Browsing by Author "Streit, Marc"

Now showing 1 - 3 of 3
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    A Process Model for Dashboard Onboarding
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Dhanoa, Vaishali; Walchshofer, Conny; Hinterreiter, Andreas; Stitz, Holger; Gröller, Eduard; Streit, Marc; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Dashboards are used ubiquitously to gain and present insights into data by means of interactive visualizations. To bridge the gap between non-expert dashboard users and potentially complex datasets and/or visualizations, a variety of onboarding strategies are employed, including videos, narration, and interactive tutorials. We propose a process model for dashboard onboarding that formalizes and unifies such diverse onboarding strategies. Our model introduces the onboarding loop alongside the dashboard usage loop. Unpacking the onboarding loop reveals how each onboarding strategy combines selected building blocks of the dashboard with an onboarding narrative. Specific means are applied to this narration sequence for onboarding, which results in onboarding artifacts that are presented to the user via an interface. We concretize these concepts by showing how our process model can be used to describe a selection of real-world onboarding examples. Finally, we discuss how our model can serve as an actionable blueprint for developing new onboarding systems.
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    Survey on the Analysis of User Interactions and Visualization Provenance
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Xu, Kai; Ottley, Alvitta; Walchshofer, Conny; Streit, Marc; Chang, Remco; Wenskovitch, John; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
    There is fast-growing literature on provenance-related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete picture of the current state of inquiry and identify knowledge gaps or possible avenues for further investigation. In this STAR, we aim to produce a comprehensive survey of work in the data visualization and visual analytics field that focus on the analysis of user interaction and provenance data. We structure our survey around three primary questions: (1) WHY analyze provenance data, (2) WHAT provenance data to encode and how to encode it, and (3) HOW to analyze provenance data. A concluding discussion provides evidence-based guidelines and highlights concrete opportunities for future development in this emerging area.
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    Visualizing Pairwise Feature Interactions in Neural Additive Models
    (The Eurographics Association, 2023) Steinparz, Christian; Hinterreiter, Andreas; Streit, Marc; Gillmann, Christina; Krone, Michael; Lenti, Simone
    We present an approach for incorporating feature interactions into Neural Additive Models (NAMs), building upon existing work in this area, to enhance their predictive capabilities while maintaining interpretability. Our contribution focuses on the visual exploration and management of the increased number of feature maps resulting from the addition of pairwise feature combinations to NAMs. This method allows for effectively visualizing individual and pairwise feature interactions using line plots and heatmaps, respectively. To address the potential explosion in the number of feature maps, we apply different scoring functions to compute the importance of a feature map and then filter and sort them based on their importance. The proposed interactive dashboard effectively manages large sets of feature maps, while preserving the white-box properties of NAMs.