The Future Web
Dataset+Report - 16/07/2010
It's all about data
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.
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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 2.2 Emerging trends: Video, Social Networking and UGC 2.2.1. Video sharing, a major Web 2.0 trend 2.1.2. Social Networking, the rise of social media 2.1.3. UGC 2.3. Market 2.3.1. Advertising: main Web business 2.3.2. Paid services: only a complementary source of revenues 2.3.3. 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 • Google • Amazon • Yahoo! • Microsoft • Facebook 3.3. Semantic Web 3.3.1. What is the Semantic Web? 3.3.2. Technological roadmap • Resource Description Framework • RDF-Schema • SPARQL • OWL (Web Ontology Language) • XML, RDF and OWL, the heart of semantic web 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 |
• 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 |
• email • searching • e-commerce • social networks • online video • online advertising |
Tab. 1: French online video market growth, Sep 2008 - Sep 2009 Tab. 2: New modes of communication Tab. 3: US UGC consumers by content type in 2008 Tab. 4: Main online advertising models Tab. 5: Breakdown of the global online advertising market by format, 2008-2012 Tab. 6: The global online advertising market, 2008-2012 Tab. 7: Revenue per user, December 2008 Tab. 8: Examples of premium services marketed by Websites Tab. 9: Breakdown of major Internet player revenue in 2008 Tab. 10: Overall Web trends Tab. 11: Major existing platforms on the Internet Tab. 12: Data portability and platform interoperability solutions Tab. 13: Comparison of the different approaches to the Semantic Web Tab. 14: Examples of Semantic Web applications Tab. 15: Example of companies positioned on semantic advertising Tab. 16: Trends with mobile Internet services compared to fixed services Tab. 17: Definitions of the opt-in and opt-out personal data collection modes
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Fig. 1: Evolution towards Web 3.0 Fig. 2: Correspondence between offline and online services Fig. 3: Evolution of the Internet penetration from 2007 to 2009 Fig. 4: Trends in time spent online in Europe and comparison with time spent watching TV Fig. 5: Internet activities in Europe in 2008 Fig. 6: Trends in monthly number of searches, August 2007 - July 2009 Fig. 7: US search market share, November 2009 Fig. 8: Asia-Pacific search market share, September 2009 Fig. 9: Webmail users in the world, early 2009 Fig. 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 NG 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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• Social Graph: Recommendation • Data Web: data-driven Web • Semantic Web: Next Gen Search?
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