I N N O V AN E T INNOVANET Innovation Engineering for the Support of Commercial / Scientific Discovery Don Allen (PIRA E-Media) Andreas Persidis (Biovista) IST

I N N O V AN E T 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

I N N O V AN E T 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

I N N O V AN E T 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

I N N O V AN E T 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

I N N O V AN E T INNOVATION KNOWLEDGE LIFE CYCLE

I N N O V AN E T PHASES OF INNOVATION Problem Identification Ideation Approach Development Operationalisation Evaluation Exploitation

I N N O V AN E T KNOWLEDGE ACTIVITIES Selection of communities/domains Selection of knowledge sources Focus on relevant knowledge Apply knowledge Gather experience Rate and share experience

I N N O V AN E T GENERIC KNOWLEDGE OBJECT MANIPULATION FUNCTIONALITIES Intelligent representation Match-making Discovery Management of Knowledge Objects Interaction / Communication

I N N O V AN E T SERVICES (1) Intelligent representation –Editing, Visualization, Alignment, Updating, Packaging, Versioning Match-making –Query support, semantic matching, personalization, brokering

I N N O V AN E T 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

I N N O V AN E T 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

I N N O V AN E T 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

I N N O V AN E T INNOVANET CONSORTIUM INMARK Estudios y Estrategias S.A. Biovista FhG-IPSI VUB STARLab, Department of Computer Science Istituto Trentino di Cultura - Istituto per la Ricerca Scientifica e Tecnologica PIRA bit media e-Learning solution