Browsing by Author "Vrotsou, Katerina"

Now showing 1 - 7 of 7
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    EuroVa 2020: Frontmatter
    (The Eurographics Association, 2020) Turkay, Cagatay; Vrotsou, Katerina; Turkay, Cagatay and Vrotsou, Katerina
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    EuroVa 2021: Frontmatter
    (The Eurographics Association, 2021) Bernard, Jürgen; Vrotsou, Katerina; Vrotsou, Katerina and Bernard, Jürgen
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    EuroVis 2021 CGF 40-3 STARs: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Smit, Noeska; Vrotsou, Katerina; Wang, Bei; Smit, Noeska and Vrotsou, Katerina and Wang, Bei
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    EuroVis 2022 CGF 41-3 STARs: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina; Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina
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    Exploring Effects of Ecological Visual Analytics Interfaces on Experts' and Novices' Decision-Making Processes: A Case Study in Air Traffic Control
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Zohrevandi, Elmira; Westin, Carl A. L.; Vrotsou, Katerina; Lundberg, Jonas; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Operational demands in safety-critical systems impose a risk of failure to the operators especially during urgent situations. Operators of safety-critical systems learn to make decisions effectively throughout extensive training programs and many years of experience. In the domain of air traffic control, expensive training with high dropout rates calls for research to enhance novices' ability to detect and resolve conflicts in the airspace. While previous researchers have mostly focused on redesigning training instructions and programs, the current paper explores possible benefits of novel visual representations to improve novices' understanding of the situations as well as their decision-making process. We conduct an experimental evaluation study testing two ecological visual analytics interfaces, developed in a previous study, as support systems to facilitate novice decisionmaking. The main contribution of this paper is threefold. First, we describe the application of an ecological interface design approach to the development of two visual analytics interfaces. Second, we perform a human-in-the-loop experiment with fortyfive novices within a simplified air traffic control simulation environment. Third, by performing an expert-novice comparison we investigate the extent to which effects of the proposed interfaces can be attributed to the subjects' expertise. The results show that the proposed ecological visual analytics interfaces improved novices' understanding of the information about conflicts as well as their problem-solving performance. Further, the results show that the beneficial effects of the proposed interfaces were more attributable to the visual representations than the users' expertise.
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    Visual Exploration of Climate-Related Volunteered Geographic Information
    (The Eurographics Association, 2020) Navarra, Carlo; Opach, Tomasz; Vrotsou, Katerina; Joling, Almar; Wilk, Julie; Neset, Tina S.; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
    This paper describes two approaches for visually exploring climate-related data collected within the citizen science research project, CitizenSensing. The project addresses the need of European cities and their citizens for enhanced knowledge of sitespecific conditions regarding climatic risks and adaptation measures. The visual exploration approaches discussed are: (1) a web portal enabling users to gain a low-level overview of the collected data on a map, and (2) a visual analysis tool facilitating in-depth visual data exploration in search of spatio-temporal patterns. The aim of the study is to assess and discuss the potential of such visual exploration approaches in the context of Volunteered Geographic Information.
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    A Window-based Approach for Mining Long Duration Event-sequences
    (The Eurographics Association, 2020) Vrotsou, Katerina; Nordman, Aida; Turkay, Cagatay and Vrotsou, Katerina
    This paper presents an interactive sequence mining approach for exploring long duration event-sequences and identifying interesting patterns within them. The approach extends previous work on exploratory sequence mining by using a sliding window to split the sequence prior to mining. Patterns are interactively grown and visualized through a tree representation, while a set of accompanying views allows for identified patterns to be explored in the context in which they occur. The approach is motivated and exemplified in the domain of air traffic control and, in particular, air traffic controller training.