Abdelaziz Bouras

Long term archiving of large masses of the lifecycle engineering data is not possible due to the rapid changes in the technologies of creating digital objects, codifying them (syntax and semantics), processing them (decision making), and storing and retrieving them (archive and access). The challenge resides in the production of new knowledge from the large masses of the multidisciplinary data and according to long term re-uses requirements and scenarios (i.e. crash scenario in aeronautics, legal purposes scenario, products reengineering scenario, etc.). To achieve this goal, there is also a real need for new knowledge preservation formal methods and languages, but also test beds and validation suites. The proposal aims at developing methods for forming useful knowledge from large engineering masses of data from multidisciplinary lifecycle domains, using advanced computational methods/technologies and based on new architectures (such as cloud computing architectures).