settings on Facebook, 2005 and 2010
Figure 78: Last.fm's profile-based recommendations
Figure 79: BBC iPlayer's related content recommendations
Figure 80: Community-based recommendations on ContentWise
Figure 81: Affinity, asocial networking recommendation engine for VOD content
Figure 82: What if VOD service CanalPlay implemented social graph-based recommendations?
Figure 83: Semantic Web and NGN
Figure 84: SPICE
Figure 85: Vodafone 360 phone address book
Figure 86: Recommendation service from Orange
Figure 87: Phorm principles
Figure 88: Phorm application
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