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Mash-Ups in Telecommunications 2010-2015

Mash-ups are increasingly being developed and used by both consumer and enterprise users in everyday life. Giving the end user the ability to combine information sources into a useable output enhances the value of information and bolsters a sense of empowerment, and by adding telecommunications data such a location, presence, and call control information to a user-generated mash up also creates new revenue opportunities for telecommunications service providers.

This study reviews how information sources resulting from established standards as well as better data access and connectivity are being coupled with tools and capabilities to enable end-users to design and develop innovative services. Insight will explore the various facets of this emerging opportunity. We analyze the leading vendors and the technologies that are creating Mash-up capabilities, report on prominent service providers that illustrate best practices, and reveal areas of high potential for carriers including forecasts of Mash-Up adoption and revenue.

Table of Contents

Chapter-I

EXECUTIVE SUMMARY

  • 1.1. Mashups and the Power of Web 2.0
  • 1.2. What We Found
  • 1.3. What Role for Telcos in Mashups?
  • 1.4. Mashup Market and Revenue Potential

Chapter-II

INTRODUCTION TO MASHUPS

  • 2.1. Definition and Classification of Mashups
  • 2.2. Taxonomy of a Typical Mashup
  • 2.3. Traction for Mashups
  • 2.4. The Technology Underlying Mashups
    • 2.4.1 Web 2.0
    • 2.4.2 SOA
    • 2.4.3 XML
    • 2.4.4 Ajax
  • 2.5. Reservations About Mashups
  • 2.6. The Need for Standards
  • 2.7. What Role for Telcos in Mashups?

Chapter-III

TELCOS AND MASHUPS

  • 3.1. What Mashups Mean for the Telcos
  • 3.2. Why Mashups Now?
  • 3.3. The Enabler is SIP
    • 3.3.1 SIP' s Importance in Mashups
  • 3.4. Social Networking
    • 3.4.1 Social Networking Application Ecosystem
    • 3.4.2 Mobile Social Networking
    • 3.4.3 Social Networking and Mashups
    • 3.4.4 Telco Perspective
  • 3.5. Location Based Services
    • 3.5.1 Mobile LBS
    • 3.5.2 Map-Based LBS
    • 3.5.3 LBS Mashups
  • 3.6. VoIP
    • 3.6.1 The VoIP Value Proposition
    • 3.6.2 Decisive Traction for VoIP
    • 3.6.3 VoIP and Mashups
    • 3.6.4 The Telco Perspective
  • 3.7. Presence
    • 3.7.1 SIP and Presence
    • 3.7.2 Mashups and Presence
    • 3.7.3 The Telco Perspective
  • 3.8. Messaging
    • 3.8.1 SIP and Messaging
    • 3.8.2 Mashups and Messaging
    • 3.8.3 The Telco Perspective
  • 3.9. Software as a Service
    • 3.9.1 SaaS Implementation Methodology
    • 3.9.2 SaaS and Mashups
    • 3.9.3 The Telco Perspective
  • 3.10. Conferencing
    • 3.10.1 Metamorphosis
    • 3.10.2 Conferencing and Mashups
    • 3.10.3 The Telco Perspective
  • 3.11. Streaming
    • 3.11.1 SIP and Streaming
    • 3.11.2 Streaming and Mashups
    • 3.11.3 The Telco Perspective
  • 3.12. Conclusion

Chapter-IV

MASHUPS AND STAKEHOLDERS

  • 4.1. Carrier Strategy Overview
    • 4.1.1 BT
    • 4.1.2 Vodafone
    • 4.1.3 NTT Group
    • 4.1.4 AT&T
    • 4.1.5 SK Telecom
    • 4.1.6 Telecom Italia
    • 4.1.7 Rogers Communications
    • 4.1.8 Sprint
  • 4.2. Other Stakeholders
    • 4.2.1 IBM
    • 4.2.2 Microsoft
    • 4.2.3 Serena Software
    • 4.2.4 Nokia
    • 4.2.5 eBay
    • 4.2.6 Cisco Systems
    • 4.2.7 Google
    • 4.2.8 Yahoo! Inc.
    • 4.2.9 BroadSoft
  • 4.3. Conclusion

Chapter-V

QUANTITATIVE ANALYSIS

  • 5.1. The Telco Revenue Model
    • 5.1.1 Data Transfer
    • 5.1.2 Access Royalties
  • 5.2. Research Methodology
    • 5.2.1 What We Will Forecast
    • 5.2.2 The Base Figures
    • 5.2.3 Construction of the Market Model
  • 5.3. Global Mashup Revenue Opportunity
  • 5.4. Social Networking Revenue Opportunity
  • 5.5. LBS Mashup Revenue Opportunity
  • 5.6. Presence Mashup Revenue Opportunity
  • 5.7. VoIP Mashup Revenue Opportunity
  • 5.8. Messaging Mashup Revenue Opportunity
  • 5.9. SaaS Mashup Revenue Opportunity
  • 5.10. Conferencing Mashup Revenue Opportunity
  • 5.11. Streaming Mashup Revenue Opportunity
  • 5.12. Conclusion

Table of Figures

Chapter-I

  • I-1. Logical Schematic of a Commercial Mashup
  • I-2. Global Mashup Revenue Opportunity for Telcos, 2010-2015

Chapter-II

  • II-1. Logical Schematic of a Commercial Mashup

Chapter-III

  • III-1. Seven Layers of OSI Model
  • III-2. Basic Components of a SIP Network
  • III-3. Example of a SIP Call Flow in Proxy Mode
  • III-4. Support for HTTP in SIP Setup
  • III-5. The Swimwire Mashup Homepage
  • III-6. The Twinkle Twitter Client for iPhone with the Near Me Tab Active
  • III-7. Schematic of the Ribbit SmartSwitch platform
  • III-8. Schematic of the BroadWorks Platform Offered by BroadSoft
  • III-9. OpSource On-Demand Platform
  • III-10 Schematic of the SaaS-enabled Mashup

Chapter-IV

  • IV-1. Mashup Combining Twitter and Google Maps Conjured by Vodafone UK
  • IV-2. Schematic Representation of SAXAE Platform
  • IV-3. Speech Mashup Manager and Speech & Understanding Engine from AT&T Labs Research
  • IV-4. Customization of Mashups Facilitated by IBM Mashup Center
  • IV-5. Securing Information Assets as Facilitated by IBM Mashup Center
  • IV-6. Failed Initiative - Microsoft Popfly
  • IV-7. Schematic Representation of the Outlook Social Connector Function
  • IV-8. Business Mashups Product from Serena Software

Table of Tables

Chapter-V

  • V-1. Global Mashup Revenue Opportunity for Telcos, 2010-2015
  • V-2. Dist. of Global Mashup Rev. Opp. for Telcos by Opp. Type, 2010-2015
  • V-3. Global Mashup Revenue Opportunity by Wireline vs. Wireless, 2010-2015
  • V-4. Regional Distribution of Global Mashup Revenue Opportunity, 2010-2015
  • V-5. Social Networking Mashup Revenue Opportunity, 2010-2015
  • V-6. Dist. of Social Networking Mashup Revenue Opp. by Type, 2010-2015
  • V-7. Social Networking Mashup Rev. Opp. by Wireline vs.Wireless, 2010-2015
  • V-8. Regional Dist. of Social Net. Mashup Rev. Opp. for Telcos, 2010-2015
  • V-9. LBS Mashup Revenue Opportunity, 2010-2015
  • V-10. Dist. of LBS Mashup Revenue Opportunity by Type, 2010-2015
  • V-11. Dist. of LBS Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
  • V-12. Regional Distribution of LBS Mashup Revenue Opportunity, 2010-2015
  • V-13. Presence Mashup Revenue Opportunity, 2010-2015
  • V-14. Dist. of Presence Mashup Revenue Opp. by Type, 2010-2015
  • V-15. Dist. of Presence Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
  • V-16. Regional Dist. of Presence Mashup Revenue Opportunity, 2010-2015
  • V-17. VoIP Mashup Revenue Opportunity, 2010-2015
  • V-18. Dist. of VoIP Mashup Revenue Opportunity by Type, 2010-2015
  • V-19. Dist. of VoIP Mashup Revenue Opp. by Wireline vs. Wireless, 2010-2015
  • V-20. Regional Dist. of VoIP Mashup Revenue Opp. for Telcos, 2010-2015
  • V-21. Messaging Mashup Revenue Opportunity for Telcos, 2010-2015
  • V-22. Distribution of Messaging Mashup Revenue Opp. by Type, 2010-2015
  • V-23. Distribution of Messaging Mashup Revenue Opp.by Wirelines vs. Wireless
  • V-24. Regional Dist. of Messaging Mashup Rev. Opp. for Telcos, 2010-2015
  • V-25. SaaS Mashup Revenue Opportunity for Telcos, 2010-2015
  • V-26. Distribution of SaaS Mashup Revenue Opportunity by Type, 2010-2015
  • V-27. Dist. of SaaS Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
  • V-28. Regional Distribution of SaaS Mashup Rev. Opp. for Telcos, 2010-2015
  • V-29. Conferencing Mashup Revenue Opportunity, 2010-2015
  • V-30. Distribution of Conferencing Mashup Revenue Opp. by Type, 2010-2015
  • V-31. Dist. of Conf. Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
  • V-32. Regional Distribution of Conferencing Mashup Revenue Opp., 2010-2015
  • V-33. Streaming Mashup Revenue Opp. for Telcos, 2010-2015
  • V-34. Dist. of Streaming Mashup Rev. Opportunity by Type, 2010-2015
  • V-35. Dist.of Streaming Mashup Rev. Opp.by Wireline vs. Wireless, 2010-2015
  • V-36. Regional Dist. of Streaming Mashup Revenue Op. for Telcos, 2010-2015
  • V-37. Mashup Revenue by Application Type Summary, 2010-2015
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