In today's highly competitive industries, engineers are driven to not only design a better product to fulfill users' needs but also demanded to develop a product in a short time to occupy the market. With the development of data collection and visualization technology, the application of data visualization into product development to enhance the ability of better product design is a significant trend.  Data visualization becomes more and more important since it could illustrate the valuable information, such as tacit needs and patterns which hidden from data, in a communicated way to help engineers get more inspiration for the conceptual design.   It is not hard to collect data; however, the challenge is to visualize the valuable information from a large number of data concisely and intuitively. In recent years, there are some visualization techniques available for product design, while, most of them are implemented in the later stage of product development, few methods are applicable for conceptual design. Therefore, this thesis is carried out to explore appropriate visualization techniques to provide support for conceptual design.   The aim of this thesis is, in an engineering environment, to investigate ways to visualize complex data legibly and intuitively to enhance engineers’ ability for conceptual design from better understanding the current machine. In order to achieve the objective, a conceptual design case of the improvement of wheel loader fuel consumption is applied, which consisted of plenty of data sets within various parameters, to explore how to reveal the hidden information of complex data for engineers.   As the result of this thesis, a prototype contains a series of visualization techniques is proposed to demonstrate data information from a wheel loader under several visualization situations. The final prototype has the functions of visualizing different operations separately; visualizing the overall fuel consumption in one operation; cluster's patterns visualization; visualizing the impact of one variable on the whole value.

La neuroimagerie est confrontée à des difficultés pour analyser et réutiliser la masse croissante de données hétérogènes qu’elle produit. La provenance des données est complexe – multi-sujets, multi-analyses, multi-temporalités – et ces données ne sont stockées que partiellement, limitant les possibilités d’études multimodales et longitudinales. En particulier, la connectivité fonctionnelle cérébrale est analysée pour comprendre comment les différentes zones du cerveau travaillent ensemble. Il est nécessaire de gérer les données acquises et traitées suivant plusieurs dimensions, telles que le temps d’acquisition, le temps entre les acquisitions ou encore les sujets et leurs caractéristiques. Cette thèse a pour objectif de permettre l’exploration de relations complexes entre données hétérogènes, ce qui se décline selon deux axes : (1) comment gérer les données et leur provenance, (2) comment visualiser les structures de données multidimensionnelles. L’apport de nos travaux s’articule autour de trois propositions qui sont présentées à l’issue d’un état de l’art sur les domaines de la gestion de données hétérogènes et de la visualisation de graphes. Le modèle de données BMI-LM (Bio-Medical Imaging – Lifecycle Management) structure la gestion des données de neuroimagerie en fonction des étapes d’une étude et prend en compte le caractère évolutif de la recherche grâce à l’association de classes spécifiques à des objets génériques. L’implémentation de ce modèle au sein d’un système PLM (Product Lifecycle Management) montre que les concepts développés depuis vingt ans par l’industrie manufacturière peuvent être réutilisés pour la gestion des données en neuroimagerie. Les GMD (Graphes Multidimensionnels Dynamiques) sont introduits pour représenter des relations complexes entre données qui évoluent suivant plusieurs dimensions, et le format JGEX (Json Graph EXchange) a été créé pour permettre le stockage et l’échange de GMD entre applications. La méthode OCL (Overview Constraint Layout) permet l’exploration visuelle et interactive de GMD. Elle repose sur la préservation partielle de la carte mentale de l’utilisateur et l’alternance de vues complètes et réduites des données. La méthode OCL est appliquée à l’étude de la connectivité fonctionnelle cérébrale au repos de 231 sujets représentées sous forme de GMD – les zones du cerveau sont représentées par les nœuds et les mesures de connectivité par les arêtes – en fonction de l’âge, du genre et de la latéralité : les GMD sont obtenus par l’application de chaînes de traitement sur des acquisitions IRM dans le système PLM. Les résultats montrent deux intérêts principaux à l’utilisation de la méthode OCL : (1) l’identification des tendances globales sur une ou plusieurs dimensions et (2) la mise en exergue des changements locaux entre états du GMD. / Neuroimaging domain is confronted with issues in analyzing and reusing the growing amount of heterogeneous data produced. Data provenance is complex – multi-subjects, multi-methods, multi-temporalities – and the data are only partially stored, restricting multimodal and longitudinal studies. Especially, functional brain connectivity is studied to understand how areas of the brain work together. Raw and derived imaging data must be properly managed according to several dimensions, such as acquisition time, time between two acquisitions or subjects and their characteristics. The objective of the thesis is to allow exploration of complex relationships between heterogeneous data, which is resolved in two parts : (1) how to manage data and provenance, (2) how to visualize structures of multidimensional data. The contribution follow a logical sequence of three propositions which are presented after a research survey in heterogeneous data management and graph visualization. The BMI-LM (Bio-Medical Imaging – Lifecycle Management) data model organizes the management of neuroimaging data according to the phases of a study and takes into account the scalability of research thanks to specific classes associated to generic objects. The application of this model into a PLM (Product Lifecycle Management) system shows that concepts developed twenty years ago for manufacturing industry can be reused to manage neuroimaging data. GMDs (Dynamic Multidimensional Graphs) are introduced to represent complex dynamic relationships of data, as well as JGEX (Json Graph EXchange) format that was created to store and exchange GMDs between software applications. OCL (Overview Constraint Layout) method allows interactive and visual exploration of GMDs. It is based on user’s mental map preservation and alternating of complete and reduced views of data. OCL method is applied to the study of functional brain connectivity at rest of 231 subjects that are represented by a GMD – the areas of the brain are the nodes and connectivity measures the edges – according to age, gender and laterality : GMDs are computed through processing workflow on MRI acquisitions into the PLM system. Results show two main benefits of using OCL method : (1) identification of global trends on one or many dimensions, and (2) highlights of local changes between GMD states.

This dissertation is focused on proposal for simplified data analyze approach for sport-car vehicle dynamic evaluation with relationship to possibility for qualified estimation of set-up parameters influence for overall vehicle performance. In common practice can be usual overlapping effect caused by concurrent changes of car setup elements if performed in the same moment with resulting in not correct or hardly definable process determination for evaluation and decision about next steps in car development. For analyze of these multidimensional data is then chosen process with approach by Linear Regression Model (LRM). In dissertation is proposed basic philosophy with concern on specificity of car vehicle dynamics, performed experiment with defined inputs including analyze and interpretation method of obtained outputs. This methodic take into account also possibility for general application of multidimensional data analyses not only in motorsport, but as well for dynamic behavior diagnostics of technical systems where finding of optimal running condition depends on multi-parametric setup whose combination must reflect often changes of outer conditions too.

在全球化趨勢與Internet帶動速度競爭的影響下，現今的企業經常採取將旗下部門分散佈署於各地，或者和位於不同地區的公司進行合併結盟的策略，藉以提昇其競爭力與市場反應能力。由於地理位置分散的結果，這類企業當中通常存在著許多不同的資料倉儲系統；為了充分支援管理決策的需求，這些不同的資料倉儲當中的資料必須能夠進行交換與整合，因此需要有一套開放且獨立的資料交換標準，俾能經由Internet在不同的資料倉儲間交換多維度資料。然而目前所知的跨資料倉儲之資料交換解決方案多侷限於逐列資料轉換或是以純文字檔案格式進行資料轉移的方式，這些方式除缺乏效率外亦不夠系統化。在本篇研究中，將探討多維度資料交換的議題，並發展一個以XML為基礎的多維度資料交換模式。本研究並提出一個基於學名結構的方法，以此方法發展一套單一的標準交換格式，並促成分散各地的資料倉儲間形成多對多的系統化映對模式。以本研究所發展之多維度資料模式與XML資料模式間的轉換模式為基礎，並輔以本研究所提出之多維度中介資料管理功能，可形成在網路上通用且以XML為基礎的多維度資料交換過程，並能兼顧效率與品質。本研究並開發一套雛型系統，以XML為基礎來實作多維度資料交換，藉資證明此多維度資料交換模式之可行性，並顯示經由中介資料之輔助可促使多維度資料交換過程更加系統化且更富效率。 / Motivated by the globalization trend and Internet speed competition, enterprise nowadays often divides into many departments or organizations or even merges with other companies that located in different regions to bring up the competency and reaction ability. As a result, there are a number of data warehouse systems in a geographically-distributed enterprise. To meet the distributed decision-making requirements, the data in different data warehouses is addressed to enable data exchange and integration. Therefore, an open, vendor-independent, and efficient data exchange standard to transfer data between data warehouses over the Internet is an important issue. However, current solutions for cross-warehouse data exchange employ only approaches either based on records or transferring plain-text files, which are neither adequate nor efficient. In this research, issues on multidimensional data exchange are studied and an XML-based Multidimensional Data Exchange Model is developed. In addition, a generic-construct-based approach is proposed to enable many-to-many systematic mapping between distributed data warehouses, introducing a consistent and unique standard exchange format. Based on the transformation model we develop between multidimensional data model and XML data model, and enhanced by the multidimensional metadata management function proposed in this research, a general-purpose XML-based multidimensional data exchange process over web is facilitated efficiently and improved in quality. Moreover, we develop an XML-based prototype system to exchange multidimensional data, which shows that the proposed multidimensional data exchange model is feasible, and the multidimensional data exchange process is more systematic and efficient using metadata.

Aquesta tesi està dedicada al disseny i a l'anàlisi d'estructures de dades multidimensionals, és a dir, estructures de dades que serveixen per emmagatzemar registres $K$-dimensionals que solen representar-se com a punts en l'espai $[0,1]^K$. Aquestes estructures tenen aplicacions en diverses àrees de la informàtica com poden ser els sistemes d'informació geogràfica, la robòtica, el processament d'imatges, la world wide web, el data mining, entre d'altres. Les estructures de dades multidimensionals també es poden utilitzar com a indexos d'estructures de dades que emmagatzemen, possiblement en memòria externa, dades més complexes que els punts.Les estructures de dades multidimensionals han d'oferir la possibilitat de realitzar operacions d'inserció i esborrat de claus dinàmicament, a més de permetre realitzar cerques anomenades associatives. Exemples d'aquest tipus de cerques són les cerques per rangs ortogonals (quins punts cauen dintre d'un hiper-rectangle donat?) i les cerques del veí més proper (quin és el punt més proper a un punt donat?).Podem dividir les contribucions d'aquesta tesi en dues parts: La primera part està relacionada amb el disseny d'estructures de dades per a punts multidimensionals. Inclou el disseny d'arbres binaris $K$-dimensionals al·leatoritzats (Randomized $K$-d trees), el d'arbres quaternaris al·leatoritzats (Randomized quad trees) i el d'arbres multidimensionals amb punters de referència (Fingered multidimensional trees).La segona part analitza el comportament de les estructures de dades multidimensionals. En particular, s'analitza el cost mitjà de les cerques parcials en arbres $K$-dimensionals relaxats, i el de les cerques per rang en diverses estructures de dades multidimensionals. Respecte al disseny d'estructures de dades multidimensionals, proposem algorismes al·leatoritzats d'inserció i esborrat de registres per als arbres $K$-dimensionals i per als arbres quaternaris. Aquests algorismes produeixen arbres aleatoris, independentment de l'ordre d'inserció dels registres i desprès de qualsevol seqüència d'insercions i esborrats. De fet, el comportament esperat de les estructures produïdes mitjançant els algorismes al·leatoritzats és independent de la distribució de les dades d'entrada, tot i conservant la simplicitat i la flexibilitat dels arbres $K$-dimensionals i quaternaris estàndard. Introduïm també els arbres multidimensionals amb punters de referència. Això permet que les estructures multidimensionals puguin aprofitar l'anomenada localitat de referència en cerques associatives altament correlacionades.I respecte de l'anàlisi d'estructures de dades multidimensionals, primer analitzem el cost esperat de las cerques parcials en els arbres $K$-dimensionals relaxats. Seguidament utilitzem aquest resultat com a base per a l'anàlisi de les cerques per rangs ortogonals, juntament amb arguments combinatoris i geomètrics. D'aquesta manera obtenim un estimat asimptòtic precís del cost de les cerques per rangs ortogonals en els arbres $K$-dimensionals aleatoris. Finalment, mostrem que les tècniques utilitzades es poden estendre fàcilment a d'altres estructures de dades i per tant proporcionem una anàlisi exacta del cost mitjà de cerques per rang en estructures de dades com són els arbres $K$-dimensionals estàndard, els arbres quaternaris, els tries quaternaris i els tries $K$-dimensionals. / Esta tesis está dedicada al diseño y al análisis de estructuras de datos multidimensionales; es decir, estructuras de datos específicas para almacenar registros $K$-dimensionales que suelen representarse como puntos en el espacio $[0,1]^K$. Estas estructuras de datos tienen aplicaciones en diversas áreas de la informática como son: los sistemas de información geográfica, la robótica, el procesamiento de imágenes, la world wide web o data mining, entre otras.Las estructuras de datos multidimensionales suelen utilizarse también como índices de estructuras que almacenan, posiblemente en memoria externa, datos complejos.Las estructuras de datos multidimensionales deben ofrecer la posibilidad de realizar operaciones de inserción y borrado de llaves de manera dinámica, pero además deben permitir realizar búsquedas asociativas en los registros almacenados. Ejemplos de búsquedas asociativas son las búsquedas por rangos ortogonales (¿qué puntos de la estructura de datos están dentro de un hiper-rectángulo dado?) y las búsquedas del vecino más cercano (¿cuál es el punto de la estructura de datos más cercano a un punto dado?).Las contribuciones de esta tesis se dividen en dos partes:La primera parte está dedicada al diseño de estructuras de datos para puntos multidimensionales, que incluye el diseño de los árboles binarios $K$-dimensionales aleatorios (Randomized $K$-d trees), el de los árboles cuaternarios aleatorios (Randomized quad trees), y el de los árboles multidimensionales con punteros de referencia (Fingered multidimensional trees).La segunda parte contiene contribuciones al análisis del comportamiento de las estructuras de datos para puntos multidimensionales. En particular, damos el análisis del costo promedio de las búsquedas parciales en los árboles $K$-dimensionales relajados y el de las búsquedas por rango en varias estructuras de datos multidimensionales.Con respecto al diseño de estructuras de datos multidimensionales, proponemos algoritmos aleatorios de inserción y borrado de registros para los árboles $K$-dimensionales y los árboles cuaternarios que producen árboles aleatorios independientemente del orden de inserción de los registros y después de cualquier secuencia de inserciones y borrados intercalados. De hecho, con la aleatorización garantizamos un buen rendimiento esperado de las estructuras de datos resultantes, que es independiente de la distribución de los datos de entrada, conservando la flexibilidad y la simplicidad de los árboles $K$-dimensionales y de los árboles cuaternarios estándar. También proponemos los árboles multidimensionales con punteros de referencia, una técnica que permite que las estructuras de datos multidimensionales exploten la localidad de referencia en búsquedas asociativas que se presentan altamente correlacionadas.Con respecto al análisis de estructuras de datos multidimensionales, comenzamos dando un análisis preciso del costo esperado de las búsquedas parciales en los árboles $K$-dimensionales relajados. A continuación, utilizamos este resultado como base para el análisis de las búsquedas por rangos ortogonales, combinándolo con argumentos combinatorios y geométricos. Como resultado obtenemos un estimado asintótico preciso del costo de las búsquedas por rango en los árboles $K$-dimensionales relajados. Finalmente, mostramos que las técnicas utilizadas pueden extenderse fácilmente a otras estructuras de datos y por tanto proporcionamos un análisis preciso del costo promedio de búsquedas por rango en estructuras de datos como los árboles $K$-dimensionales estándar, los árboles cuaternarios, los tries cuaternarios y los tries $K$-dimensionales. / This thesis is about the design and analysis of point multidimensional data structures: data structures that store $K$-dimensional keys which we may abstract as points in $[0,1]^K$. These data structures are present in many applications of geographical information systems, image processing or robotics, among others. They are also frequently used as indexes of more complex data structures, possibly stored in external memory.Point multidimensional data structures must have capabilities such as insertion, deletion and (exact) search of items, but in addition they must support the so called {em associative queries}. Examples of these queries are orthogonal range queries (which are the items that fall inside a given hyper-rectangle?) and nearest neighbour queries (which is the closest item to some given point?).The contributions of this thesis are two-fold:Contributions to the design of point multidimensional data structures: the design of randomized $K$-d trees, the design of randomized quad trees and the design of fingered multidimensional search trees;Contributions to the analysis of the performance of point multidimensional data structures: the average-case analysis of partial match queries in relaxed $K$-d trees and the average-case analysis of orthogonal range queries in various multidimensional data structures.Concerning the design of randomized point multidimensional data structures, we propose randomized insertion and deletion algorithms for $K$-d trees and quad trees that produce random $K$-d trees and quad trees independently of the order in which items are inserted into them and after any sequence of interleaved insertions and deletions. The use of randomization provides expected performance guarantees, irrespective of any assumption on the data distribution, while retaining the simplicity and flexibility of standard $K$-d trees and quad trees.Also related to the design of point multidimensional data structures is the proposal of fingered multidimensional search trees, a new technique that enhances point multidimensional data structures to exploit locality of reference in associative queries.With regards to performance analysis, we start by giving a precise analysis of the cost of partial matches in randomized $K$-d trees. We use these results as a building block in our analysis of orthogonal range queries, together with combinatorial and geometric arguments and we provide a tight asymptotic estimate of the cost of orthogonal range search in randomized $K$-d trees. We finally show that the techniques used apply easily to other data structures, so we can provide an analysis of the average cost of orthogonal range search in other data structures such as standard $K$-d trees, quad trees, quad tries, and $K$-d tries.

An integrating approach, including knowledge about whole systems of processes, is essential in order to reach both development and environmental protection goals. In this thesis Geographical Information Systems (GIS) are suggested as a tool to realise such integrated models. The main hypothesis in this work is that several natural technical and social systems that share a time-space can be compared and analysed in a GIS. My first objective was to analyze how GIS can support research, planning, and, more specifically, bring a broad scattering of competence together in an interdisciplinary process. In this process GIS was ivestigated as a tool to achieve models that give us a better overview of a problem, a better understanding for the processes involved, aid in foreseeing conflicts between interests, find ecological limits and assist in choosing countermeasures and monitor the result of different programs. The second objective concerns the requirement that models should be comparable and possible to include in other models and that they can be communicated to planners, politicians and the public. For this reason the possibilities to communicate the result and model components of multidimensional and multi-temporal data are investigated. Four examples on the possibilities and problems when using GIS in interdisciplinary studies are presented. In the examples, water plays a central role as a component in questions about development, management and environmental impact. The first articles focus on non-point source pollutants as a problem under growing attention when the big industrial and municipal point sources are brought under control. To manage non-point source pollutants, detailed knowledge about local conditions is required to facilitate precise advices on land use. To estimate the flow of metals and N(itrogen) in an area it is important to identify the soil moisture. Soil moisture changes over time but also significantly in the landscape according to several factors. Here a method is presented that calculate soil moisture over large areas. Man as a hydrologie factor has to be assessed to also understand the relative importance of anthropogen processes. To offer a supplement to direct measurements and add anthropogen factors, a GIS model is presented that takes soil-type, topography, vegetation, land-use, agricultural drainage and relative position in the watershed into account. A method to analyse and visualise development over time and space in the same model is presented in the last empirical study. The development of agricultural drainage can be discussed as a product of several forces here analyzed together and visualized with help of colour coded "Hyper pixels" and maps. Finally a discussion concerning the physiological and psychological possibilities to communicate multidimensional phenomena with the help of pictures and maps is held. The main conclusions in this theses are that GIS offer the possibilities to develop distributed models, e.g., models that calculate effects from a vide range of factors in larger areas and with a much higher spatial resolution than has been possible earlier. GIS also offer a possibility to integrate and communicate information from different disciplines to scientists, decision makers and the public. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1993, härtill 6 uppsatser.</p> / digitalisering@umu

Lors de l’exploration d’espace de conception, les données résultantes de la simulation d’un grand nombre d’alternatives de conception peuvent conduire à la surcharge d’information quand il s’agit de choisir une bonne solution de conception. Cette exploration d’espace de conception s’apparente à une méthode d’optimisation en conception multicritère mais en mode manuel pour lequel des outils appropriés à la visualisation de données multidimensionnelle sont employés. Pour le concepteur, un processus en trois phases – découverte, optimisation, sélection – est suivi selon un paradigme dit de Design by Shopping. Le fait de « parcourir » l’espace de conception permet de gagner en intuition sur les sous-espaces de solutions faisables et infaisables et sur les solutions offrant de bons compromis. Le concepteur apprend au cours de ces manipulations graphiques de données. La sélection d’une solution optimale se fait donc sur la base d’une décision dite informée. L’objectif de cette recherche est la performance des représentations graphiques pour l’exploration d’espace de conception, pour les trois phases du processus en Design by Shopping. Pour cela, cinq représentations graphiques, identifiées comme potentiellement performantes, sont testées à travers deux expérimentations. Dans la première, trente participants ont testé trois graphiques, pour la phase de sélection dans une situation multi-attribut, à travers trois scénarios de conception où une voiture doit être choisie parmi quarante selon des préférences énoncées. Pour cela, un indice de qualité est proposé pour calculer la qualité de la solution du concepteur pour un des trois scénarios définis, la solution optimale selon cet indice étant comparée à celles obtenues après manipulation des graphiques. Dans la deuxième expérimentation, quarante-deux concepteurs novices ont résolu deux problèmes de conception à l’aide de trois graphiques. Dans ce cas, la performance des graphiques est testée pour la prise de décision informée et pour les trois phases du processus dans une situation multi-objectif. Les résultats révèlent qu’un graphique est adapté à chacune des trois phases du Design by Shopping :: le graphique Scatter Plot Matrix pour la phase de découverte et pour la prise de décision informée, le graphique Simple Scatter pour la phase d’optimisation et le graphique Parallel Coordinate Plot pour la phase de sélection aussi bien dans une situation multi-attribut que multi-objectif. / In Design space exploration, the resulting data, from simulation of large amount of new design alternatives, can lead to information overload when one good design solution must be chosen. The design space exploration relates to a multi-criteria optimization method in design but in manual mode, for which appropriate tools to support multi-dimensional data visualization are employed. For the designer, a three-phase process - discovery, optimization, selection - is followed according to a paradigm called Design by Shopping. Exploring the design space helps to gain insight into both feasible and infeasible solutions subspaces, and into solutions presenting good trade-offs. Designers learn during these graphical data manipulations and the selection of an optimal solution is based on a so-called informed decision. The objective of this research is the performance of graphs for design space exploration according to the three phases of the Design by Shopping process. In consequence, five graphs, identified as potentially efficient, are tested through two experiments. In the first, thirty participants tested three graphs, in three design scenarios where one car must be chosen out of a total of forty, for the selection phase in a multi-attribute situation where preferences are enounced. A response quality index is proposed to compute the choice quality for each of the three given scenarios, the optimal solutions being compared to the ones resulting from the graphical manipulations. In the second experiment, forty-two novice designers solved two design problems with three graphs. In this case, the performance of graphs is tested for informed decision-making and for the three phases of the process in a multi-objective situation. The results reveal three efficient graphs for the design space exploration: the Scatter Plot Matrix for the discovery phase and for informed decision-making, the Simple Scatter Plot for the optimization phase and the Parallel Coordinate Plot for the selection phase in a multi-attribute as well as multi-objective situation.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Entre as mudanÃas globais enfrentadas nas pouco mais de trÃs Ãltimas dÃcadas, destacam-se as maneiras como a informaÃÃo, no espaÃo digital e na Web, à acessada, inter-relacionada e ressignificada, no aspecto da construÃÃo de novos conhecimentos e saberes. Estas mudanÃas estÃo significativamente vinculadas à quebra de paradigmas e crises entre as Ãreas de conhecimento. Neste cenÃrio, a sociedade enfrenta uma inesperada corrida de rÃpidas transformaÃÃes, fusÃes e nascimento de novas Ãreas de conhecimento interdisciplinares, carreando o processo educacional para uma contÃnua e desafiante crise. Progressivamente, o uso pedagÃgico das TIC ocupa os espaÃos da outrora educaÃÃo conservadora presencial e instrucionista, outorgando cenÃrios favorecedores à integraÃÃo pedagÃgica entre: as mÃdias, o construtivismo, a autonomia, a criatividade e o aprender juntos. Nas prÃximas dÃcadas, decorrerÃo mudanÃas significativas nas propostas de avaliaÃÃo, notadamente voltadas para o desenvolvimento da aprendizagem colaborativa, em espaÃos assÃncronos, o que suscita profundas reflexÃes, concernentes Ãs transposiÃÃes teÃrico-metodolÃgicas e prÃticas, que incidirÃo sobre a ressignificaÃÃo e relaÃÃes entre o desenvolvimento da aprendizagem e sua avaliaÃÃo. A presente investigaÃÃo, de carÃter qualitativo e de pesquisa-aÃÃo, se insere no cenÃrio do desenvolvimento de atividades pedagÃgicas colaborativas, expressas por narrativas, postadas em FÃruns de discussÃo, durante o transcurso de uma disciplina de InformÃtica na EducaÃÃo, ofertada presencialmente pelo Departamento de Fundamentos da EducaÃÃo da FACED/UFC, em que majoritariamente participaram estudantes de graduaÃÃo. A proposta didÃtica da disciplina se baseia nos pressupostos da teoria da aprendizagem significativa ausubeliana, no mapeamento cognitivo, na visÃo de Okada, e no estar junto virtual, segundo Valente e Almeida. Foram escolhidos dois de seus FÃruns temÃticos disciplinares, que abordavam as temÃticas de estudo: o uso pedagÃgico de mapas conceituais e pressupostos da avaliaÃÃo formativa da aprendizagem, numa visÃo construtivista (AUSUBEL, FERNANDES, MASETTO, PERRONOUD, ZABALA). Parte do referencial teÃrico da Tese permeia a avaliaÃÃo na forma clÃssica e contribuiÃÃes nÃo clÃssicas, que apontam para a necessidade de se repensar a avaliaÃÃo, numa Ãtica do construtivismo e da aprendizagem assÃncrona. Os conjuntos de narrativas, postados pelos estudantes, sÃo constituÃdos por dados multidimensionais fortemente entrelaÃados, que foram mapeados e analisados, sob a forma de categorias, à luz do referencial teÃrico e objetivos adotados na Tese, sob o foco da anÃlise textual discursiva (MORAES, GALIAZZI) e da anÃlise qualitativa de dados multidimensionais, fazendo-se o uso do software CHIC (ALMOULOUD, PRADO, VALENTE). Em seguida, partindo-se de uma Ãrvore de similaridade, gerada pelo CHIC, foram estabelecidas inter-relaÃÃes hierÃrquicas e relacionais, entre as categorias, organizadas em trÃs eixos temÃticos, e as narrativas dos cursistas, de modo a analisar, numa Ãtica do referencial teÃrico da Tese, como se desenvolve a aprendizagem e como a avaliaÃÃo, qualitativa e formativa, pode estar associada ao desenvolvimento da aprendizagem. Da anÃlise multidimensional das narrativas dos cursistas, numa Ãtica transdisciplinar, emergiram indÃcios preliminares de inter-relaÃÃes hierÃrquicas e relacionais, entre os trÃs campos de conhecimentos desenvolvimento da aprendizagem, avaliaÃÃo e saberes pedagÃgicos e tecnolÃgicos, e as aÃÃes pedagÃgicas vivenciadas nos FÃruns TelEduc, que questionam se repensar os pressupostos da avaliaÃÃo da aprendizagem e a convergÃncia dos futuros caminhos das prÃticas pedagÃgicas e avaliativas. / Among the global challenges, FACED during the last three decades, it is important to point out the different ways how the information, in the digital space and on the Web, is accessed, interrelated, in order to give a new meaning, according the aspect of building new knowledges. These changes are meaningful linked to paradigms break and crises between the areas of knowledge. In this scenario, the human society faces an unexpected rush of rapid transformations, mergers and birth of new areas of interdisciplinary knowledge, leading the educational process for continuous and challenging crisis. Progressively, the pedagogical use of ICT occupies the space of the once classroom and instructional conservative education, favoring granting scenarios to the pedagogical integration of: media, constructivism, autonomy, creativity and learning together. In the coming decades, it will take significant changes in the proposal evaluation, notably focused on the development of collaborative learning in asynchronous spaces, which raises profound reflections, concerning the theoretical and methodological and practice transpositions, which will focus on redefining and relationships between learning development and its assessment. This research, that is qualitative and action research, is included in the scenario of the development of collaborative educational activities, expressed by narratives, posted in the TelEduc discussion Forums, during the development of activities on a course of informatics in Education, offered by the Department of Education Foundations of FACED/UFC, where mostly attended graduate students. The didactic proposal of the course is based on the assumptions of the theory of Ausubel&#8223;s meaningful learning, cognitive mapping, in Okada's vision, and on the learning together in the virtual space, according to Valente and Almeida. Two of his disciplinary thematic forums were chosen which addressed the topics of study: the educational use of concept maps and assumptions of formative assessment of learning, according the constructivist view (AUSUBEL; FERNANDES; MASETTO; PERRENOUD; ZABALA). Part of the Thesis theoretical framework permeates the assessment in a classical view and non-classical contributions, what point out to the need to rethink the assessment in a perspective of constructivism and asynchronous learning. The sets of narratives, posted by students, are made up of multidimensional data strongly intertwined, which were mapped and analyzed in the form of categories. This is done based on the theoretical framework and objectives adopted in this Thesis, from the perspective of the discursive textual analysis (MORAES; GALIAZZI) and the multi-dimensional analysis for qualitative data, making the use of software CHIC (ALMEIDA; ALMOULOUD; VALENTE). Then, starting from a similarity tree, generated by CHIC, hierarchical and relational interrelationships have been established between the categories, organized into three themes, and the narratives of the course participants. This is done in order to analyze, in a perspective of the theoretical framework of the Thesis, how learning can be developed and how the assessment, qualitative and formative, may be associated with the learning development. From the multidimensional analysis of the narratives of the course participants, and according a transdisciplinary perspective, it was emerged preliminary evidence of hierarchical and relational interrelationships, between the knowledge fields learning development, assessment and technological pedagogical content knowledge, and the collaborative pedagogical actions, experienced in the TelEduc Forums, that induce to rethink the assumptions of the assessment of learning and the future possibles ways of the pedagogical and assessment practices.

Des données complexes sont fréquentes dans les essais cliniques récents et nécessitent des méthodes statistiques adaptées. La recherche vaccinale du VIH est un exemple d’un domaine avec des données complexes et une absence de critères de jugement validés dans les essais précoces. Cette thèse d’Université concerne des recherches méthodologiques sur la conception et les aspects statistiques des essais cliniques vaccinaux du VIH, en particulier sur les critères de jugement d’immunogénicité et les schémas d’essai de phase I-II. A l’aide des données cytokiniques multiplex, nous illustrons les aspects méthodologiques spécifiques à une technique de mesure. Nous proposons ensuite des définitions de critères de jugement et des méthodes statistiques adéquates pour l'analyse des données d'immunogénicité multidimensionnelles. En particulier, nous montrons l’intérêt des scores multivariés non-paramétriques, permettant de résumer l’information à travers différents marqueurs d’immunogénicité et de faire des comparaisons inter- et intra-groupe. Dans l’objectif de contribuer à la conception méthodologique des nouveaux essais vaccinaux, nous présentons la construction d’un schéma d’essai optimisé pour le développement clinique précoce. En imbriquant les phases I et II d’évaluation clinique, ce schéma permet d’accélerer le développement de plusieurs stratégies vaccinales en parallèle. L’intégration d’une règle d’arrêt est proposée dans des perspectives fréquentistes et Bayesiennes. Les méthodes mises en avant dans cette thèse sont transposables à d’autres domaines d’application avec des données complexes, telle que les données d’imagerie ou les essais d’autres immunothérapies. / Complex data are frequently recored in recent clinical trials and require the use of appropriate statistical methods. HIV vaccine research is an example of a domaine with complex data and a lack of validated endpoints for early-stage clinical trials. This thesis concerns methodological research with regards to the design and analysis aspects of HIV vaccine trials, in particular the definition of immunogenicity endpoints and phase I-II trial designs. Using cytokine multiplex data, we illustrate the methodological aspects specific to a given assay technique. We then propose endpoint definitions and statistical methods appropriate for the analysis of multidimensional immunogenicity data. We show in particular the value of non-parametric multivariate scores, which allow for summarizing information across different immunogenicity markers and for making statistical comparisons between and within groups. In the aim of contributing to the design of new vaccine trials, we present the construction of an optimized early-stage HIV vaccine design. Combining phase I and II assessments, the proposed design allows for accelerating the clinical development of several vaccine strategies in parallel. The integration of a stopping rule is proposed from both a frequentist and a Bayesian perspective. The methods advocated in this thesis are transposable to other research domains with complex data, such as imaging data or trials of other immune therapies.

Les processus biologiques sont nombreux et leurs interactions complexes. Les mesures de cesphénomènes génèrent des biomarqueurs multiples. Ainsi, l’épidémiologie doit évoluer dans cecontexte de données complexes et de nature multidimensionnelle. Les maladies du systèmeimmunitaire et les troubles immunologiques qui leur sont associés constituent un bon exemplede pathologies où les questions clinico-épidémiologiques sont de plus en plus complexes,nécessitant des méthodes biostatistiques et épidémiologiques adaptées. Dans cette thèsed’Université, des méthodes permettant de prendre en compte les difficultés méthodologiquesgénérées par les données d’immunologie sont présentées autour de trois applicationscliniques. Notre approche consiste en l’utilisation de méthodes intégratives qui prennent encompte l’ensemble des mesures concernant une pathologie donnée. Nous montrons l’intérêtde l’analyse en composantes principales et de la classification hiérarchique ascendante pourrésumer et extraire l’information de données multiples de cytométrie en flux et celui desmodèles d’équations structurelles pour l’étude de relations complexes entre variables lors deprocessus multifactoriels. Enfin, via l’exemple d’un modèle de reconstitution immunitaireasymptotique utilisant une fonction exponentielle, nous illustrons l’importance de s’appuyersur la structure même des données et sur la compréhension des mécanismes biologiques quisous-tendent la variabilité de ces données dans la réflexion qui concourt au choix d’un modèlestatistique. Les méthodes et la réflexion proposées dans cette thèse sont transposables àd’autres domaines d’application avec des données multiples complexes. / Numerous biological processes with potentially complex interactions exist. Measurements ofthese processes allow to produce multiple biomarkers. Thus, there is a need for epidemiologyto evolve within the context of complex and multidimensional data. Immune system diseasesand associated immune disorders are an example of a field where clinical and epidemiologicalissues are increasingly complex, requiring appropriate statistical and epidemiologicalmethods. In this thesis, methods taking into account methodological difficulties generated byimmunology data are presented through three motivating examples. The general paradigm ofour approach is to take into account all measurements on a given pathology using integrativemethods. We propose principal component analysis and hierarchical clustering to summarizemultidimensional cytometry data and structural equation modelling for dealing with complexrelationships between variables in multifactorial processes. Then, through the example of anasymptotic model of immune reconstitution using an exponential function, we illustrate theimportance about the data’s structure and the biological mechanisms underlying its variabilitywhen building a mathematical model. The methods and the thinking advocated in this thesisare transposable to other research domains with complex data.