74 research outputs found
Subjective information visualizations
Information Visualizations (InfoViz) are systems that require high levels of cognitive processing. They
revolve around the notion of decoding and interpreting visual patterns in order to achieve certain
goals. We argue that purely designing for the visual will not allow for optimum experiences since there
is more to InfoViz than just the visual. Interaction is a key to achieving higher levels of knowledge. In
this position paper we present a different perspective on the underlying meaning of interaction, where
we describe it as incorporating both the visual and the physical activities. By physical activities we
mean the physical actions upon the physical input device/s. We argue that interaction is the key
element for supporting users’ subjective experiences hence these experiences should first be
understood. All the discussions in this paper are based upon on going work in the field of visualizing
the literature knowledge domain (LKDViz)
A Task-Centered Visualization Design Environment and a Method for Measuring the Complexity of Visualization Designs
Recent years have seen a growing interest in the emerging area of computer security visualization which is about developing visualization methods to help solve computer security problems. In this thesis, we will first present a method for measuring the complexity of information visualization designs. The complexity is measured in terms of visual integration, number of separable dimensions for each visual unit, the complexity of interpreting the visual attributes, number of visual units, and the efficiency of visual search. This method is designed to better assist fellow developers to quickly evaluate multiple design choices, potentially enables computer to automatically measure the complexity of visualization data. We will also analyze the design space of network security visualization. Our main contribution is a new taxonomy that consists of three dimensions – data, visualizations, and tasks. Each dimension is further divided into hierarchical layers, and for each layer we have identified key parameters for making major design choices. This new taxonomy provides a comprehensive framework that can guide network security visualization developers to systematically explore the design space and make informed design decisions. It can also help developers or users systematically evaluate existing network security visualization techniques and systems. Finally it helps developers identify gaps in the design space and create new techniques. Taxonomy showed that most of the existing computer security visualization programs are data centered. However, some studies have shown that task centered visualization is perhaps more effective. To test this hypothesis, we propose a task centered visualization design framework, in which tasks are explicitly identified and organized and visualizations are constructed for specific tasks and their related data parameters. The center piece of this framework is a task tree which dynamically links the raw data with automatically generated visualization. The task tree serves as a high level interaction technique that allows users to conduct problem solving naturally at the task level, while still giving end users flexible control over the visualization construction. This work is currently being extended by building a prototype visualization system based on a Task-centered Visualization Design Architecture
Visualising multiple overlapping classification hierarchies.
The revision or reorganisation of hierarchical data sets can result in many possible hierarchical classifications composed of the same or overlapping data sets existing in parallel with each other. These data sets are difficult for people to handle and conceptualise, as they tryto reconcile the different perspectives and structures that such data represents. One area where this situation occurs is the study of botanical taxonomy, essentially the classification and naming of plants. Revisions, new discoveries and new dimensions for classifying plants lead to a proliferation of classifications over the same set of plant data. Taxonomists would like a method of exploring these multiple overlapping hierarchies for interesting information, correlations, or anomalies. The application and extension of Information Visualisation (IV) techniques, the graphical display of abstract information, is put forward as a solution to this problem. Displaying the multiple classification hierarchies in a visually appealing manner along with powerful interaction mechanisms for examination and exploration of the data allows taxonomists to unearth previously hidden information. This visualisation gives detail that previous visualisations and statistical overviews cannot offer. This thesis work has extended previous IV work in several respects to achieve this goal. Compact, yet full and unambiguous, hierarchy visualisations have been developed. Linking and brushing techniques have been extended to work on a higher class of structure, namely overlapping trees and hierarchies. Focus and context techniques have been pushed to achieve new effects across the visually distinct representations of these multiple hierarchies. Other data types, such as multidimensional data and large cluster hierarchies have also been displayed using the final version of the visualisation
Graph-level operations: A high-level interface for graph visualization technique specification
More and more the world is being described as graphs---as connections between people, places, and ideas---since they provide a richer model than simply understanding each item in isolation. In order to help analysts understand these graphs, researchers have developed and studied a large number of graph visualization techniques. This variety of techniques presents solutions to a breadth of graph analysis tasks, but it introduces a new issue: complexity. The variety introduces both the complexity of comparing techniques in an objective way and the engineering complexity of implementing so many techniques. In this thesis, I present graph-level operations models (or GLO models) as an elegant solution to these challenges. A GLO model consists of a model of visual elements and a set of functions (GLOs) that manipulate those elements. I introduce GLOv1 and GLOv2, GLO models derived from six hand-picked graph visualization techniques and twenty-nine techniques derived from a review of 430 graph visualization publications, respectively. I show how to use GLOs to define graph visualization techniques, including a model's original seed techniques as well as novel techniques. I demonstrate the analysis potential of the GLO model by clustering the twenty-nine seed techniques using two different GLO-based schemes. Finally, I demonstrate the practical engineering potential of the model through an open-source Javascript implementation (GLO.js) and two applications built atop the implementation for exploring a graph and discovering novel techniques using GLOs (GLO-STIX and GLO-CLI).Ph.D
Adaptive Methods for Color Vision Impaired Users
Color plays a key role in the understanding of the information in computer environments. It
happens that about 5% of the world population is affected by color vision deficiency (CVD),
also called color blindness. This visual impairment hampers the color perception, ending up by
limiting the overall perception that CVD people have about the surrounding environment, no
matter it is real or virtual. In fact, a CVD individual may not distinguish between two different
colors, what often originates confusion or a biased understanding of the reality, including web
environments, whose web pages are plenty of media elements like text, still images, video,
sprites, and so on.
Aware of the difficulties that color-blind people may face in interpreting colored contents,
a significant number of recoloring algorithms have been proposed in the literature with the
purpose of improving the visual perception of those people somehow. However, most of those
algorithms lack a systematic study of subjective assessment, what undermines their validity, not
to say usefulness. Thus, in the sequel of the research work behind this Ph.D. thesis, the central
question that needs to be answered is whether recoloring algorithms are of any usefulness and
help for colorblind people or not.
With this in mind, we conceived a few preliminary recoloring algorithms that were published in
conference proceedings elsewhere. Except the algorithm detailed in Chapter 3, these conference
algorithms are not described in this thesis, though they have been important to engender
those presented here. The first algorithm (Chapter 3) was designed and implemented for people
with dichromacy to improve their color perception. The idea is to project the reddish hues onto
other hues that are perceived more regularly by dichromat people.
The second algorithm (Chapter 4) is also intended for people with dichromacy to improve their
perception of color, but its applicability covers the adaptation of text and image, in HTML5-
compliant web environments. This enhancement of color contrast of text and imaging in web
pages is done while keeping the naturalness of color as much as possible. Also, to the best of our
knowledge, this is the first web recoloring approach targeted to dichromat people that takes
into consideration both text and image recoloring in an integrated manner.
The third algorithm (Chapter 5) primarily focuses on the enhancement of some of the object
contours in still images, instead of recoloring the pixels of the regions bounded by such contours.
Enhancing contours is particularly suited to increase contrast in images, where we find adjacent
regions that are color indistinguishable from dichromat’s point of view. To our best knowledge,
this is one of the first algorithms that take advantage of image analysis and processing techniques
for region contours.
After accurate subjective assessment studies for color-blind people, we concluded that the CVD
adaptation methods are useful in general. Nevertheless, each method is not efficient enough to
adapt all sorts of images, that is, the adequacy of each method depends on the type of image
(photo-images, graphical representations, etc.).
Furthermore, we noted that the experience-based perceptual learning of colorblind people
throughout their lives determines their visual perception. That is, color adaptation algorithms must satisfy requirements such as color naturalness and consistency, to ensure that dichromat
people improve their visual perception without artifacts. On the other hand, CVD adaptation
algorithms should be object-oriented, instead of pixel-oriented (as typically done), to select
judiciously pixels that should be adapted. This perspective opens an opportunity window for
future research in color accessibility in the field of in human-computer interaction (HCI).A cor desempenha um papel fundamental na compreensão da informação em ambientes computacionais.
Porém, cerca de 5% da população mundial é afetada pela deficiência de visão de
cor (ou Color Vision Deficiency (CVD), do Inglês), correntemente designada por daltonismo. Esta
insuficiência visual dificulta a perceção das cores, o que limita a perceção geral que os indivíduos
têm sobre o meio, seja real ou virtual. Efetivamente, um indivíduo com CVD vê como iguais
cores que são diferentes, o que origina confusão ou uma compreensão distorcida da realidade,
assim como dos ambientes web, onde existe uma abundância de conteúdos média coloridos,
como texto, imagens fixas e vídeo, entre outros.
Com o intuito de mitigar as dificuldades que as pessoas com CVD enfrentam na interpretação de
conteúdos coloridos, tem sido proposto na literatura um número significativo de algoritmos de
recoloração, que têm como o objetivo melhorar, de alguma forma, a perceção visual de pessoas
com CVD. Porém, a maioria desses trabalhos carece de um estudo sistemático de avaliação
subjetiva, o que põe em causa a sua validação, se não mesmo a sua utilidade. Assim, a principal
questão à qual se pretende responder, como resultado do trabalho de investigação subjacente
a esta tese de doutoramento, é se os algoritmos de recoloração têm ou não uma real utilidade,
constituindo assim uma ajuda efetiva às pessoas com daltonismo.
Tendo em mente esta questão, concebemos alguns algoritmos de recoloração preliminares que
foram publicados em atas de conferências. Com exceção do algoritmo descrito no Capítulo 3,
esses algoritmos não são descritos nesta tese, não obstante a sua importância na conceção
daqueles descritos nesta dissertação. O primeiro algoritmo (Capítulo 3) foi projetado e implementado
para pessoas com dicromacia, a fim de melhorar a sua perceção da cor. A ideia consiste
em projetar as cores de matiz avermelhada em matizes que são melhor percebidos pelas pessoas
com os tipos de daltonismo em causa.
O segundo algoritmo (Capítulo 4) também se destina a melhorar a perceção da cor por parte de
pessoas com dicromacia, porém a sua aplicabilidade abrange a adaptação de texto e imagem,
em ambientes web compatíveis com HTML5. Isto é conseguido através do realce do contraste
de cores em blocos de texto e em imagens, em páginas da web, mantendo a naturalidade da
cor tanto quanto possível. Além disso, tanto quanto sabemos, esta é a primeira abordagem de
recoloração em ambiente web para pessoas com dicromacia, que trata o texto e a imagem de
forma integrada.
O terceiro algoritmo (Capítulo 5) centra-se principalmente na melhoria de alguns dos contornos
de objetos em imagens, em vez de aplicar a recoloração aos pixels das regiões delimitadas por
esses contornos. Esta abordagem é particularmente adequada para aumentar o contraste em
imagens, quando existem regiões adjacentes que são de cor indistinguível sob a perspetiva dos
observadores com dicromacia. Também neste caso, e tanto quanto é do nosso conhecimento,
este é um dos primeiros algoritmos em que se recorre a técnicas de análise e processamento de
contornos de regiões.
Após rigorosos estudos de avaliação subjetiva com pessoas com daltonismo, concluiu-se que os
métodos de adaptação CVD são úteis em geral. No entanto, cada método não é suficientemente
eficiente para todos os tipo de imagens, isto é, o desempenho de cada método depende do tipo de imagem (fotografias, representações gráficas, etc.).
Além disso, notámos que a aprendizagem perceptual baseada na experiência das pessoas daltónicas
ao longo de suas vidas é determinante para perceber aquilo que vêem. Isto significa que os
algoritmos de adaptação de cor devem satisfazer requisitos tais como a naturalidade e a consistência
da cor, de modo a não pôr em causa aquilo que os destinatários consideram razoável
ver no mundo real. Por outro lado, a abordagem seguida na adaptação CVD deve ser orientada
aos objetos, em vez de ser orientada aos pixéis (como tem sido feito até ao momento), de
forma a possibilitar uma seleção mais criteriosa dos pixéis que deverão ser sujeitos ao processo
de adaptação. Esta perspectiva abre uma janela de oportunidade para futura investigação em
acessibilidade da cor no domínio da interacção humano-computador (HCI)
The state of the art in integrating machine learning into visual analytics
Visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning and data visualization is still under-explored. This state-of-the-art report presents a summary of the progress that has been made by highlighting and synthesizing select research advances. Further, it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions
How to tell stories using visualization: strategies towards narrative visualization
Os benefícios da utilização das narrativas são desde há muito conhecidos e o seu potencial
para simplificar conceitos, transmitir valores culturais e experiências, criar ligações emocionais
e capacidade para ajudar a reter a informação tem sido explorado em diferentes áreas.
As narrativas não são só a principal forma como as pessoas obtêm o sentido do mundo, mas
também a forma mais fácil que encontrámos para partilhar informações complexas.
Devido ao seu potencial, as narrativas foram recentemente abordadas na área da Visualização
de Informação e do Conhecimento, muitas vezes apelidada de Visualização Narrativa.
Esta questão é particularmente importante para os media, uma das áreas que tem impulsionado
a investigação em Visualização Narrativa. A necessidade de incorporar histórias nas visualizações
surge da necessidade de partilhar dados complexos de um modo envolvente. Hoje em dia
somos confrontados com a elevada quantidade de informação disponível, um desafio difícil de
resolver. Os avanços da tecnologia permitiram ir além das formas tradicionais de narrativa e
de representação de dados, dando-nos meios mais atraentes e sofisticados para contar histórias.
Nesta tese, exploro os benefícios da introdução de narrativas nas visualizações. Adicionalmente
também exploro formas de combinar histórias com a visualizações e métodos
eficientes para representar e dar sentido aos dados de uma forma que permite que as pessoas se
relacionem com a informação. Esta investigação está bastante próxima da área do jornalismo,
no entanto estas técnicas podem ser aplicadas em diferente áreas (educação, visualização científica,
etc.). Para explorar ainda mais este tema foi adotada um avaliação que utiliza diferentes
metodologias como a tipologia, vários casos de estudo, um estudo com grupos de foco, e ainda
estudos de design e análise de técnicas.The benefits of storytelling are long-known and its potential to simplify concepts,
convey cultural values and experiences, create emotional connection, and capacity to help retain
information has been explored in di erent areas, such as journalism, education, marketing,
and others. Narratives not only have been the main way people make sense of the world, but
also the easiest way humans found out to share complex information.
Due to its potential narratives have also recently been approached in the area of Information
and Knowledge Visualization, several times being referred to as Narrative Visualization.
This matter is also particularly important for news media, one of the areas that has been pushing
the research on Narrative Visualization. The necessity to incorporate storytelling in visualizations
arises from the need to share complex data in a way that is engaging. Nowadays we also
have the challenge of the high amount of information available, which can be hard to cope with.
Advances in technology have enabled us to go beyond the traditional forms of storytelling and
representing data, giving us more attractive and sophisticated means to tell stories.
In this dissertation, I explore the benefits of infusing visualizations with narratives. In
addition I also present ways of combining storytelling with visualization and e cient methods
to represent and make sense of data in a way that allows people to relate with the information.
This research is closely related to journalism, but these techniques can be applied to completely
di erent areas (education, scientific visualization, etc.). To further explore this topic a mixedmethod
evaluation that consists of a typology, several case studies and a focus group study
was chosen, as well as design studies and techniques review. This dissertation is intended to
contribute to the evolving understanding of the field of narrative visualization
From tool to instrument: An experiential analysis of interacting with Information Visualization.
Information Visualizations (InfoVis) are tools that represent huge amount of abstract data visually on a computer screen. These tools are not reaching the users since constituents of good InfoVis design are still an unknown. In this thesis I argue that good design is one that delivers positive experiences due to the subjectivity of the knowledge gaining processes. Hence, what constitutes a positive experience is the focus of this research. The application domain chosen was the Academic Literature Domain (ALD). ALD InfoVis tools exist however they do not cater for users' requirements or interface usability, both of which are crucial for a better experience. As a result, an ALD InfoVis tool was created following a User Centred Design (UCD) approach, starting with requirements and ending with usability. The requirements were first generated based on a qualitative study from which it became clear that researchers equate authors with their publications and position them in terms of the ideas they portray. Based on this, the tool was designed and implemented. The tool's usability was then evaluated through a set of low and high level tasks. Low-level tasks target the visual syntax whereas high-level tasks tap into the generated semantics. The latter allowed for subjective reasoning and interaction, and were therefore used as the basis of the experiential study. The experiential study captured users' experiences by relying on a Grounded Theory (GT) analysis. This study resulted in the generation of a base theory of InfoVis interaction that properly fitted within the context of the instrumental genesis theoretical framework which argues for the design of instruments not tools, where instruments are mental appropriations of tools. The theoretical approach applied by this research has value across InfoVis even if not tailored for evaluation
Making Sense of Document Collections with Map-Based Visualizations
As map-based visualizations of documents become more ubiquitous, there is a greater need for them to support intellectual and creative high-level cognitive activities with collections of non-cartographic materials -- documents. This dissertation concerns the conceptualization of map-based visualizations as tools for sensemaking and collection understanding. As such, map-based visualizations would help people use georeferenced documents to develop understanding, gain insight, discover knowledge, and construct meaning. This dissertation explores the role of graphical representations (such as maps, Kohonen maps, pie charts, and other) and interactions with them for developing map-based visualizations capable of facilitating sensemaking activities such as collection understanding. While graphical representations make document collections more perceptually and cognitively accessible, interactions allow users to adapt representations to users’ contextual needs. By interacting with representations of documents or collections and being able to construct representations of their own, people are better able to make sense of information, comprehend complex structures, and integrate new information into their existing mental models. In sum, representations and interactions may reduce cognitive load and consequently expedite the overall time necessary for completion of sensemaking activities, which typically take much time to accomplish. The dissertation proceeds in three phases. The first phase develops a conceptual framework for translating ontological properties of collections to representations and for supporting visual tasks by means of graphical representations. The second phase concerns the cognitive benefits of interaction. It conceptualizes how interactions can help people during complex sensemaking activities. Although the interactions are explained on the example of a prototype built with Google Maps, they are independent iv of Google Maps and can be applicable to various other technologies. The third phase evaluates the utility, analytical capabilities and usability of the additional representations when users interact with a visualization prototype – VIsual COLlection EXplorer. The findings suggest that additional representations can enhance understanding of map-based visualizations of library collections: specifically, they can allow users to see trends, gaps, and patterns in ontological properties of collections
- …