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FAW Inst. für Anwendungsorientierte Wissensverarbeitung

Workshop in eScience Applications for Seismology March 7-9 2011, Edinburgh. FAW Inst. für Anwendungsorientierte Wissensverarbeitung . On finding Links between Information Systems and Knowledge Based Systems in Civil Engineering and Seismology / Earthquake Engineering.

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FAW Inst. für Anwendungsorientierte Wissensverarbeitung

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  1. Workshop in eScience Applications for Seismology March 7-9 2011, Edinburgh FAWInst. für Anwendungsorientierte Wissensverarbeitung On finding Links between Information Systems and Knowledge Based Systems in Civil Engineering and Seismology / Earthquake Engineering Earthquake Engineering a.Univ.-Prof. Dr. Josef Küng

  2. FAW About the Institute Facts and Figures • History- 1990 founded as a research institute- 1991 first year in Hagenberg- 1997 regularly institute of JKU- 2005 foundation of FAW-GmbH- 2005 EU-FP6-Project SAFEPIPES- 2008 EU-FP7-Project IRIS- 2010 EU-FP7-Project NERA • Team (FAW-Institut)- currently 15 persons in research and development • R&D- more than 100 successful finished projects and co-operations- among others currently we are coordinating (together with Dr. Wenzel, VCE) the large EU-FP7 project IRIS (Integrated European Industrial Risk Reduction System) Information and Knowledge | (c) FAW – Johannes Kepler Universität

  3. FAW Current Research Domains Information • Information ModelingAdaptive modeling tool Modeling dynamic aspects of processes • Information-IntegrationSemantic data integration (in the grid) • DatawarehousesLoading Processes (e.g. automatic regression tests) • Information-ExtractionIntelligent (semantic and rule based) extraction of structured information out of unstructured web pages | (c) FAW – Johannes Kepler Universität

  4. FAW Current Research Domains Knowledge • Semantic Technologies, OntologiesUsing Topic Maps and Ontologies to support queries and decisions Ontology Enineering • Case Based ReasoningSimilarity queries in Case Based ReasoningApplication of Case Based Reasoning Structural Health Monitoring Application of Case Based Reasoning in passive and active Decision Support | (c) FAW – Johannes Kepler Universität

  5. FAW Past Research Work our famous example: tiscover [1] Introduction • Web Based Destination-Management-System • Access to complete and up-to-date information about Tourism Holiday Destinations • Booking Functions • System Provider:Tiscover AG Innsbruck • Development:FAW-HagenbergTiscover AG Hagenberg | (c) FAW – Johannes Kepler Universität

  6. FAW Past Research Work our famous example: tiscover [2] tiscover is more than a web page Customized Booking Engine Internet home/office Reservation & CallCenter Public Terminal (AccessPoint) | (c) FAW – Johannes Kepler Universität

  7. FAW Current Research Work ad Information: AMMI[1] Meta Modeling Tool (Adaptive Modeling tool for Meta models and it Instances) | (c) FAW – Johannes Kepler Universität

  8. FAW Current Research Work ad Information: AMMI[2] Instance Modeling View | (c) FAW – Johannes Kepler Universität

  9. FAW Current Research Work ad Information: AMMI[3] Administration Module | (c) FAW – Johannes Kepler Universität

  10. FAW Current Research Work ad Knowledge: EU-Project IRIS [1] Introduction • IRIS – Integrated European Industrial Risk Reduction System • Oct. 2008 – Mar 2012, about 40 Partners, mainly form civil engineering domain, 4 partners from IT-Domain, one associated partner form Japan (University of Tokyo ) and US (Drexel University, Stanford University) • Motivation • Within Current practices in risk assessment and management for industrial systems are characterized by its methodical diversity and fragmented approaches. Integration is needed. • The large collaborative project IRIS is proposed to identify, quantify and mitigate existing and emerging risks to create societal cost-benefits, to increase industrial safety and to reduce impact on human health and environment. • Basic Concept • The basic concept is to focus on diverse industrial sector’s main safety problems as well as to transform its specific requirements into integrated and knowledge-based safety technologies, standards and services. • WP7: Monitoring, Assessment, Early Warning, Decision Support • FAW has its main task in this work package – setting up the decision support system. | (c) FAW – Johannes Kepler Universität

  11. FAW Current Research Work ad Knowledge: EU-Project IRIS [2] General Structure | (c) FAW – Johannes Kepler Universität

  12. FAW Current Research Work ad Knowledge: EU-Project IRIS [2] Overall Goal – Find the early warning point | (c) FAW – Johannes Kepler Universität

  13. FAW Current Research Work ad Knowledge: EU-Project IRIS [3] Decision Support System • Passive Decision Support • Providing the right information at the right time to the decision maker in order to support him/her. (i.e. via Data Warehouses or via good organized (good accessible/searchable) document bases • Active Decision Support • A system, that uses some AI (Artificial Intelligence) methods to elaborate a proposal to the decision maker or to do a decision autonomously. (data mining, neural networks, support vector machines, decision trees, case based reasoning, ... ) -> Within IRIS we work in both directions • Active Decision Support -> Case Based Reasoning • Passive Decision Support -> Semantic Networks | (c) FAW – Johannes Kepler Universität

  14. FAW Current Research Work ad Knowledge: EU-Project IRIS [4] Active Decision Support System • Case-based Decision Support(Example: Assessment of Simple Structures (Lamp Posts) Data • Design (Type, Height, Material, ... ) • Measurement (Set of selected eigenfrequencies ,vibration measured after a stimulation) • Visual Inspection (Condition of post and stand,Scratches, oxidation, condition of concrete) Task • Classification of lamp post’s condition | (c) FAW – Johannes Kepler Universität

  15. FAW Current Research Work ad Knowledge: EU-Project IRIS [5] Active Decision Support System • Results • Currently case base consists of 800 measurements of different lamp posts • Above 90% “correct” classifications • Improvement of results: • End-user can adjust parameters (attribute weights, predefined distances) – results are improving • Identify and exclude “unrepresentative cases” (where connection (parameter values  classification result) is irreproducible) • In some ways the inspection process could be adapted (e.g. less “free-text” attributes) In contrast to complex structures like e.g. bridges, an automated assessment of more simple structures, as lamp posts are, looks very promising | (c) FAW – Johannes Kepler Universität

  16. FAW Current Research Work ad Knowledge: EU-Project IRIS [6] Passive Decision Support System • Combining Semantic Nets and Search Engines [1](Example: VCDECIS) • This system builds a basic level of a wide scoped passive Decision Support System • Organization/management of an institution‘s content (documents) to enable easier retrieval of knowledge | (c) FAW – Johannes Kepler Universität

  17. Topics Content Topics Content FAW Current Research Work ad Knowledge: EU-Project IRIS [7] Passive Decision Support • Combining Semantic Nets and Search Engines [2](Example: VCEDEIS ) Components • Search engine • Topic Map (3 layer), currently transferred to OWL • Web Portal • Document upload platform • Topic Map navigator incl. full-text search | (c) FAW – Johannes Kepler Universität

  18. FAW Current Research Work ad Knowledge: EU-Project IRIS [8] • Decentralized Approach • Each group can operate its own Knowledge Base (KB) and Decision Support Systems • IRIS Knowledge Base provides interface to partner KBs • Web Portal to access and administrate IRIS KB • Decision support (data assessment) mainly relies on local measurement data and on local background information (KB) • OWL will be the languageKnowledge Representation(at higher level) | (c) FAW – Johannes Kepler Universität

  19. FAW EU-FP7-Project IRIS IRIS Ontology Landscape IT-Framework, Current Big Picture | (c) FAW – Johannes Kepler Universität

  20. FAW EU-FP7-Project IRIS Case Based Reasoning in General Case Based Decision Support [1] CBR-Cycle (Aamodt&Plaza1994): • Case Base: General knowledge (knowledge base, e.g. models, reports, rules …) and already known cases • Retrieve: Search • Retrieve the most similar case or cases • Reuse: Adaptation • Reuse the information and knowledge in that case to solve the problem • Revise: Verification • Revise the proposed solution • Retain: Learn • Retain the parts of this experience likely to be useful for future problem solving | (c) FAW – Johannes Kepler Universität

  21. FAW EU-FP7-Project IRIS Our new CBR-Framework for IRIS Case Based Decision Support [1] CBR for IRIS • Adopted to IRIS-Demands • More flexible (to be used in different Domains) | (c) FAW – Johannes Kepler Universität

  22. FAW EU-FP7-Project IRIS General Statements on Cloud Computing Long Term Vision ‘The IRIS Cloud’ [1] Classical Computing • Buy & Own: Hardware, System Software, Applications (often to meet peak needs) • 5 • Install, Configure,Test, Verify, Evaluate • Manage: • . . . • Finally, use it • €€€€€ - high Cost Cloud Computing • Subscribe • Use • € - pay for what you use, based on QoS (Quality of Service) every 18 Month? | (c) FAW – Johannes Kepler Universität

  23. FAW EU-FP7-Project IRIS General Statements on Cloud Computing Long Term Vision ‘The IRIS Cloud’ [2] Definition 1A Cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualisedcomputers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements established through negotiationbetween the service provider and consumers. Cloud Services • Software as a Service (e.g. Google Mail, … ) • Platform as a Service (e.g. Google App Engine, Microsoft Azure, … ) • Infrastructure as a Service (e.g. Amazon.com, … ) • Ownership and Exposure • Public/Internet Clouds (3rd party Cloud Infrastructure and services, available on subscription basis) • Private/Enterprise Clouds (Cloud runs within a company’s data center, for internal and/or partners use) • Hybrid/Mixed Clouds (mixed usage of private and public clouds) 1RajkumarBuyya, Cloud Computing and Distributed Systems (CLOUDS) Lab, Dept. of Computer Science and Software Engineering, The University of Melbourne, Australia | (c) FAW – Johannes Kepler Universität

  24. FAW EU-FP7-Project IRIS IRIS Private Cloud Long Term Vision ‘The IRIS Cloud’ [3] | (c) FAW – Johannes Kepler Universität

  25. FAW EU-FP7-Project IRIS IRIS Private Cloud and Mediator Long Term Vision ‘The IRIS Cloud’ [4] | (c) FAW – Johannes Kepler Universität

  26. FAW EU-FP7-Project IRIS IRIS Private Cloud and Consumption Long Term Vision ‘The IRIS Cloud’ [5] | (c) FAW – Johannes Kepler Universität

  27. FAW EU-FP7-Project IRIS State, Plan for Next Steps • Decision Support (WP7) • - State: Enhanced Case Based Reasoning Framework is in an implementation stage • Work on Active Decision Support is promising • - Plan: Continue on CBR, Active Decision Support Knowledge Base and Prototypes (Proof of Concepts) • Data / Knowledge Integration (WP6) and Risk Informed Design (WP8) • - State: IRIS System Landscape is in a stable version • Work on Integration Ontologies is ‘well on track’ (e.g. Bride Ontology is almost finished) • - Plan: Continue on Ontologies, keep integration in mind, (if time, think and work more on the IRIS-Cloud) | (c) FAW – Johannes Kepler Universität

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