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S3 knowledge value-generation-discussion_report


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Discussion, challenges and proposed solution on knowledge value generation.
(FInES Cluster Meeting, December 2012)

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S3 knowledge value-generation-discussion_report

  1. 1. FInES Cluster MeetingKnowledge Value Generation Session #3 Contact Point: Eva Coscia Rapporteur: Michele Missikoff
  2. 2. FramingInterested Projects (open list) BIVEE, MSEE, COIN, Premanus, Imagine, ExtremeFactories, EPES, NisB, Comvantage, Venture Gate, Unite, Ensemble.Discussion seeds• Collaborative Intelligence;• semantic knowledge management;• monitoring and governance and early detection methods in dispersed knowledge environments;• knowledge sharing; business intelligence automation
  3. 3. List of Challenges 1/5Key Challenges: focus on K usage and Pragmatics• Dynamicity of knowledge and fuzziness – We need to survive with (partially) incorrect, incomplete knowledge – Accept more imprecision / incompleteness be managed with probability models (Bayesian, Marcovian, ...)• Semantic enrichment of business and production – Use of ontologies to annotate business entities, components, subsystems, ...• Flexibility vs Guidance – Rigid, prescriptive patterns and guidelines may not be widely applicable and maintanable, but the absence of patterns and guidelines will lead to inefficiencies and chaos
  4. 4. LoC 2/5• Quality vs value of knowledge. – Relevance depends on timeliness, recipients, ‘packaging’, ... – Errors: false positive, false negative, right solution to the wrong problem (due to the problem of understanding also the problem) – How can we survive with Faulty Knowledge? (unavoidable, btw) – Value is connected to impact – Impact is connected to the correct usage (by the right actors, in the right moment, on the right problem and domain), that depends on the way K is applied – We need people to change • their perception towards knowledge, seen as a primary value for enterprises, to be systematically managed as a production means • the way they interact and communicate
  5. 5. LoC 3/5• Knowledge acquisition – bottom-up (inductive) from reality vs top-down from conceptualization – knowledge sources: • Active K sources: people (experts), objects, computers • Passive K sources: documents, databases and various repositories, various phenomena, ... – explicit (entities expressing their knowledge) – implicit (actors observing phenomena and invoved entities, to extract knowledge) – Endorsement, for reliability, traceability, non repudiation – Emergence and recognition of given phenomena – collaborative intelligence
  6. 6. LoC 4/5• Knowlege representation and organization – From informal to formal: video, textual documents, databases, terminological resources, RDF, OWL, ...• Knowledge evolution• Harmonization, mapping, integration of K from different sources. – Interoperability needs knowledge, a lot of knowledge about the two (or more) interoperating actors – Sustainable Interoperability, since things change• knowledge diffusion – upon request, to requestor – proactively sent, to needy destination (even if they don’t know)
  7. 7. LoC 5/5Verification and assessment• knowledge usage, how to improve.• verification of impact (is the available knowledge actually used by people?)• Knowledge to manage the transitions, rather than the stable situation• Common understanding vs articulation of diverse opinions:• Multiculturalism: towards constellations of ontologies rather that universal ontologies.• Science Base: to provide a robust foundation to the proposed solutions
  8. 8. Solutions???• Knowledge: the oil of the Third Millennium• Since Lisbon 2010, the EC has indicated that the future of Europe will be Knowledge• We need to converge, within the FInES Cluster, on common models, tools and methodsProposal• Organise a focused Workshop on Knowledge Value for FInES