Bleisch, Susanne

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Bleisch
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Susanne
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Bleisch, Susanne

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2020 - 20235
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Enddatum: 2023 × Anfangsdatum: 2020 ×

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  • Vorschaubild
    Publikation
    Square-glyphs. Assessing the readability of multidimensional spatial data visualized as square-glyphs
    (Taylor & Francis, 2023) Müller, Gianna; Hollenstein, Daria; Cöltekin, Arzu; Bleisch, Susanne [in: International Journal of Cartography]
    Glyphs have long been used to approach the challenge of visualising multidimensional data with geospatial reference. Depending on the glyph design, data-dense visualizations of several concurrent data dimensions can be created. The square-glyph is a compound glyph to represent up to four data dimensions, e.g. walkability indices, with reference to a gridded geographic space (Bleisch and Hollenstein 2018 [Exploring multivariate representations of indices along linear geographic features. Proceedings of the 2017 International Cartographic Conference, Washington D.C. (pp. 1–5)]). In this paper, we present a user study to evaluate the readability and interpretability of the square-glyphs. We compare user performance with square-glyph plots containing two and four simultaneously mapped data dimensions under different value compositions. Our results show that the user performance with square-glyphs does not decrease as the number of data dimensions represented increases from two to four. The study results indicate no significant differences in efficiency and effectiveness between the four-dimensional square-glyphs and the two-dimensional square-glyphs. The average values of five adjacent glyphs can be estimated with a mean error of eight percentage points. The results suggest that equal value distances between the displayed dimensions are more accurately perceived in a lower-value composition than in higher-value arrangements.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Poster Presentation of Project Examples in the Field of Artificial Intelligence
    (17.11.2022) Schwaninger, Adrian; Sterchi, Yanik; Wäfler, Toni; Renggli, Philipp; Rack, Oliver; Bleisch, Susanne; Paneth, Lisa; Jeitziner, Loris Tizian; Gasparik, Matus; Zahn, Carmen
    06 - Präsentation
  • Vorschaubild
    Publikation
    Toward flexible visual analytics augmented through smooth display transitions
    (Elsevier, 2021) Tominski, Christian; Andrienko, Gennady; Andrienko, Natalia; Bleisch, Susanne; Fabrikant, Sara Irina; Mayr, Eva; Miksch, Silvia; Pohl, Margit; Skupin, André [in: Visual Informatics]
    Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Gaining overview with transient focus+context maps
    (Taylor & Francis, 2021) Hollenstein, Daria; Bleisch, Susanne [in: International Journal of Cartography]
    Gaining an overview of large spatial data sets presents a challenge common to various domains. 'Overviewing' spatial data involves viewing different areas of focus and context at different scales and requires access to detail from zoomed-out views. Standard pan and zoom interfaces provide limited support with this. Motivated by the application scenario of flood risk monitoring, we extend pan and zoom affordances with a combination of focus+context techniques and multiple maps to support 'overviewing' spatial data with a graph-like information structure. A combination of transient overlays to preview context-on-demand as well as detail-on-demand with the option to decouple additional maps enables fast navigation through the graph-like information space. User-created and -positioned, resizable multiple maps allow for simultaneous exploration of distant regions at flexible scales. The seamless integration of these concepts and the versatility of its components allow for continuously adaptable, user-defined layouts that support various analysis situations. We present a prototype implementation of this interaction model and illustrate its working in application to a hydrometric network, but we believe the model could be transferred to graph-like data in other domains.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Exploratory bivariate and multivariate geovisualizations of a social vulnerability index
    (North American Cartographic Information Society, 2020) Strode, Georgianna; Mesev, Victor; Bleisch, Susanne; Ziewitz, Kathryn; Reed, Fennis; Morgan, John Derek [in: Cartographic Perspectives]
    In the United States, the Centers for Disease Control and Prevention (CDC) is the national agency that conducts and supports public health research and practice. Among the CDC’s many achievements is the development of a social vulnerability index (SVI) to aid planners and emergency responders when identifying vulnerable segments of the population, especially during natural hazard events. The index includes an overall social vulnerability ranking as well as four individual themes: socioeconomic, household composition & disability, ethnicity & language, and housing & transportation. This makes the SVI dataset multivariate, but it is typically viewed via maps that show one theme at a time. This paper explores a suite of cartographic techniques that can represent the SVI beyond the univariate view. Specifically, we recommend three techniques: (1) bivariate mapping to illustrate overall vulnerability and population density, (2) multivariate mapping using cartographic glyphs to disaggregate levels of the four vulnerability themes, and (3) visual analytics using Euler diagrams to depict overlap between the vulnerability themes. The CDC’s SVI, and by extension, vulnerability indices in other countries, can be viewed in a variety of cartographic forms that illustrate the location of vulnerable groups of society. Viewing data from various perspectives can facilitate the understanding and analysis of the growing amount and complexity of data.
    01A - Beitrag in wissenschaftlicher Zeitschrift