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Item EuroVis 2022 Short Papers: Frontmatter(The Eurographics Association, 2022) Agus, Marco; Aigner, Wolfgang; Hoellt, Thomas; Agus, Marco; Aigner, Wolfgang; Hoellt, ThomasItem Using Data Comics to Enhance Visualization Literacy(The Eurographics Association, 2022) Boucher, Magdalena; Stoiber, Christina; Aigner, Wolfgang; Krone, Michael; Lenti, Simone; Schmidt, JohannaVisualization Literacy as a skill is becoming important, as growing amounts of data require complex ways of visualizing and interpreting them. Yet, it is hardly taught during general education, and not many resources conveying visualization knowledge in an easily accessible way exist. We draw on the notion of data comics, which are already well-suited for communicating visualization insights, but so far have not been explored in the context of teaching visualization skills. We aim to map the research landscape around this idea through a systematic literature research and present a first overview of related areas and how they might influence data comics used to enhance visualization literacy.Item Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges(The Eurographics Association, 2014) Alsallakh, Bilal; Micallef, Luana; Aigner, Wolfgang; Hauser, Helwig; Miksch, Silvia; Rodgers, Peter; R. Borgo and R. Maciejewski and I. ViolaA variety of data analysis problems can be modelled by defining multiple sets over a collection of elements and analyzing the relations between these sets. Despite their simple concept, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-theart techniques for visualizing different kinds of set relations. We classify these techniques into 7 main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address with these challenges.Item PubViz: Lightweight Visual Presentation of Publication Data(The Eurographics Association, 2017) Rind, Alexander; Haberson, Andrea; Blumenstein, Kerstin; Niederer, Christina; Wagner, Markus; Aigner, Wolfgang; Barbora Kozlikova and Tobias Schreck and Thomas WischgollPublications play a central role in presenting the outcome of scientific research but are typically presented as textual lists, whereas related work in visualization of publication focuses on exploration - not presentation. To bridge this gap, we conducted a design study of an interactive visual representation of publication data in a BibTeX file. This paper reports our domain and problem characterization as well as our visualization design decisions in light of our user-centered design process including interviews, two user studies with a paper prototype and a d3.js prototype, and practical application at our group's website.Item Frontmatter: EuroRV3 2015 EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization(Eurographics Association, 2015) Rosenthal, Paul; Aigner, Wolfgang; Scheidegger, Carlos; -Item Comparative Evaluation of an Interactive Time-Series Visualization that Combines Quantitative Data with Qualitative Abstractions(The Eurographics Association and Blackwell Publishing Ltd., 2012) Aigner, Wolfgang; Rind, Alexander; Hoffmann, Stephan; S. Bruckner, S. Miksch, and H. PfisterIn many application areas, analysts have to make sense of large volumes of multivariate time-series data. Explorative analysis of this kind of data is often difficult and overwhelming at the level of raw data. Temporal data abstraction reduces data complexity by deriving qualitative statements that reflect domain-specific key characteristics. Visual representations of abstractions and raw data together with appropriate interaction methods can support analysts in making their data easier to understand. Such a visualization technique that applies smooth semantic zooming has been developed in the context of patient data analysis. However, no empirical evidence on its effectiveness and efficiency is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares this technique with another visualization method used in the well-known KNAVE-II framework. Both methods integrate quantitative data with qualitative abstractions whereas the first one uses a composite representation with color-coding to display the qualitative data and spatial position coding for the quantitative data. The second technique uses juxtaposed representations for quantitative and qualitative data with spatial position coding for both. Results show that the test persons using the composite representation were generally faster, particularly for more complex tasks that involve quantitative values as well as qualitative abstractions.Item Integrating Predictions in Time Series Model Selection(The Eurographics Association, 2015) Bögl, Markus; Aigner, Wolfgang; Filzmoser, Peter; Gschwandtner, Theresia; Lammarsch, Tim; Miksch, Silvia; Rind, Alexander; E. Bertini and J. C. RobertsTime series appear in many different domains. The main goal in time series analysis is to find a model for given time series. The selection of time series models is done iteratively based, usually, on information criteria and residual plots. These sources may show only small variations and, therefore, it is necessary to consider the prediction capabilities in the model selection process. When applying the model and including the prediction in an interactive visual interface it is still difficult to compare deviations from actual values or benchmark models. Judging which model fits the time series adequately is not well supported in current methods. We propose to combine visual and analytical methods to integrate the prediction capabilities in the model selection process and assist in the decision for an adequate and parsimonious model. In our approach a visual interactive interface is used to select and adjust time series models, utilize the prediction capabilities of models, and compare the prediction of multiple models in relation to the actual values.Item EuroVis 2023 Short Papers: Frontmatter(The Eurographics Association, 2023) Hoellt, Thomas; Aigner, Wolfgang; Wang, Bei; Hoellt, Thomas; Aigner, Wolfgang; Wang, BeiItem Developing an Extended Task Framework for Exploratory Data Analysis Along the Structure of Time(The Eurographics Association, 2012) Lammarsch, Tim; Rind, Alexander; Aigner, Wolfgang; Miksch, Silvia; Kresimir Matkovic and Giuseppe SantucciExploratory data analysis of time-oriented data is an important goal that Visual Analytics has to tackle. When users from real-world domains are asked about time-oriented tasks, they often refer to the unique structure of time (e.g., calendars, primitives, etc.). Several task frameworks have been developed, but none of them combines a complete, systematic approach with explicit attention to the structure of time. To fill this gap, we aim for complementing an established task framework with a rule set that explicitly models the structure of time for tasks. This rule set allows to consistently formulate tasks for evaluating time-oriented data analysis methods.Item A Unified Process for Visual-Interactive Labeling(The Eurographics Association, 2017) Bernard, Jürgen; Zeppelzauer, Matthias; Sedlmair, Michael; Aigner, Wolfgang; Michael Sedlmair and Christian TominskiAssigning labels to data instances is a prerequisite for many machine learning tasks. Similarly, labeling is applied in visualinteractive analysis approaches. However, the strategies for creating labels often differ in the two fields. In this paper, we study the process of labeling data instances with the user in the loop, from both the machine learning and visual-interactive perspective. Based on a review of differences and commonalities, we propose the 'Visual-Interactive Labeling' (VIAL) process, conflating the strengths of both. We describe the six major steps of the process and highlight their related challenges.
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