1,356 research outputs found

    NetPanorama: A Declarative Grammar for Network Construction, Transformation, and Visualization

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    This paper introduces NetPanorama, a domain-specific language and declarative grammar for interactive network visualizations. Exploring complex networks with multivariate, geographical, or temporal information often require bespoke visualization designs, such as adjacency matrices, arc-diagrams, small multiples, timelines, or geographic map visualizations. However, creating these requires implementing data loading, data transformations, visualization, and interactivity, which is time-consuming and slows down the iterative exploration of this huge design space. With NetPanorama, a developer specifies a network visualization design as a pipeline of parameterizable steps. Our specification and reference implementation aims to facilitate visualization development and reuse; allow for easy design exploration and iteration; and make data transformation and visual mapping decisions transparent. Documentation, source code, examples, and an interactive online editor can be found online: https://netpanorama.netlify.app

    Ways of Visualizing Curves

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    International audienceThis paper reviews the many ways curves are used to encode data in information visualization. As part of our review, we introduce a curve-based visualization framework where data can be encoded in two major ways: i) through a curve’s shape (a process we call embedding) and ii) through a curve’s local visual attributes (a process we call enrichment). Our framework helps describing and organizing the rich design space of curve-based data visualizations, and offer inspiration for novel data visualizations

    Visualizing and Interacting with Geospatial Networks:A Survey and Design Space

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    This paper surveys visualization and interaction techniques for geospatial networks from a total of 95 papers. Geospatial networks are graphs where nodes and links can be associated with geographic locations. Examples can include social networks, trade and migration, as well as traffic and transport networks. Visualizing geospatial networks poses numerous challenges around the integration of both network and geographical information as well as additional information such as node and link attributes, time, and uncertainty. Our overview analyzes existing techniques along four dimensions: i) the representation of geographical information, ii) the representation of network information, iii) the visual integration of both, and iv) the use of interaction. These four dimensions allow us to discuss techniques with respect to the trade-offs they make between showing information across all these dimensions and how they solve the problem of showing as much information as necessary while maintaining readability of the visualization. https://geonetworks.github.io.Comment: To be published in the Computer Graphics Forum (CGF) journa

    The Public Life of Data: Investigating Reactions to Visualizations on Reddit

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    This research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific expertise and shared incentives openly express their thoughts, feelings, and insights in response to data visualizations. Motivated by the extensive social exchange around visualizations in online communities, this research examines characteristics and motivations of people's reactions to posts featuring visualizations. Following a Grounded Theory approach, we study 475 reactions from the /r/dataisbeautiful community, identify ten distinguishable reaction types, and consider their contribution to the discourse. A follow-up survey with 168 Reddit users clarified their intentions to react. Our results help understand the role of personal perspectives on data and inform future interfaces that integrate audience reactions into visualizations to foster a public discourse about data
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