EuroVA2020

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https://diglib.eg.org/handle/10.2312/2632904

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Browsing EuroVA2020 by Subject "Applied computing"

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    Progressive Parameter Space Visualization for Task-Driven SAX Configuration
    (The Eurographics Association, 2020) Loeschcke, Sebastian; Hogräfer, Marius; Schulz, Hans-Jörg; Turkay, Cagatay and Vrotsou, Katerina
    As time series datasets are growing in size, data reduction approaches like PAA and SAX are used to keep them storable and analyzable. Yet, finding the right trade-off between data reduction and remaining utility of the data is a challenging problem. So far, it is either done in a user-driven way and offloaded to the analyst, or it is determined in a purely data-driven, automated way. None of these approaches take the analytic task to be performed on the reduced data into account. Hence, we propose a task-driven parametrization of PAA and SAX through a parameter space visualization that shows the difference of progressively running a given analytic computation on the original and on the reduced data for a representative set of data samples. We illustrate our approach in the context of climate analysis on weather data and exoplanet detection on light curve data.
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    Quality Metrics to Guide Visual Analysis of High Dimensional Genomics Data
    (The Eurographics Association, 2020) Fernstad, Sara Johansson; Macquisten, Alexander; Berrington, Janet; Embleton, Nicholas; Stewart, Christopher; Turkay, Cagatay and Vrotsou, Katerina
    Studies of genome sequenced data are increasingly common in many domains. Technological advances enable detection of hundreds of thousands of biological entities in samples, resulting in extremely high dimensional data. To enable exploration and understanding of such data, efficient visual analysis approaches are needed that take domain and data specific requirements into account. Based on a survey with bioscience experts, this paper suggests a categorisation and a set of quality metrics to identify patterns of interest, which can be used as guidance in visual analysis, as demonstrated in the paper.