Authors:
John McAuley
1
;
Rohan Goel
2
and
Tamara Matthews
1
Affiliations:
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
Keyword(s):
Visual Analytics, Automatic Chart Generation, Data Exploration, Intelligent Visual Interfaces.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Interactive Visual Interfaces for Visualization
;
Interface and Interaction Techniques for Visualization
;
Visual Data Analysis and Knowledge Discovery
;
Visual Representation and Interaction
;
Visualization Applications
Abstract:
General-purpose visualization tools are used by people with varying degrees of data literacy. Often the user is not a professional analyst or data scientist and uses the tool infrequently, to support an aspect of their job. 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. To address this problem, we developed a visual analytics application called exploroBOT. The exploroBOT automatically generates visualizations and the exploration guidance path (an associated network of decision points, mapping nodes where visualizations change). These combined approaches enable users to explore visualizations based on a degree of “interestingness”. The user-driven approach draws on the browse/explore metaphor commonly applied in social media applications and is supported by guided navigation. In this paper we describe exploroBOT an
d present an evaluation of the tool.
(More)