EuroVisShort2018

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https://diglib.eg.org/handle/10.2312/2632400

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Browsing EuroVisShort2018 by Subject "Information visualization"

Now showing 1 - 4 of 4
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    Exploring Interactive Linking Between Text and Visualization
    (The Eurographics Association, 2018) Latif, Shahid; Liu, Diao; Beck, Fabian; Jimmy Johansson and Filip Sadlo and Tobias Schreck
    Visualizations are included in documents as augmentation to text and they become more intuitive if readers have the ability to interact with them. Modern web technologies facilitate the development of interactive documents including both text and visualizations. The aim of this research it to explore the design space of possible visualization-text linking and interactions based on various triggers such as mouse events. We describe a framework that takes text containing markup, a related dataset, and a configuration file as inputs and produces an interactive document. The resulting document provides interactions such as details on demand, visual highlighting and comparison, and bushing-and-linking. In addition to regular sized graphics, the use of word-sized graphics or sparklines presents related content in view-focus of the reader. Finally, an illustrative example is presented to showcase the approach.
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    Learning from the Best - Visual Analysis of a Quasi-Optimal Data Labeling Strategy
    (The Eurographics Association, 2018) Bernard, Jürgen; Hutter, Marco; Lehmann, Markus; Müller, Martin; Zeppelzauer, Matthias; Sedlmair, Michael; Jimmy Johansson and Filip Sadlo and Tobias Schreck
    An overarching goal of active learning strategies is to reduce the human effort when labeling datasets and training machine learning methods. In this work, we focus on the analysis of a (theoretical) quasi-optimal, ground-truth-based strategy for labeling instances, which we refer to as the upper limit of performance (ULoP). Our long-term goal is to improve existing active learning strategies and to narrow the gap between current strategies and the outstanding performance of ULoP. In an observational study conducted on five datasets, we leverage visualization methods to better understand how and why ULoP selects instances. Results show that the strategy of ULoP is not constant (as in most state-of-the-art active learning strategies) but changes within the labeling process. We identify three phases that are common to most observed labeling processes, partitioning the labeling process into (1) a Discovery Phase, (2) a Consolidation Phase, and (3) a Fine Tuning Phase.
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    STEIN: Speeding up Evaluation Activities With a Seamless Testing Environment INtegrator
    (The Eurographics Association, 2018) Angelini, Marco; Blasilli, Graziano; Lenti, Simone; Santucci, Giuseppe; Jimmy Johansson and Filip Sadlo and Tobias Schreck
    The evaluation of an information visualization system is a complex activity, involving the understanding of both the visualization itself and the process that it is meant to support. Moreover, if the evaluation activity includes a task based user study, it requires a considerable effort, involving both conceptual (e.g., the definition of user tasks) and technical (e.g., logging of the relevant user actions while using the system) aspects. The solution presented in this paper, STEIN (Seamless Testing Environment INtegrator), allows integrating the system under evaluation with the questions that have been designed for the user study, tracing the user's activities and automatically collecting the user's answers using the events that are generated while interacting with the system. This results in a substantial reduction of the effort associated with technical activities, thus allowing the evaluation designer to focus mainly on the conceptual aspects. A prototype of the system is available for download at awareserver.dis.uniroma1.it:8080/stein.
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    TapVis: A Data Visualization Approach for Assessment of Alternating Tapping Performance in Patients with Parkinson's Disease
    (The Eurographics Association, 2018) Jusufi, Ilir; Memedi, Mevludin; Nyholm, Dag; Jimmy Johansson and Filip Sadlo and Tobias Schreck
    Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson's disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems. In this paper we present a visualization metaphor that represents symptom information of PD patients during tapping tests performed with a smartphone. The metaphor has been developed and evaluated with a clinician. It enabled the clinician to observe fine motor impairments and identify motor fluctuations regarding several movement aspects of patients that perform the tests from their homes.