Browsing by Author "Leite, Roger A."

Now showing 1 - 3 of 3
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    Shapes of Time: Visualizing Set Changes Over Time in Cultural Heritage Collections
    (The Eurographics Association, 2019) Salisu, Saminu; Mayr, Eva; Filipov, Velitchko Andreev; Leite, Roger A.; Miksch, Silvia; Windhager, Florian; Madeiras Pereira, João and Raidou, Renata Georgia
    In cultural heritage collections, categorization is a central technique used to distinguish cultural movements, styles, or genres. For that end, objects are tagged with set-typed metadata and other information, such as time of origin. Visualizations can communicate how such sets organize a collection - and how they change over time. But existing interfaces fall short of a) representing an overview of temporal set-developments in an integrated fashion and b) of representing the set elements (i.e., the cultural objects) themselves to be contemplated on demand. Against this background, we introduce two integrated visualization techniques - a superimposition and a space-time cube view - depicting the development of sets and their elements over time. We share first results from a qualitative evaluation with casual users and outline open challenges for future research.
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    VisMiFlow: Visual Analytics to Support Citizen Migration Understanding Over Time and Space
    (The Eurographics Association, 2021) Scheidl, Andreas; Leite, Roger A.; Miksch, Silvia; Agus, Marco and Garth, Christoph and Kerren, Andreas
    Multivariate networks are complex data structures, which are ubiquitous in many application domains. Driven by a real-world problem, namely the movement behavior of citizens in Vienna, we designed and implemented a Visual Analytics (VA) approach to ease citizen behavior analyses over time and space. We used a dataset of citizens' movement behavior to, from, or within Vienna from 2007 to 2018, provided by Vienna's city. To tackle the complexity of time, space, and other moving people's attributes, we follow a data-user-tasks design approach to support urban developers. We qualitatively evaluated our VA approach with five experts coming from the field of VA and one non-expert. The evaluation illustrated the importance of task-specific visualization and interaction techniques to support users' decision-making and insights. We elaborate on our findings and suggest potential future works to the field.
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    Visual Exploration of Financial Data with Incremental Domain Knowledge
    (Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Arleo, Alessio; Tsigkanos, Christos; Leite, Roger A.; Dustdar, Schahram; Miksch, Silvia; Sorger, Johannes; Hauser, Helwig and Alliez, Pierre
    Modelling the dynamics of a growing financial environment is a complex task that requires domain knowledge, expertise and access to heterogeneous information types. Such information can stem from several sources at different scales, complicating the task of forming a holistic impression of the financial landscape, especially in terms of the economical relationships between firms. Bringing this scattered information into a common context is, therefore, an essential step in the process of obtaining meaningful insights about the state of an economy. In this paper, we present , a Visual Analytics (VA) approach for exploring financial data across different scales, from individual firms up to nation‐wide aggregate data. Our solution is coupled with a pipeline for the generation of firm‐to‐firm financial transaction networks, fusing information about individual firms with sector‐to‐sector transaction data and domain knowledge on macroscopic aspects of the economy. Each network can be created to have multiple instances to compare different scenarios. We collaborated with experts from finance and economy during the development of our VA solution, and evaluated our approach with seven domain experts across industry and academia through a qualitative insight‐based evaluation. The analysis shows how enables the generation of insights, and how the incorporation of transaction models assists users in their exploration of a national economy.