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NEED FOR SYSTEMATIC INNOVATION

INNOVANET Innovation Engineering for the Support of Commercial / Scientific Discovery Don Allen (PIRA E-Media) dona@pira.co.uk Andreas Persidis (Biovista) IST- 2001-38422. NEED FOR SYSTEMATIC INNOVATION. Increasing Competition Innovation speed is becoming key

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NEED FOR SYSTEMATIC INNOVATION

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  1. INNOVANETInnovation Engineering for the Support of Commercial / Scientific DiscoveryDon Allen (PIRA E-Media)dona@pira.co.ukAndreas Persidis (Biovista)IST- 2001-38422

  2. NEED FOR SYSTEMATIC INNOVATION • Increasing Competition • Innovation speed is becoming key • Competitive advantage based increasingly on knowledge content • There is an innovation deficit especially in knowledge intensive industries • Pressure for systematic innovation exists

  3. CURRENT ISSUES • AI and ‘expert mode’ operation of systems are not appropriate • The scientific discovery process needs to be understood • We need to think about: • Knowledge life cycle • Knowledge value chain

  4. GOALS OF INNOVANET • Strategic Roadmap on Systematic Innovation as an aid to R&D investment decision making • Create a model of systematic innovation based on knowledge life cycle and related principles • Align technology provider with end user views • Define a high-level specification of an Innovation Engineering Environment (IEE) • Create an interactive resource that helps design elements of the IEE

  5. PROJECT PLAN • Define a systematic innovation model • Perform a Delphi study • Qualitative questionnaire to finalize model • Quantitative questionnaire to confirm trends • Bibliometric analysis of EC projects, patents and scientific papers to identify trends in objective manner • Gap-fit analysis between current and desired state • Definition of an IEE and other resources • Creation of the Roadmap

  6. INNOVATION KNOWLEDGE LIFE CYCLE

  7. PHASES OF INNOVATION • Problem Identification • Ideation • Approach Development • Operationalisation • Evaluation • Exploitation

  8. KNOWLEDGE ACTIVITIES • Selection of communities/domains • Selection of knowledge sources • Focus on relevant knowledge • Apply knowledge • Gather experience • Rate and share experience

  9. GENERIC KNOWLEDGE OBJECT MANIPULATION FUNCTIONALITIES • Intelligent representation • Match-making • Discovery • Management of Knowledge Objects • Interaction / Communication

  10. SERVICES (1) • Intelligent representation • Editing, Visualization, Alignment, Updating, Packaging, Versioning • Match-making • Query support, semantic matching, personalization, brokering

  11. SERVICES (2) • Discovery • Trends analysis, applications discovery, needs discovery, aggregates discovery • Management of Knowledge Objects • Version control, comparables, terms of use, person/community profiling • Interaction / Communication • Thread comparison, emergence, thread content summarization

  12. FINDINGS (1) • Systematic Innovation (SI) is a controversial concept (considered essential by some and impossible/undesirable by others) • Tools for SI are currently not available in an integrated and usable form • The concepts of knowledge life cycle and knowledge value chain are central to SI • Soft (human-centric) issues which are important to SI are currently not well covered

  13. FINDINGS (2) • Scientific discovery principles need to be better modeled and tools to implement them should be created • Applications and Needs discovery are two steps that bridge the gap between products and needs that should be supported and can lead to SI • In the next 3-5 years software R&D funding should focus on a number of areas including the following: • Flexible representation schemes to cover updating, versioning, packaging and alignment of knowledge • Information resource alignment and interoperability • New Reasoning algorithms to provide synthesis and overview of complex data • Interface and visualisation techniques • Modeling and simulation • Planning and service integration

  14. INNOVANET CONSORTIUM

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