Relationship analysis : improving the systems analysis process

A significant aspect of systems analysis involves discovering and representing entities and their inter-relationships. Guidelines exist to identify entities but do not provide a rigorous and comprehensive process to explicitly capture the relationship structure of the problem domain. Whereas, other analysis techniques lightly address the relationship discovery process, Relationship Analysis is the only systematic, domain-independent analysis technique focusing exclusively on a domain\u27s relationship structure. The quality of design artifacts, such as class diagrams, and development time necessary to generate these artifacts can be improved by first representing the complete relationship structure of the problem domain. The Relationship Analysis Model is the first theory-based taxonomy to classify relationships. A rigorous evaluation was conducted, including a formal experiment comparing novice and experienced analysts with and without Relationship Analysis. It was shown that the Relationship Analysis Process based on the model does provide a fuller and richer systems analysis, resulting in improved quality of and reduced time in generating class diagrams. It also was shown that Relationship Analysis enables analysts of varying experience levels to achieve a similar level of quality of class diagrams. Relationship Analysis significantly enhances the systems analyst\u27s effectiveness, especially in the area of relationship discovery and documentation resulting in improved analysis and design artifacts

Utilisation de l'humidité du sol comme indicateur de changement climatique

Dans le contexte actuel de changement climatique, le Québec doit s’attendre à voir ses températures grimper, notamment l’hiver, ainsi que les précipitations liquides. Ceci aura un impact non négligeable sur le cycle hydrologique des bassins versants québécois. L’objectif de cette étude est d’évaluer si l’humidité du sol pourrait être un indicateur de changement climatique fiable afin d’anticiper certaines modifications des débits par exemple. Le bassin versant étudié, celui de la rivière Gatineau au sud-ouest du Québec, a une superficie de 23 724 km2 et est essentiellement forestier. Le modèle hydrologique Hydrotel, permettant de subdiviser le bassin en six sous-bassins et 715 UHRH, et séparant le sol en trois couches, a été utilisé. Le calibrage s’est effectué manuellement en mettant l’emphase sur la période estivale et a donné de bons résultats sur quatre sous-bassins avec des coefficients de Nash-Sutcliffe avoisinant les 0,8. Les données d’humidité du sol utilisées pour cette étude étaient les sorties d’Hydrotel au pas de temps journalier pour les trois couches de sol. La période de contrôle (1975-2001) a permis d’établir que l’humidité du sol dépendait davantage des conditions climatiques pour certains mois (notamment l’été) alors qu’au printemps, la fonte de la neige saturait presque constamment les trois couches de sol. Les simulations à l’horizon 2056, effectuées grâce aux données climatiques du MRCC (2042-2068), ont montré qu’une baisse de l’humidité du sol au cours de l’été et de l’automne était à prévoir. La variabilité interannuelle devrait quant à elle augmenter. Au niveau spatial, certaines régions au sud du bassin devraient présenter un comportement particulier. La végétation, le type de sol ainsi que les conditions climatiques ont été définis comme étant les facteurs principaux responsables de la variabilité spatiale

Managing complex taxonomic data in an object-oriented database.

This thesis addresses the problem of multiple overlapping classifications in object-oriented databases through the example of plant taxonomy. These multiple overlapping classifications are independent simple classifications that share information (nodes and leaves), therefore overlap. Plant taxonomy was chosen as the motivational application domain because taxonomic classifications are especially complex and have changed over long periods of time, therefore overlap in a significant manner. This work extracts basic requirements for the support of multiple overlapping classifications in general, and in the context of plant taxonomy in particular. These requirements form the basis on which a prototype is defmed and built. The prototype, an extended object-oriented database, is extended from an object-oriented model based on ODMG through the provision of a relationship management mechanism. These relationships form the main feature used to build classifications. This emphasis on relationships allows the description of classifications orthogonal to the classified data (for reuse and integration of the mechanism with existing databases and for classification of non co-operating data), and allows an easier and more powerful management of semantic data (both within and without a classification). Additional mechanisms such as integrity constraints are investigated and implemented. Finally, the implementation of the prototype is presented and is evaluated, from the point of view of both usability and expressiveness (using plant taxonomy as an application), and its performance as a database system. This evaluation shows that the prototype meets the needs of taxonomists