30 research outputs found

    The State-of-the-Art of Set Visualization

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    Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

    Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

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    Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

    Diagrammatic Reasoning and Modelling in the Imagination: The Secret Weapons of the Scientific Revolution

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    Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid

    Uintah: a massively parallel problem solving environment

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    Journal ArticleThis paper describes Uintah, a component-based visual problem solving environment (PSE) that is designed to specifically address the unique problems of massively parallel computation on terascale computing platforms. Uintah supports the entire life cycle of scientific applications by allowing scientific programmers to quickly and easily develop new techniques, debug new implementations, and apply known algorithms to solve novel problems. Uintah is built on three principles: 1) As much as possible, the complexities of parallel execution should be handled for the scientist, 2) software should be reusable at the component level, and 3) scientists should be able to dynamically steer and visualize their simulation results as the simulation executes. To provide this functionality, Uintah builds upon the best features of the SCIRun PSE and the DOE Common Component Architecture (CCA)

    Gráficos que cuentan historias: caracterización de infografías y visualizaciones narrativas a través de Pinterest

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    Este artículo tiene por objetivo caracterizar las infografías y visualizaciones en términos narrativos. Para ello, se realizarán tres operaciones. Primero, se proporcionarán definiciones específicas para explicar qué entendemos por “infografías y visualizaciones” y “narrativa” en el contexto digital. Luego, se presentará la herramienta de descubrimiento visual Pinterest, empleada para recopilar un corpus representativo de infografías y visualizaciones a través del sistema de tableros (colecciones) y pines (imágenes), del cual se ha extraído un corpus aún más específico de infografías y visualizaciones narrativas. Por último, en la discusión de los resultados se destacarán los formatos infográficos narrativos más predominantes extraídos de este corpus más concreto

    A survey of computational steering environments

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    Computational steering is a powerful concept that allows scientists to interactively control a computational process during its execution. In this paper, a survey of computational steering environments for the on-line steering of ongoing scientific and engineering simulations is presented. These environments can be used to create steerable applications for model exploration, algorithm experimentation, or performance optimization. For each environment the scope is identified, the architecture is summarized, and the concepts of the user interface is described. The environments are compared and conclusions and future research issues are given

    Computational steering and the SCIRun integrated problem solving environment

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    Journal ArticleSCIRun is a problem solving environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. We review related systems and introduce a taxonomy that explores different computational steering solutions. Considering these approaches, we discuss why a tightly integrated problem solving environment, such as SCIRun, simplifies the design and debugging phases of computational science applications and how such an environment aids in the scientific discovery process

    Integrated problem solving environment: the SCIRun computational steering system

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    Journal ArticleSCIRun is a scientific programming environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. We review related systems and introduce a taxonomy that explores different computational steering solutions, Considering these approaches, we discuss why a tightly integrated problem solving environment, such as SCIRun, simplifies the design and debugging phases of computational science applications and how such an environment aids in the scientific discovery process

    Mini-VLAT: A Short and Effective Measure of Visualization Literacy

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    The visualization community regards visualization literacy as a necessary skill. Yet, despite the recent increase in research into visualization literacy by the education and visualization communities, we lack practical and time-effective instruments for the widespread measurements of people's comprehension and interpretation of visual designs. We present Mini-VLAT, a brief but practical visualization literacy test. The Mini-VLAT is a 12-item short form of the 53-item Visualization Literacy Assessment Test (VLAT). The Mini-VLAT is reliable (coefficient omega = 0.72) and strongly correlates with the VLAT. Five visualization experts validated the Mini-VLAT items, yielding an average content validity ratio (CVR) of 0.6. We further validate Mini-VLAT by demonstrating a strong positive correlation between study participants' Mini-VLAT scores and their aptitude for learning an unfamiliar visualization using a Parallel Coordinate Plot test. Overall, the Mini-VLAT items showed a similar pattern of validity and reliability as the 53-item VLAT. The results show that Mini-VLAT is a psychometrically sound and practical short measure of visualization literacy
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