EuroVisShort2019

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https://diglib.eg.org/handle/10.2312/2632781

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Browsing EuroVisShort2019 by Subject "Information visualization"

Now showing 1 - 4 of 4
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    Authoring Combined Textual and Visual Descriptions of Graph Data
    (The Eurographics Association, 2019) Latif, Shahid; Su, Kaidie; Beck, Fabian; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    The interactive linking of text and visualizations supports easy and guided exploration of information and results in a coherent document. Authoring such documents for the web requires writing custom HTML and JavaScript. Existing research aims at reducing the effort by providing a declarative syntax. However, these approaches either do not support the interactive linking of text and visualizations or require advance programming skills to establish this linking. Targeting a specific type of data i.e., graph data, we introduce an approach that uses a declarative syntax to produce interactive documents and requires little to no programming. Based on the user specifications in an HTML file, the system queries the database to retrieve subgraphs and link them to the relevant text fragments. The resulting document consists of a node-link diagram and text; the two representations are closely linked via interactions and word-sized graphics, and provide an active reading experience.
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    CoCoa: A Linked Network Visualization System of Co-citation and Co-author Relationships
    (The Eurographics Association, 2019) Nakazawa, Rina; Itoh, Takayuki; Saito, Takafumi; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    We usually use a text-based search engine while surveying research papers. Such search systems have difficulties for novice researchers in case they do not know appropriate keywords or do not understand the positions of papers. Many visualization tools of citation networks have been proposed to help this task. These tools demonstrated that not only text information of papers but citation relationships and co-author relationships also are helpful clues for research survey. We propose CoCoa, a linked network visualization of co-citation and co-author relationships for surveying research papers. Our system visualizes both citation and co-author networks at the same time. To make comparison and grasp of correspondence between co-citation and co-author networks easier, the system treats both a paper and an author as bags of words and cluster them into topics applying LDA (Latent Dirichlet Allocation) at the same time. Based on the clustering result, it places the clusters of a citation network by a hybrid force-directed and space-filling algorithm. The position of topic clusters in the networks would have an influence on the correspondence of a particular topic in the networks. Our system extracts the clusters which consist of the common combinations of topics in two networks. Then it reuses the positions of the clusters in a citation network as the initial cluster positions of a co-author network, supposing there are a large number of authors.
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    Label Placement for Outliers in Scatterplots
    (The Eurographics Association, 2019) Mumtaz, Haris; Garderen, Mereke van; Beck, Fabian; Weiskopf, Daniel; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    In many application scenarios, outliers can be associated with specific importance for various reasons. In such cases, labeling outliers is important to connect them to the actual semantics of the respective entity. In this paper, we present a cost-based greedy approach that places labels with outliers within scatterplots. The approach uses a search strategy to find the position that represents the least cost to place labels. Our approach can also produce different labeling outcomes by adjusting the weights of the criteria of the cost function. We demonstrate our approach with scatterplots produced from object-oriented software metrics, where outliers often relate to bad smells in the software.
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    Visualizing Transportation Flows with Mode Split using Glyphs
    (The Eurographics Association, 2019) PĂ©rez-Messina, Ignacio; Graells-Garrido, Eduardo; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    The increasing trend of using unconventional data in urban planning environments has led to the need for developing systems that can visualize this data. Here we present a visualization for studying commuting flows within a city, with a particular focus on the distribution of mode of transportation usage. Our design, called ModalCell, uses a glyph-based flow map to show a city's flows considering mode split, direction, and distance range. We evaluate ModalCell with a pilot survey and a use case that shows the potential of the approach to make flows within a city visible and understandable.