Objectif
Today, corporate knowledge of large industrial European Companies is scattered amongst many databases at different geographical locations. For example : engineering and manufacturing databases that contain data about the design and the production of a product, field databases that contain information about the product usage at the end-user's site and problems encountered etc., financial data base, safety data bases, marketing data bases...
Existing legacy databases were usually constructed for the purpose of storing and managing administrative information, and are targeted for specific uses and for specific needs. In today's rapidly changing world, and in order to enter the information society, it becomes increasingly important to improve the decision process by making better use of this scattered information.
Although it is technically possible to physically access data at remote locations, it is difficult to correlate the information in these different legacy databases. In an ideal environment , one would like to have a single database that serves the purpose of everyone (i.e. engineering, manufacturing, marketing, field operations etc...). In practice, due to the great variety of specific uses, it is impossible to create a single database that corresponds to everyone's needs.
The present project, NOEMIE, aims at facilitating experience feedback between different organizations in order to improve the decision making process. Leading edge information technologies, such as Case-Based Reasoning and Data Mining, coupled with some business process re-engineering, will allow to make a global reuse of corporate knowledge distributed amongst legacy databases.
The goal of NOEMIE is to develop a methodology and tools for automated reuse of industrial experience from large collections of data in the technical, safety and business domains. It will demonstrate the interest of such a product through the development of two technically oriented applications.
The consortium is made of leading European organizations in software development, Data Mining and Case Based Reasoning as well as end-users directly motivated to apply the results in their specific business.
The end users objectives are to integrate their large amount of data and use them effectively in their day-to-day operations in order to improve cost of maintenance and safety of their operations, and to achieve a concurrent R&D and operations approach.
The main technical objectives will be the integration of two techniques which have shown some promising results in helping to reuse past data and effectively capturing new data for reuse : Data Mining and Case Based Reasoning.
SINTEF and Université Dauphine will develop technologies for collecting and classifying data, ACKNOSOFT will bring CBR and KATE, modify it to allow the reuse of end-user data, ISEI/JRC will develop methodology in reliability domain, Matra Cap System will bring its expertise in data base technologies for integration and correlation.
NOEMIE will start by manually building a prototype of a merge data base (integration of raw data) to help developers in defining and evaluating methodologies and tools. An assessment of result will be done before continuing with the development. The goal is to automatically gather data from legacy database and use them to built the knowledge database. The last part of the project will be dedicated to building the pilot applications, and evaluate the technology to assess its business benefits.
Tasks are shared as follows :
- End-users : to set requirements, demonstrate results and manage the project;
- University : to develop technologies for integration of Data Mining and CBR together.
- Information Technology developers : To bring their tools and their development knowledge. To integrate and validate all methodologies and tools together. To provide the end-users with the prototype of a commercial package. To technically lead the project.
Both end-users are world wide companies that makes a large use of information technologies. Their large legacy data bases have to be integrated within a global system to improve communication between their several business lines and third party. Decision making and business modeling will be supported by the experience data base built from past cases and updated case by case.
Champ scientifique (EuroSciVoc)
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN. Voir: Le vocabulaire scientifique européen.
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN. Voir: Le vocabulaire scientifique européen.
- sciences naturelles informatique et science de l'information bases de données
- sciences naturelles informatique et science de l'information science des données exploration de données
- sciences naturelles informatique et science de l'information logiciel développement logiciel
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Coordinateur
92140 Clamart
France
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