Context-Aware Visualization Recommendations Reduce Decision Overload for Operators

Data visualization recommendation aims to assist the user in creating visualizations from a given dataset. The process of creating appropriate visualizations requires expert knowledge of the available data model as well as the dashboard application that is used. To relieve the user from requiring this knowledge and from the manual process needed to create numerous visualizations or dashboards, we present a context-aware visualization recommender system that automatically recommends a personalized dashboard to the user, based on the system they are monitoring and the task they are trying to achieve. Through a knowledge graph-based approach, expert knowledge about the data and the application is included to improve the recommendation process. Preliminary results show a promising performance of the presented recommender system, validating its ability to assist the end-user in visualizing the most relevant information and reduce the time required to manually create dashboards.