Dans des situations où la perception visuelle est fortement contrainte ou déficiente, il est nécessaire de rendre perceptible l'information dans une modalité non visuelle, tout en prenant en compte des capacités sensorielles et mnésiques humaines. Par exemple, un non-voyant, souhaitant prendre connaissance d'un itinéraire, devra le parcourir de façon non visuelle et le mémoriser. Cependant, outre l'aspect matériel, la mise en œuvre de solutions alternatives (non visuelles) demeure confrontée aux capacités cognitives de l'utilisateur (compréhension, mémorisation, intégration de plusieurs informations, etc.). L'objet de cette thèse est de contribuer à la conception de techniques d'interactions permettant d'optimiser la transmission non visuelle d'informations. A ces fins, j'ai exploré l'apport de la multimodalité comme moyen d'optimisation permettant d'outrepasser les limites de la mémorisation. Je me suis concentré sur l'étude des techniques d'interaction basées sur les modalités auditives et tactiles, en limitant au maximum l'utilisation de la parole, afin de concevoir des techniques pour des environnements différents (flexibilité), d'optimiser l'utilisation de canaux perceptifs (exploitation des propriétés du son dans des messages audio pour transmettre plus d'informations, par exemple), d'éviter de limiter mes techniques par la barrière de la langue ou de sa compréhension et enfin, pour explorer d'autres solutions que la synthèse vocale seule. Les travaux de ma thèse ont mené à la conception, à l'implémentation et à l'évaluation de techniques d'interaction multimodale non visuelle, en réponse à différents contextes, dont, en particulier, ceux de la transmission d'informations de type <valeur>, <position> (couple de coordonnées) et <itinéraire> (séquence de couples direction-distance). Pour parvenir à concevoir mes interactions, j'ai, tout d'abord, effectué une revue de la littérature, afin d'en extraire les principaux facteurs de conception de techniques d'interaction dédiées à la transmission non visuelle d'information. Puis, j'ai organisé ces facteurs sous la forme d'un cadre d'analyse, sur lequel je me suis appuyé pour concevoir chacune de mes techniques. Trois expériences distinctes ont permis d'évaluer l'influence de facteurs de conception sur l'efficacité des interactions et la satisfaction des utilisateurs vis-à-vis des techniques. Je peux, notamment, citer l'implication des utilisateurs (actif ou passif), la présence d'aides explicites", la transmission de plusieurs informations en parallèle et la modalité principale utilisée et, le type de codage dans lequel est encodée l'information. / In situations where the visual perception is strongly constraint or deficient, it is necessary to make perceptible the information with a "not visual form" while taking into account human sensory and mnesic capacities. For example, a blind person wishing to acquaint an itinerary must read it under a non visual form and memorize it. However, besides the material aspect, the implementation of alternatives (non-visual) still faces to the cognitive abilities of the user (comprehension, memorization, integration of various information, etc.). The purpose of this thesis is to contribute to the design of interaction techniques allowing to optimize the transmission not visual of the information. For these purposes, I explored the feature of multimodality as a means of optimization, allowing of exceeding the memorization limits. I focused on the study of interaction techniques based on auditory and tactile modalities and by minimizing the use of the speech, in order to develop techniques for different environments (flexibility), optimize the use of perceptual channels (operating the properties of sound in audio messages to transmit more information, for example), avoid limiting my techniques by the language barrier or understanding and finally, to explore alternatives to the synthesised voice alone. The works of my thesis led to the design, to the implementation and to the evaluation of interaction techniques "non-visual" and "multiform", in answer to different contexts, whom in particular those of the information transmission of type <value>, <position> (pair of coordinates) and <itinerary> (sequence of couples direction-distance). To achieve design my interactions, I have made a review of literature in order to extract the main factors of design of interaction techniques dedicated to the transmission not visual of the information. Then, I have organized these factors in an analytical framework on which I have relied to design each of my techniques. Three separate experiments were led to evaluate the influence of design factors on the effectiveness of interactions and satisfaction towards users of technology. I can give some of them, the involvement of users (active or passive), the presence of explicit help, the transmission of several information in parallel, the main modality used and the type of coding in which is encoded the information.

Ensemble simulation is a commonly used technique in operational forecasting of weather and floods. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists and hydrologists are interested in understanding the uncertainties associated with the simulation; specifically variability between the ensemble members. The visualization of ensemble members is currently accomplished through spaghetti plots or hydrographs. To improve visualization techniques and tools for forecasters, we conducted a userstudy to evaluate the effectiveness of existing uncertainty visualization techniques on 1D and 2D synthetic datasets. We designed an uncertainty evaluation framework to enable easier design of such studies for scientific visualization. The techniques evaluated are errorbars, scaled size of glyphs, color-mapping on glyphs, and color-mapping of uncertainty on the data surface. Although we did not find a consistent order among the four techniques for all tasks, we found that the efficiency of techniques used highly depended on the tasks being performed. Errorbars consistently underperformed throughout the experiment. Scaling the size of glyphs and color-mapping of the surface performed reasonably well. With results from the user-study, we iteratively developed a tool named ‘Noodles’ to interactively explore the ensemble uncertainty in weather simulations. Uncertainty was quantified using standard deviation, inter-quartile range, width of the 95% confidence interval, and by bootstrapping the data. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers and avoiding the parametrizations leading to these outliers. Additionally, they could identify spatial regions with high uncertainty thereby determining poorly simulated storm environments and deriving physical interpretation of these model issues. We also describe uncertainty visualization capabilities developed for a tool named ‘FloodViz’ for visualization and analysis of flood simulation ensembles. Simple member and trend plots and composited inundation maps with uncertainty are described along with different types of glyph based uncertainty representations. We also provide feedback from a hydrologist using various features of the tool from an operational perspective.

Climate analysts use Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations to make sense of models performance in predicting extreme events such as heavy precipitation. Similarly, weather analysts use numerical weather prediction models (NWP) to simulate weather conditions either by perturbing initial conditions or by changing multiple input parameterization schemes, e.g., cumulus and microphysics schemes. These simulations are used in operational weather forecasting and for studying the role of parameterization schemes in synoptic weather events like storms. This work addresses the need for visualizing the differences in both CMIP5 and NWP model output. This work proposes three glyph designs used for communicating CMIP5 model error. It also describes Ensemble Visual eXplorer tool that provides multiple ways of visualizing NWP model output and the related input parameter space. The proposed interactive dendrogram provides an effective way to relate multiple input parameterization schemes with spatial characteristics of model uncertainty features. The glyphs that were designed to communicate CMIP5 model error are extended to encode both parameterization schemes and graduated uncertainty, to provide related insights at specific locations such as storm center and the areas surrounding it. The work analyzes different ways of using glyphs to represent parametric uncertainty using visual variables such as color and size, in conjunction with Gestalt visual properties. It demonstrates the use of visual analytics in resolving some of the issues such as visual scalability. As part of this dissertation, we evaluated three glyph designs using average precipitation rate predicted by CMIP5 simulations, and Ensemble Visual eXplorer tool using WRF 1999 March 4th, North American storm track dataset.

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets.