Abstract:
A visualisation is subjectively interpreted by the user depending on past experiences, education, gender, culture, situation, and individual limitations, abilities, and requirements. For instance, colour-deficient viewers are limited in interpreting colour pictures; a person with deficient fine motor skills will have problems accurately pointing at small objects on the screen. In order to create a user model, the system needs to learn facts about the user. Most of these facts can be extracted from observing the user perform special tasks. Through extensive study, we are building user models to understand how non-experts and experts perceive visualisations in their daily life. The findings from this study will help us come up with guidelines for designing visualisations that people can understand and take decisions.

Publications:

• Jena, A., Engelke, U., Dwyer, T., Raiamanickam, V., & Paris, C. (2020, June). Uncertainty Visualisation: An Interactive Visual Survey. In 2020 IEEE Pacific Visualization Symposium (PacificVis) (pp. 201-205). IEEE.

• Collins, C., Andrienko, N., Schreck, T., Yang, J., Choo, J., Engelke, U., ... & Dwyer, T. (2018). Guidance in the human–machine analytics process. Visual Informatics, 2(3), 166-180.