Browsing by Author "Kucher, Kostiantyn"

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    EuroVis 2024 Posters: Frontmatter
    (The Eurographics Association, 2024) Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
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    Project in Visualization and Data Analysis: Experiences in Designing and Coordinating the Course
    (The Eurographics Association, 2021) Kucher, Kostiantyn; Martins, Rafael M.; Kerren, Andreas; Sousa Santos, Beatriz and Domik, Gitta
    Visual analytics involves both visual and computational components for empowering human analysts who face the challenges of making sense and making use of large and heterogeneous data sets in various application domains. In order to facilitate the learning process for the students at higher education institutions with regard to both the theoretical knowledge and practical skills in visual analytics, the respective courses must cover a variety of topics and include multiple assessment methods and activities. In this paper, we report on the design and first instantiation of a full term project-based course in visualization and data analysis, which was recently offered to graduate and post-graduate students at our department and met with positive feedback from the course participants.
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    Text Visualization Revisited: The State of the Field in 2019
    (The Eurographics Association, 2019) Kucher, Kostiantyn; Kerren, Andreas; Madeiras Pereira, João and Raidou, Renata Georgia
    Text and document data visualization is an important research field within information visualization and visual analytics with multiple application domains including digital humanities and social media, for instance. During the past five years, we have been collecting text visualization techniques described in peer-reviewed literature, categorizing them according to a detailed categorization schema, and providing the resulting manually curated collection in an online survey browser. In this poster paper, we present the updated results of analyses of this data set as of spring 2019. Compared to the recent surveys and meta-analyses that mainly focus on particular aspects and problems related to text visualization, our results provide an overview of the current state of the text visualization field and the respective research community in general.
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    Towards a Visual Analytics System for Emotion Trajectories in Multiparty Conversations
    (The Eurographics Association, 2024) Huang, Zeyang; Kucher, Kostiantyn; Kerren, Andreas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    Visualizing sentiments in textual data has received growing interest; however, representing emotions within interlocutor relationships and associating them with the temporal progression of dialogues remains challenging. In this poster abstract, we describe the ongoing work on a visual analytics tool designed for analyzing emotion trajectories within dialogue collections composed of utterances from multiple speakers. The proposed tool provides exploration at different levels of detail to complex multigraphs, where edges represent direct responses between speakers through their utterances. Our approach includes several selection strategies for connecting different views: summaries of emotion transitions across dialogue groups, detailed analyses of individual utterances within specific dialogues of interest in interlocutor networks, and close reading. The tool aims to support model development in natural language processing by allowing users to explore text corpora interactively.
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    Visual Analysis of Power Plant Data for European Countries
    (The Eurographics Association, 2024) Wang, Jinyi; Kucher, Kostiantyn; Kerren, Andreas; Kucher, Kostiantyn; Diehl, Alexandra; Gillmann, Christina
    A power plant is a complex real-world system associated with rich multidimensional data relevant to its construction and activity. Thus, choosing an appropriate way to visualize power plant data is important for users to understand and explore more about such systems. Most of the approaches existing in this field support only a static representation of data from a small region. This makes it hard for the users to get an overview or explore specific power plants. In this poster abstract, we describe an interactive visualization tool designed for the analysis of power plant data in Europe. Our approach provides an overview and detail visualization approach for Global Power Plant Database entries. With this tool, users can easily find power plants, see details on demand, filter, compare, and explore the power plant outage scenarios from the nearest neighbor perspective.