This can present difficulties as the user’s unfamiliarity with visualization practice and infrequent use of the tool can result in long processing time, inaccurate data representations or inappropriate visual encodings. Often the user is not a professional analyst or data scientist and uses the tool infrequently, to support an aspect of their job. General-purpose visualization tools are used by people with varying degrees of data literacy. In this paper we describe exploroBOT an d present an evaluation of the tool. The user-driven approach draws on the browse/explore metaphor commonly applied in social media applications and is supported by guided navigation. These combined approaches enable users to explore visualizations based on a degree of “interestingness”. The exploroBOT automatically generates visualizations and the exploration guidance path (an associated network of decision points, mapping nodes where visualizations change).
To address this problem, we developed a visual analytics application called exploroBOT. Visual Data Analysis and Knowledge DiscoveryĪbstract: General-purpose visualization tools are used by people with varying degrees of data literacy. Interface and Interaction Techniques for Visualization Interactive Visual Interfaces for Visualization Subjects/Areas/Topics: Abstract Data VisualizationĬomputer Vision, Visualization and Computer Graphics Keyword(s): Visual Analytics, Automatic Chart Generation, Data Exploration, Intelligent Visual Interfaces.
Authors: John McAuley 1 Rohan Goel 2 and Tamara Matthews 1Īffiliations: 1 CeADAR, School of Computing, Technological University Dublin, Kevin Street, Dublin 8 and Ireland 2 CeADAR, School of Computing, Technological University Dublin, Kevin Street, Dublin 8, Ireland, BITS Pilani, Department of Computer Science, Goa and India
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