1,356 research outputs found
NetPanorama: A Declarative Grammar for Network Construction, Transformation, and Visualization
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
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
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
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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