Human-centered Information Visualization Adaptation Engine

Abstract

Data Analytics is the art of turning data into insights for efficient and effective business decisions. Data visualization is among the most powerful tools in the data analyst’s arsenal, enabling the transformation of data into effective visualizations that can be easily comprehended. However, its effectiveness is often affected by the data analysts’ experience and their ability to quickly understand and interpret information. Even though business analytics tools have made a significant progress to deliver immersive data visualization environments for improving users’ efficiency and effectiveness, they still do not consider the individual differences in the core process that influences the visualization structure, encoding, and readability.

This paper leverages the users’ individual differences to deliver a novel human-centered by-design adaptation engine for business users. The adaptation engine aims to improve the comprehension of data visualizations by delivering personalized content (visualization type and adaptation of visual elements), which in turn leads to improved accuracy and time-to-action efficiency. The proposed adaptation mechanism is evaluated using 45 professional business analysts from multiple industry sectors. The results suggest that individual differences can play an important role in the adaptation process of data visualizations enhancing analysts’ comprehensibility and decision making.