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ADMIRE Overview

ADMIRE Overview. European Commission 7 th Framework Programme. ADMIRE Partners. Partners: University of Edinburgh, UK (Coordinator) Fujitsu Laboratories of Europe, UK University of Vienna, Austria Universidad Politécnica de Madrid, Spain

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ADMIRE Overview

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  1. ADMIRE Overview European Commission 7th Framework Programme

  2. ADMIRE Partners • Partners: • University of Edinburgh, UK (Coordinator) • Fujitsu Laboratories of Europe, UK • University of Vienna, Austria • Universidad Politécnica de Madrid, Spain • Institute of Informatics, Slovak Academy of Sciences, Slovakia • ComArch S.A., Poland • Finance: • €4.3 Million in costs, €3 Million in EC funding.

  3. ADMIRE Goals Accelerate access to and increase the benefits from data exploitation; Deliver consistent and easy to use technology for extracting information and knowledge; Cope with complexity, distribution, change and heterogeneity of services, data, and processes, through abstract view of data mining and integration; and Provide power to users and developers of data mining and integration processes.

  4. ADMIRE Structure • WP1: High-Level Model and Language Research • Incremental development of models and languages • WP2: Architecture Research • Incremental development of a flexible, scalable, open DMI arch. • WP3: Platform Support & Delivery • Deliver robust service platforms, support users • WP4: Service Infrastructure Development and Enhancement • Develop technology and services to enhance the DMI service infra. • WP5: DMI Tools Development • Develop and integrate tools that make the technology easier to use • WP6: Integrated Applications • Demonstration of validation and performance • WP7: Project Management

  5. Data Mining Process Model – V0

  6. ADMIRE’s High-Level Architecture Unified Systems Management Technologies

  7. ADMIRE Gateways USMT

  8. ADMIRE Components (USMT)

  9. ADMIRE User Tools WFCA SKSA CRM app view OLAP SDA Flood app view DMI Process Designer Portal DMI experts Domain experts Gateway

  10. FFSC Use Case – Hydrological Modelling Target Area SelectionThe user selects using a visual tool available in the ADMIRE user interface the geographical area of interest, concretely a river basin. Mining Parameters DefinitionThe user defines several important parameters of the data mining process, like the length of the deciding interval for meteorological similarity, minimum and maximum amounts of accumulated rainfall and sunshine. These parameters then drive the data mining process. Meteorological Data PreprocessingThe system then starts preprocessing of the available meteorological data, trying to find time intervals with meteorological conditions suitable for further processing – which conform to the parameters given by the user. Runoff ComputationAfter the time intervals from step 3 are available, the system then proceeds towards computing actual runoffs from the data available on hydrological conditions of the river’s basin, the levels of the waterworks on the river, and the inflow-outflow conditions of the waterworks. Data InterpretationAn important step is the interpretation of the runoff data. The user reviews the output data, and draws conclusions as to the evolution of foliage parameters in the target river basin.

  11. ADMIRE Pilot App: CRM • Prediction of churn • Marketing planning: up-selling, cross-selling

  12. ADMIRE Month 8 • Research foundations: • DMI model, high-level language, ontology and architecture – directions defined • Testbed platform construction: • distributed testbed set up based on USMT “v0” and OGSA-DAI v3.0 • Tools integration planning: • plans drawn up for the integration and continued development of a raft of existing tools and platforms • prototyping of use case scenarios • Applications use cases and designs: • two primary pilot apps analysed, over 20 individual use cases identified and codified. Designs for ADMIRE versions of apps complete

  13. Any questions? www.admire-project.eu

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