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FAW Inst. für Anwendungsorientierte Wissensverarbeitung Earthquake Engineering Workshop in eScience Applications for Seismology March 7-9 2011, Edinburgh On finding Links between Information Systems and Knowledge Based Systems in Civil Engineering and Seismology / Earthquake Engineering a.Univ.-Prof. Dr. Josef Küng
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2 Facts and Figures FAWAbout the Institute 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) (c) FAW – Johannes Kepler Universität | Information and Knowledge
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3 Information FAWCurrent Research Domains Information Modeling Adaptive modeling tool Modeling dynamic aspects of processes Information-Integration Semantic data integration (in the grid) Datawarehouses Loading Processes (e.g. automatic regression tests) Information-Extraction Intelligent (semantic and rule based) extraction of structured information out of unstructured web pages (c) FAW – Johannes Kepler Universität |
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4 Knowledge Semantic Technologies, Ontologies Using Topic Maps and Ontologies to support queries and decisions Ontology Enineering Case Based Reasoning Similarity queries in Case Based Reasoning Application of Case Based Reasoning Structural Health Monitoring Application of Case Based Reasoning in passive and active Decision Support (c) FAW – Johannes Kepler Universität | FAWCurrent Research Domains
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5 our famous example: tiscover [1] FAWPast Research Work 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-Hagenberg Tiscover AG Hagenberg (c) FAW – Johannes Kepler Universität |
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6 our famous example: tiscover [2] FAWPast Research Work tiscover is more than a web page (c) FAW – Johannes Kepler Universität | Public Terminal (AccessPoint) Reservation & CallCenter Customized Booking Engine Internet home/office
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7 ad Information: AMMI [1] Meta Modeling Tool (Adaptive Modeling tool for Meta models and it Instances) (c) FAW – Johannes Kepler Universität | FAWCurrent Research Work
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8 ad Information: AMMI [2] Instance Modeling View (c) FAW – Johannes Kepler Universität | FAWCurrent Research Work
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9 ad Information: AMMI [3] Administration Module (c) FAW – Johannes Kepler Universität | FAWCurrent Research Work
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10 ad Knowledge: EU-Project IRIS [1] FAWCurrent Research Work 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 |
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11 ad Knowledge: EU-Project IRIS [2] FAWCurrent Research Work (c) FAW – Johannes Kepler Universität | General Structure
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12 Overall Goal – Find the early warning point (c) FAW – Johannes Kepler Universität | ad Knowledge: EU-Project IRIS [2] FAWCurrent Research Work
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13 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 | ad Knowledge: EU-Project IRIS [3] FAWCurrent Research Work
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14 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 | FAWCurrent Research Work ad Knowledge: EU-Project IRIS [4]
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15 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 | FAWCurrent Research Work ad Knowledge: EU-Project IRIS [5]
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16 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 | FAWCurrent Research Work ad Knowledge: EU-Project IRIS [6]
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17(c) FAW – Johannes Kepler Universität | FAWCurrent 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 Content Topics Topics Content
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18(c) FAW – Johannes Kepler Universität | FAWCurrent 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 language Knowledge Representation (at higher level)
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IRIS Ontology Landscape IT-Framework, Current Big Picture FAWEU-FP7-Project IRIS 19 | (c) FAW – Johannes Kepler Universität
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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 Case Based Reasoning in General Case Based Decision Support [1] FAWEU-FP7-Project IRIS 20 | (c) FAW – Johannes Kepler Universität
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CBR for IRIS Adopted to IRIS-Demands More flexible (to be used in different Domains) Our new CBR-Framework for IRIS Case Based Decision Support [1] FAWEU-FP7-Project IRIS 21 | (c) FAW – Johannes Kepler Universität
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General Statements on Cloud Computing 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? Long Term Vision ‘The IRIS Cloud’ [1] FAWEU-FP7-Project IRIS 22 | (c) FAW – Johannes Kepler Universität
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General Statements on Cloud Computing Definition 1 A Cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualised computers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements established through negotiation between 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 (3 rd 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) 1 Rajkumar Buyya, Cloud Computing and Distributed Systems (CLOUDS) Lab, Dept. of Computer Science and Software Engineering, The University of Melbourne, Australia Long Term Vision ‘The IRIS Cloud’ [2] FAWEU-FP7-Project IRIS 23 | (c) FAW – Johannes Kepler Universität
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IRIS Private Cloud Long Term Vision ‘The IRIS Cloud’ [3] FAWEU-FP7-Project IRIS 24 | (c) FAW – Johannes Kepler Universität
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IRIS Private Cloud and Mediator Long Term Vision ‘The IRIS Cloud’ [4] FAWEU-FP7-Project IRIS 25 | (c) FAW – Johannes Kepler Universität
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IRIS Private Cloud and Consumption Long Term Vision ‘The IRIS Cloud’ [5] FAWEU-FP7-Project IRIS 26 | (c) FAW – Johannes Kepler Universität
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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 ) State, Plan for Next Steps FAWEU-FP7-Project IRIS 27 | (c) FAW – Johannes Kepler Universität
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