A survey on automatic dashboard recommendation systems

Praveen Soni (1, 2) , Cyril de Runz (2) , Fatma Bouali (1, 3) , Gilles Venturini (4)

1 RFAI - Reconnaissance des formes et analyse d'images
2 BDTLN - Bases de données et traitement des langues naturelles
3 Université de Lille
4 LIFAT - Laboratoire d'Informatique Fondamentale et Appliquée de Tours

This paper presents a survey on automatic or semi-automatic recommendation systems which help users to create dashboards. It starts by showing the important role that dashboards play in data science, and give an informal definition of dashboards, i.e., a set of visualizations possibly with linkage, a screen layout and user feedback. We are mainly interested in systems that use a fully or partially automatic mechanism to recommend dashboards to users. This automation includes the suggestion of data and visualizations, the optimization of the layout and the use of user feedback. We position our work with respect to existing surveys. Starting from a set of over 1000 papers, we have selected and analyzed 19 papers/systems along several dimensions. The main dimensions were the set of considered visualizations, the suggestion method, the utility/objective functions, the layout, and the user interface. We conclude by highlighting the main achievements in this domain and by proposing perspectives.

Mots clés: Automatic Visualization; Dashboard recommendation; Multiple View Interfaces

Domaines: Informatique [cs]

Praveen Soni, Cyril de Runz, Fatma Bouali, Gilles Venturini. A survey on automatic dashboard recommendation systems. Visual Informatics, inPress, ⟨10.1016/j.visinf.2024.01.002⟩. ⟨hal-04403155⟩