Improving Comprehension Efficiency of High Content Screening Data Through Interactive Visualizations

Abstract

In this study, an experiment is conducted to measure the performance in speed and accuracy of interactive visualizations. A platform for interactive data visualizations was implemented using Django, D3, and Angular. Using this platform, a questionnaire was designed to measure a difference in performance between interactive and noninteractive data visualizations. In this questionnaire consisting of 12 questions, participants were given tasks in which they had to identify trends or patterns. Other tasks were directed at comparing and selecting algorithms with a certain outcome based on visualizations. All tasks were performed on high content screening data sets with the help of visualizations. The difference in time to carry out tasks and accuracy of performance was measured between a group viewing interactive visualizations and a group viewing noninteractive visualizations. The study shows a significant advantage in time and accuracy in the group that used interactive visualizations over the group that used noninteractive visualizations. In tasks comparing results of different algorithms, a significant decrease in time was observed in using interactive visualizations over noninteractive visualizations.