EuroVA14

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https://diglib.eg.org/handle/10.2312/7746

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Browsing EuroVA14 by Subject "General"

Now showing 1 - 3 of 3
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    Integrated Visualization and Analysis of a Multi-scale Biomedical Knowledge Space
    (The Eurographics Association, 2014) Agibetov, Asan; Vaquero, Ricardo Manuel Millan; Friese, Karl-Ingo; Patane, Giuseppe; Spagnuolo, Michela; Wolter, Franz-Erich; M. Pohl and J. Roberts
    The study and analysis of relationships in a complex and multi-scale data set is a challenge of information and scientific visualization. This work proposes an integrated visualization to capture all the important aspects of multi-scale data into the same view by leveraging the multi-scale biomedical knowledge encoded into an underlying ontology. Ontology supports visualization by providing semantic means to identify relevant items that must be presented to the user. The study and analysis of relationships across the scales are presented as results of queries to the multi-scale biomedical knowledge space. We demonstrate the prototype of the graphical interface of an integrated visualization framework and the knowledge formalization support in an example scenario related to the musculoskeletal diseases.
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    Supporting an Early Detection of Diabetic Neuropathy by Visual Analytics
    (The Eurographics Association, 2014) Luboschik, Martin; Röhlig, Martin; Kundt, Günther; Stachs, Oliver; Peschel, Sabine; Zhivov, Andrey; Guthoff, Rudolf F.; Winter, Karsten; Schumann, Heidrun; M. Pohl and J. Roberts
    In this paper, we describe a step-wise approach to utilize ophthalmic markers for detecting early diabetic neuropathy (DN), the most common long-term complication of diabetes mellitus. Our approach is based on the Visual Analytics Mantra: First, we statistically analyze the data to identify those variables that separate DN patients from a control group. Afterwards, we show the important separating variables individually, but also in the context of all variables regarding a pre-defined classification. By doing so, we support the understanding of the categorization in respect of the value distribution of variables. This allows for zooming, filtering and further analysis like deleting non-relevant variables that do not contribute to the definition of markers as well as deleting data records with false data values or false classifications. Finally, outliers are observed and investigated in detail. So, a third group of potential DN patients can be introduced. In this way, the detection of early DN can be effectively supported.
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    A Visual Analytics Field Experiment to Evaluate Alternative Visualizations for Cyber Security Applications
    (The Eurographics Association, 2014) Fischer, Fabian; Davey, James; Fuchs, Johannes; Thonnard, Olivier; Kohlhammer, Jörn; Keim, Daniel A.; M. Pohl and J. Roberts
    The analysis and exploration of emerging threats in the Internet is important to better understand the behaviour of attackers and develop new methods to enhance cyber security. Fully automated algorithms alone are often not capable of providing actionable insights about the threat landscape. We therefore combine a multi-criteria clustering algorithm, tailor-made for the identification of such attack campaigns with three interactive visualizations, namely treemap representations, interactive node-link diagrams, and chord diagrams, to allow the analysts to visually explore and make sense of the resulting multi-dimensional clusters. To demonstrate the potential of the system, we share our lessons learned in conducting a field experiment with experts in a security response team and show how it helped them to gain new insights into various threat landscapes.