Authors:
Pawandeep Kaur
and
Michael Owonibi
Affiliation:
Friedrich-Schiller-University, Germany
Keyword(s):
Data Visualization, Visualization Recommendation, Visual Mapping, Review, Survey, Graphic Selection.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Interactive Visual Interfaces for Visualization
;
Knowledge-Assisted Visualization
;
Perception and Cognition in Visualization
;
Visualization Taxonomies and Models
Abstract:
Choosing the best visualization of a given dataset becomes more and more complex as not only the amount
of data, but also the number of visualization types and the number of potential uses of visualizations grow
tremendously. This challenge has spurred on the research into visualization recommendation systems. The
ultimate aim of such a system is the suggestion of visualizations which provide interesting insights into the
data. It should ideally consider data characteristics, domain knowledge and individual preferences to produce
aesthetically appealing and easy to understand charts. Based on the mentioned factors, we have reviewed in
this paper the state-of-the-art in visualization recommendation systems starting from the earliest attempt made
on this subject. We identify challenges to visualization and visualization recommendation to guide future
research directions.