DeepAI AI Chat
Log In Sign Up

An Automated Approach to Reasoning About Task-Oriented Insights in Responsive Visualization

by   Hyeok Kim, et al.
Carnegie Mellon University
Northwestern University

Authors often transform a large screen visualization for smaller displays through rescaling, aggregation and other techniques when creating visualizations for both desktop and mobile devices (i.e., responsive visualization). However, transformations can alter relationships or patterns implied by the large screen view, requiring authors to reason carefully about what information to preserve while adjusting their design for the smaller display. We propose an automated approach to approximating the loss of support for task-oriented visualization insights (identification, comparison, and trend) in responsive transformation of a source visualization. We operationalize identification, comparison, and trend loss as objective functions calculated by comparing properties of the rendered source visualization to each realized target (small screen) visualization. To evaluate the utility of our approach, we train machine learning models on human ranked small screen alternative visualizations across a set of source visualizations. We find that our approach achieves an accuracy of 84 ranking visualizations. We demonstrate this approach in a prototype responsive visualization recommender that enumerates responsive transformations using Answer Set Programming and evaluates the preservation of task-oriented insights using our loss measures. We discuss implications of our approach for the development of automated and semi-automated responsive visualization recommendation.


page 2

page 3

page 4

page 6

page 7

page 9

page 10

page 11


Cicero: A Declarative Grammar for Responsive Visualization

Designing responsive visualizations can be cast as applying transformati...

Design Patterns and Trade-Offs in Responsive Visualization for Communication

Increased access to mobile devices motivates the need to design communic...

A Comparative Evaluation of Animation and Small Multiples for Trend Visualization on Mobile Phones

We compare the efficacy of animated and small multiples variants of scat...

Prototyping Information Visualization in 3D City Models: a Model-based Approach

When creating 3D city models, selecting relevant visualization technique...

VizML: A Machine Learning Approach to Visualization Recommendation

Data visualization should be accessible for all analysts with data, not ...

VisMaker: a Question-Oriented Visualization Recommender System for Data Exploration

The increasingly rapid growth of data production and the consequent need...

On the "Calligraphy" of Books

Authorship attribution is a natural language processing task that has be...