Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

We have developed a framework to support development of ontology based Web applications. This framework is composed of a tree-view browser, an attribute selector, the ontology persistence module, an ontology query module, and a utility class that allows the users, to plug-in their own customized functions. The framework supports SPARQL-DL query language. The purpose of this framework is to shield the complexity of ontology from the users and thereby ease the development of ontology based Web applications. Having high quality ontology and using this framework, the end-users can develop Web applications in many domains. For example, a professor can create highly customized study guides; a domain expert can generate the Web forms for data collections; a geologist can create a Google Maps mashup. We have also reported three ontology-based Web applications in education, meteorology and geographic information system.

This thesis reports an ontology-based approach to automatic generation of highly tailored GUI components that can make customized data requests for the end users. Using this GUI generator, without knowing any programming skill a domain expert can browse the data schema through the ontology file of his/her own field, choose attribute fields according to business's needs, and make a highly customized GUI for end users' data requests input. The interface for the domain expert is a tree view structure that shows not only the domain taxonomy categories but also the relationships between classes. By clicking the checkbox associated with each class, the expert indicates his/her choice of the needed information. These choices are stored in a metadata document in XML. From the viewpoint of programmers, the metadata contains no ambiguity; every class in an ontology is unique. The utilizations of the metadata can be various; I have carried out the process of GUI generation. Since every class and every attribute in the class has been formally specified in the ontology, generating GUI is automatic. This approach has been applied to a use case scenario in meteorological and oceanographic (METOC) area. The resulting features of this prototype have been reported in this thesis.

Little is known about the distribution, abundance, or life histories of the Northern Saw-whet Owl (Aegolius acadicus) in the Southern Appalachian Mountains of Northeast Tennessee. This study relied upon the Pennsylvania Protocol of audio playback of a Northern Saw-whet Owl call to monitor for owl presence at various areas above 3,500 feet in elevation. Owls were found at multiple areas in Northeast Tennessee, including Roan Mountain, Unaka Mountain, Rocky Fork, and the Pond Mountain Area. Statistical analysis revealed that these owls were not limited by habitat, showing equal presence in Hardwood habitats along with Spruce and/or Fir habitats. Data also revealed that the owls showed a statistical preference for higher elevations at the surveyed sites. The habitat and elevation preferences, coupled with the locations where owls were detected, allow for a greater understanding of the life histories and population distribution of the Northern Saw-whet Owl in the Southern Appalachian Mountains.

La thèse soutenue est que l'utilisation conjointe de plusieurs modèles de connaissances pour représenter des connaissances et raisonner permet élégamment de modéliser des connaissances et de résoudre des problèmes complexes. Cette thèse propose des transitions de modèles entre les modèles de connaissances OWL, Graphes Conceptuels et UML. L'originalité de cette thèse réside en la modélisation centralisée de connaissances au sein d'un système de connaissance et en l'action de faire transiter ces connaissances d'un modèle à un autre du système au fur et à mesure des besoins exigés par la modélisation et les raisonnements. L'objectif principal de ces transitions de modèles de connaissances est double. D'une part, il s'agit de bénéficier de manière relativement aisée des différences d'expressivités entre les modèles et ainsi aboutir à un système de connaissance au pouvoir expressif fort. D'autre part, cela permet lors de la conception et l'exploitation d'une modélisation, d'utiliser les modèles qu'on connaît ou les mieux adaptés. Les outils de chaque modèle peuvent ainsi être utilisés sur les connaissances obtenues, offrant une complémentarité d'utilisation de ces modèles.

Graduation date: 1993

No description available.

Universiẗat Fridericiana, Diss--Karlsruhe, 2007. / Internetausg.: Ähnlichkeitsbasierte Modellierungsunterstützung für Geschäftsprozesse.

Thesis (doctoral)--Rijksuniversiteit te Groningen, 1983. / Includes bibliographical references (p. 83-88).

Internet of Things (IoT) is becoming commonplace in people's daily life. Even, many governments' authorities have already deployed a very large number of IoT sensors toward their smart city initiative and development road-map. However, lack of semantics in the presentation of IoT-based sensory data represents the perception complexity by general people. Adding semantics to the IoT sensory data remains a challenge for smart cities and environments. In this thesis proposal, we present an implementation that provides a meaningful IoT sensory data notifications approach about indoor and outdoor environment status for people and authorities. The approach is based on analyzing spatio-temporal thresholds that compose of multiple IoT sensors readings. Our developed IoT sensory data analytics adds real-time semantics to the received sensory raw data stream by converting the IoT sensory data into meaningful and descriptive notifications about the environment status such as green locations, emergency zone, crowded places, green paths, polluted locations, etc. Our adopted IoT messaging protocol can handle a very large number of dynamically added static and dynamic IoT sensors publication and subscription processes. People can customize the notifications based on their preference or can subscribe to existing semantic notifications in order to be acknowledged of any concerned environmental condition. The thesis is supposed to come up with three contributions. The first, an IoT approach of a three-layer architecture that extracts raw sensory data measurements and converts it to a contextual-aware format that can be perceived by people. The second, an ontology that infers a semantic notification of multiple sensory data according to the appropriate spatio-temporal reasoning and description mechanism. We used a tool called Protégé to model our ontology as a common IDE to build semantic knowledge. We built our ontology through extending a well-known web ontology called Semantic Sensor Network (SSN). We built the extension from which six classes were adopted to derive our SENS-IT ontology and fulfill our objectives. The third, a fuzzy system approach is proposed to make our system much generic of providing broader semantic notifications, so it can be agile enough to accept more measurements of multiple sensory sources.