4,228 research outputs found

    Feeling what you hear: tactile feedback for navigation of audio graphs

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    Access to digitally stored numerical data is currently very limited for sight impaired people. Graphs and visualizations are often used to analyze relationships between numerical data, but the current methods of accessing them are highly visually mediated. Representing data using audio feedback is a common method of making data more accessible, but methods of navigating and accessing the data are often serial in nature and laborious. Tactile or haptic displays could be used to provide additional feedback to support a point-and-click type interaction for the visually impaired. A requirements capture conducted with sight impaired computer users produced a review of current accessibility technologies, and guidelines were extracted for using tactile feedback to aid navigation. The results of a qualitative evaluation with a prototype interface are also presented. Providing an absolute position input device and tactile feedback allowed the users to explore the graph using tactile and proprioceptive cues in a manner analogous to point-and-click techniques

    ToonNote: Improving Communication in Computational Notebooks Using Interactive Data Comics

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    Computational notebooks help data analysts analyze and visualize datasets, and share analysis procedures and outputs. However, notebooks typically combine code (e.g., Python scripts), notes, and outputs (e.g., tables, graphs). The combination of disparate materials is known to hinder the comprehension of notebooks, making it difficult for analysts to collaborate with other analysts unfamiliar with the dataset. To mitigate this problem, we introduce ToonNote, a JupyterLab extension that enables the conversion of notebooks into “data comics.” ToonNote provides a simplified view of a Jupyter notebook, highlighting the most important results while supporting interactive and free exploration of the dataset. This paper presents the results of a formative study that motivated the system, its implementation, and an evaluation with 12 users, demonstrating the effectiveness of the produced comics. We discuss how our findings inform the future design of interfaces for computational notebooks and features to support diverse collaborators

    USABILITY TESTING OF THE M.A.E.G.U.S. SERIOUS GAME

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    Interpreting raw data in serious games and simulations can be a time consuming and uninteresting task without visualizations. This study proposes one possible solution for an interface that incorporates data visualizations for Whittinghill and Nataraja\u27s (2013) MAEGUS simulation, a serious game used to increase the retention of wind energy and solar energy concepts in students, while still being fun. After the interface was designed and developed, a think aloud usability test was conducted to answer the following research questions: how do students use a series of information visualizations to operate a multi-variate game-based simulation and what are some the usability issues the students face in the simulation? A thematic analysis was then conducted to document and organize the responses

    Automated recognition of design patterns for framework understanding

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    System design is one of the most important tasks in the software development cycles but it is also one of the most complex and time-consuming tasks. Thus, reuse of existing designs becomes very important. Object-oriented frameworks are generic designs for specific application domains that enable the reuse of designs and domain expert experience. In spite of this, frameworks are not simple to reuse because they are difficult to comprehend, mainly due to a lack of good documentation and supporting tools. In this work, an approach to framework comprehension based on the automated recognition and visualization of design patterns is presented. A tool was built to support this approach, by trying to automatically identify and explain the potentia~ patterns existing in a given designo Experimental results and conclusions of tool utilization are also presented

    How to tell stories using visualization: strategies towards narrative visualization

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    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

    Understanding Visualization: A formal approach using category theory and semiotics

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    This article combines the vocabulary of semiotics and category theory to provide a formal analysis of visualization. It shows how familiar processes of visualization fit the semiotic frameworks of both Saussure and Peirce, and extends these structures using the tools of category theory to provide a general framework for understanding visualization in practice, including: relationships between systems, data collected from those systems, renderings of those data in the form of representations, the reading of those representations to create visualizations, and the use of those visualizations to create knowledge and understanding of the system under inspection. The resulting framework is validated by demonstrating how familiar information visualization concepts (such as literalness, sensitivity, redundancy, ambiguity, generalizability, and chart junk) arise naturally from it and can be defined formally and precisely. This article generalizes previous work on the formal characterization of visualization by, inter alia, Ziemkiewicz and Kosara and allows us to formally distinguish properties of the visualization process that previous work does not

    Exploranative Code Quality Documents

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    Good code quality is a prerequisite for efficiently developing maintainable software. In this paper, we present a novel approach to generate exploranative (explanatory and exploratory) data-driven documents that report code quality in an interactive, exploratory environment. We employ a template-based natural language generation method to create textual explanations about the code quality, dependent on data from software metrics. The interactive document is enriched by different kinds of visualization, including parallel coordinates plots and scatterplots for data exploration and graphics embedded into text. We devise an interaction model that allows users to explore code quality with consistent linking between text and visualizations; through integrated explanatory text, users are taught background knowledge about code quality aspects. Our approach to interactive documents was developed in a design study process that included software engineering and visual analytics experts. Although the solution is specific to the software engineering scenario, we discuss how the concept could generalize to multivariate data and report lessons learned in a broader scope.Comment: IEEE VIS VAST 201
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