July 1, 2022
Smartwatches are becoming increasingly smart in that they capture and relay a variety of data to wearers. However, it is difficult to find empirical advice on how to represent and make this data understandable to wearers. My research intends to understand how to design and use micro-visualizations for pervasive and mobile data exploration. In this talk, I will start by presenting findings from an ideation workshop that can help us to imagine future smartwatch visualization in the context of sightseeing. I will then talk about currently practiced data types and representations on smartwatch faces and untapped opportunities for smartwatch visualization. Also, I will show you design dimensions for smartwatch data representations which can help designers and experts to think of intuitive designs for smartwatch data. Finally, I will present my work on the readability of micro-visualizations on fitness trackers (e.g., smartwatches, fitness bands), considering the impact of size and aspect ratio in sleep tracking data. In summary, I will give an overview of my past work in fitness trackers' visualizations and share my insights on how they can help to enable a more pervasive use of visual data representation.
is currently a third-year Ph.D. student at the AVIZ
research team, INRIA and Université Paris-Saclay
, supervised by Dr. Petra Isenberg
. His research is focused on micro visualizations or the challenge of creating and reading small-scale visualizations for fitness trackers. He holds a master's degree in human-computer interaction from the Université Paris-Saclay, France. His research is supported by the Agence Nationale de la Recherche (ANR-18-CE92-0059-01).