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Technical Insights - Semantic Web, Funding Analysis

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Frost & Sullivan technical insight analysis discusses Semantic Web -- Funding Analysis

Frost & Sullivan technical insight analysis discusses Semantic Web -- Funding Analysis

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  • 1. Semantic Web--Funding Analysis
    (Technical Insights)
    D2A2-TI
    March 2011
  • 2. Table of Contents
    Executive Summary
    Research Outline
    Key Findings
    Research Methodology
    1. Sectoral Analysis
    Current Technology Trends and Roadmap
    Governmental Grants and Stimulus Funding
    GAP Analysis: Technology Developer Community –Need for Funding
    2. Assessment of Investor Ecosystems
    Investor Networks and Recent Investment Climate
    Future Plans and expectation of Investors
  • 3. Table of Contents
    3. Analyst Insights and Recommendations
    Investment Prospects & Opportunity Evaluation for Investors
    Smart Scouting & Procurement Strategies for Developers
    Key Contacts
    Hot Funding Deals
    About Frost & Sullivan
  • 4. Key Findings
    1
    Twelve different semantic implementations have received funding in 2010 and early 2011. Nine different semantic implementations have been identified with scope for investments
    2
    Venture Capitals, Private Equity Investors and Angel Investors are the major financial contributors. The investment climate for the semantic web space was not very warm for the start ups. Big funding deals were sparse and accompanied by slightly higher number of smaller funding deals
    3
    Semantic Search Engines are expected to become prevalent in 2011 and the years ahead. Semantic Search could bring in new functionalities by providing direct as well as aggregated responses to factual queries posed
    4
    Companies which have acquired minimal initial capitalization, have been successful and then went for more traditional funding in a bigger round. Moreover, such products focus on catering to customer needs rather than concentrating on enhancing the capabilities of the core technology
    Venture Capitals would look forward to invest in companies which have a rich Intellectual Property portfolio. Mere execution plays with weak underlying technology are unlikely to attract funds, and customers in the long run
    Companies trying to venture into the semantic space should concentrate on developing solutions or add-ons that could address limitations of key participant solution offerings. For instance, refining search engine results and interesting add-ons for social networking ecosystems would add value
    Application arenas with a well defined business use case model and a definitive purpose of usage have acquired funding in the recent past. Semantic based mobile and web applications, which are bound to attract more consumers from the social computing space have been the areas of major interest for the funding agencies
    5
    6
    7
  • 5. Semantic Search - Technology Focus AreaCurrent Technology Trends (Contd…)
    SEARCH ENGINE EVOLUTION
    RDFa
    HTML5
    Enhanced Visual Querying By Semantic
    Semantic
    Search
    Clustering and
    Visual Search
    Keywords
    Search Engine
    Semantic Indexing
    Search Engine Optimization (SEO)
    SEMANTIC SEARCH – THE PATH AHEAD
    Unstructured data could be organized and connected to deliver meaningful and customized search results
    Semantic search could help in refining search along two dimensions
    2011 could witness more activities and efforts taken towards structuring data
    Structuring of information and data could eventually bring software agents back into the spotlight
    On the other hand, intelligent analysis of structured information to gain a deeper understanding is also bound to occur
  • 6. Semantic ApplicationsCurrent Technology Trends (Contd…)
    Semantic
    Applications
    Semantic Content Tools
    • Semantic Design Tools
    • 7. Semantic Authoring
    • 8. Visual language Semantics
    • 9. Semantic Content Generation
    • 10. Semantic email, blogging
    • 11. Semantic Tag Clouds
    • 12. Semantic Bookmarking
    Semantic Social Computing
    • Multiple types of inferencing
    • 13. Graphs querying databases
    • 14. Logic generation for uncertainty, conflicts and other primitive tasks
    Automated Reasoning
    • Semantic mashups
    • 15. Policy based Computing
    • 16. Semantic Simulation and planning
    • 17. Silico Sciences
    Knowledge Based Applications
    • Multi-agent systems
    • 18. Social Operating Systems
    • 19. Goal-oriented software engineering platforms
    Semantic Software
    Semantic Architecture
    • Service Oriented architecture
    • 20. Model driven architecture
    • 21. Semantic Interoperability
  • GAP Analysis: Successful Deals and Need for Funding
    Companies which have realized that semantic space has more convergence than technology segmentation have been able to procure funds. A holistic systems approach to deliver a menu of models and algorithms for varied purposes has attracted funds
    Scientific research projects with limited applicability are of little interest to the funding bodies as they lack the potential to meet the in-demand commercial needs
    Application developers have been successful in acquiring indirect form of funding by selling or licensing their inhouse technologies or products. For instance Europe based Talis has acquired 18 million euros, by selling their library division
    Companies which have acquired minimal initial capitalization, have been successful and then went for more traditional funding in a bigger round. Moreover, such products focus on catering to customer needs rather than concentrating on enhancing the capabilities of the core technology
    Lack of business use cases and definite business models restrict funding inflow. Openly available data sources which have poor business models acquire negligible financial incentives since there are no serious investments due to the free model
    GAP ANALYSIS - Need For Funding
    Solutions competing against big competitors would require surplus amounts of funding and is accompanied by a high risk factor. Hence this has been an area of negligible interest for investors However, VC division of corporates and other key participants show interest in niche targeted search engines that are capable of rapidly enhancing existing services
    Companies have been successful in attracting Series A funding compared to others. Founders and investors in early stage seem to prove more on less capital. Series B and other later series funding investments translate to growth and financial aspects unlike Series A which is procured for the innovation or idea and hence has been difficult to procure
    Start-up companies like Bueda and AlphaLabs which have leveraged on the data explosion over the internet have good funding inflow
  • 22. Promising Technology Segments for InvestmentInvestor Networks and Recent Investment Climate
    Key Areas of Investment
    Social Media
    Platform
    Open Data
    Platform
    Semantic Search
    Platform
    Content
    Management
    • The twelve key areas of investment in the semantic space for the year 2010 and early 2011
    • 23. Major funding sources include Venture Capital firms, Private Equity firms and Angel Investors
    • 24. Applications with the potential to serve diverse industry verticals have attracted investors
    Advertising
    Tools
    Text Analysis
    Social
    Analytics
    Metadata
    Storage
    Platform
    Enterprise
    Processes
    Semantic Mobile
    and Web Apps
    Data Sets
    Querying
    Consumer
    Insights
  • 25. Investment Prospects & Opportunity Evaluation for Investors
    Harvey Balls Table – Sneak Preview and Need for Evaluation
    • The Investment Prospects and Opportunity Evaluation for Investors is assessed by making use of the Harvey Balls Table
    • 26. The purpose of this model is to rate the factors/characteristics/drivers/challenges affecting the technology. The shading of the harvey balls indicate (0-1-2-3-4)/(Low, Low-Med, Med, Med-High, High). The table shows the composite rating of each characteristic in the short, medium and long term (or in different regions)
    • 27. The Harvey Balls table has been employed to assess the funding prospects based on four different criteria
    • 28. Return On Investment (ROI): This reflects the prospect of the technology domain under consideration to deliver expected returns. A darker shading reflects the domain with relatively higher ROI.
    • 29. Market Requirement (MR): This reflects the demand for the solution in the market which is created either by the technology push or market pull. A darker shading reflects the domain with high demand.
    • 30. Time Line (TL): The timeline refers to the duration from research stage to commercialization of the solution. A solution that is likely to have a longer time before it is commercialized is represented to be having weak investment prospects (white harvey ball).
    • 31. Market Concentration (MC): Market Concentration is based on the presence of start up companies or established ventures seeking investments. More the companies in need of funds, higher the market concentration and hence high investment prospects (represented in a darker shade)
    • 32. The nine segments of the semantic space have been chosen on the basis of the viability and capability in terms of performance.
  • Low
    High
    Investment Prospects & Opportunity Evaluation for Investors (Contd…)
  • 33. Low
    High
    Investment Prospects & Opportunity Evaluation for Investors (Contd…)
  • 34. COLLABORATION
    STRATEGY
    INNOVATION
    STRATEGY
    RESEARCH
    STRATEGY
    PROCUREMENT
    STRATEGIES
    LICENSING STRATEGY
    INTELLECTUAL
    PROPERTY
    PRODUCT DEVELOPMENT STRATEGY
    Smart Scouting and Procurement Strategies for Developers
  • 35. Viable Applications - Business-to-Consumer ModelSmart Scouting Strategies for Developers (Contd…)
    Personalized
    Task Manager
    Semantic Mobile Applications
    Semantic Social Networking Applications
    Semantic Desktops and Webtops
    E-learning
    Viable Applications for B2C
    Semantic Wikis
    Search Engine Enhancers
    Semantic Instant Messaging
    Web Browser Enhancement
    Intelligent User Interfaces