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Nowadays the current market is in evolution, organisations must work together to ensure their survival. The collaboration partners are heterogeneous and incompatible, which makes the interaction and exchange between them complicated, and requires new technologies to support them. This paper presents a knowledge management-based approach for inter-organisational collaborative processes IOCP modelling. Ontologies represent an effective solution to deal with the heterogeneity and incompatibility problems in different domains. Collaboration ontologies provide a way to promote its modelling. In this domain, there are only few ontologies which cover it partially. The developed system is composed of three part: 1) gathering and formalising collaborative network knowledge; 2) storing knowledge in a knowledge-based to infer the collaborative process model; 3) the IOCP modelling. The heart of this knowledge-based system is a modular ontology conceived to cover as maximum as possible the collaboration domain. The proposed system was conceived as a part of a collaborative platform allowing the modelling of the IOCP in a generic way.

Business intelligence systems provide an effective solution from large volumes of data for multidimensional online computing and analysis. Usually, in a decision-making process, organisations and enterprises, require several internal and/or external cubes which are often heterogeneous. Most of the time, the structure of these cubes is unknown to the decision-makers. To analyse a phenomenon, the decision-maker seeks among sets of cubes, in a collection, the cube which responds better to his need. In this context, we propose an approach that enables decision-makers to express their needs via a query expressed in a natural language, returns top-K relevant cubes and designs/constructs new cubes when no, or few deployed cubes are relevant. We propose a tool called RD-cubes-query implementing our approach in a ROLAP architecture. We use this tool in some experiments to validate our approach.

Plague of modern times, the phenomenon of the traffic accidents hampers heavily resources of the society. The road mows every year thousands of deaths and tens of thousands wounded. This frightening number of victims requires a study of this phenomenon in order to extract all indicators affecting this problem and allow proposing preventive measures. Traditionally, the analysis is performed on alphanumeric data, but some phenomenon as road risk are closely related to their geographic environments where the need to integrate the geographical dimension in the analysis process. In previous work, we have integrated geographic information GI represented by a road object in the analysis of this phenomenon. A map with road network theme is so displayed as a response to a SOLAP query. Graphic markers are used to emphasise certain information like dangerous roads. Although displayed maps may be congested and imperceptible, we so propose to improve the displayed information quality by adapting the displayed map to the needs of decision-makers. Maps with different levels of detail are so provided and associated with different analysis levels. This is achieved through on-the-fly map generalisation, which is a well known concept, widely addressed in cartographic domain that we adapt to SOLAP applications. A geospatial decision-making solution based on a spatial data warehouse and a geospatial tool is developed. Some functionalities of our developed geo-decisional tool are described in the experiment section.