Data visualizations are visual representations of data, perceived via the sense of human vision. At Data Sensification & Human Data Interaction lab, we explore means to extend this to other human senses, i.e., we are interested in creating data representations that can be touched, smelled, tasted, or heard (in addition to be viewed). By data sensification, we aim to improve overall human data interaction and experiences. Our research especially focuses on human aspects such as perception, memorability, cognitive load, motivation, mood, and feelings. Thus, we are exploring ways to:
- improve perception and interpretation of data
- create immersive and embodied data experiences
- make data memorable
- reduce cognitive load
- create data-driven behavior stimulation
- improve accessibility
Our current research topics center around:
- Data physicalization and tangible interactions with data
- Beyond-desktop data representations
- Post-WIMP (Windows, Icon, Menue, Pointer), beyond mouse-keyboard-touch interactions with data
- Data as everyday objects/ Smart data objects
- Multisensory data representation and perception
- Sensing and actuation as material for representing data
Our Projects:
- EmoClock: Realtime physicalization of human emotions
- Bloomie: Motivating older adults to be more physically active
- Temperature and Vibration to represent sustainable energy data
- Interact with planet data in an interactive way (LEGO concepts for data physicalization): https://youtu.be/2A7bITAQyhA
- Refugee flow: https://www.youtube.com/watch?v=ySdvdfwa7O0
- Corel bleaching: https://youtu.be/PfqhZxZtfqY
- Drugs and human body: https://www.youtube.com/watch?v=gmuSeItS0HQ
- Volcano- Jobs and Stress: https://www.youtube.com/watch?v=Frg6jkmdWLQ
Publications
- Peeters, Dennis, et al. "EmoClock: Communicating Real-Time Emotional States Through Data Physicalizations." IFIP Conference on Human-Computer Interaction. Cham: Springer Nature Switzerland, 2023.
- van Loenhout, R., Ranasinghe, C., Degbelo, A., & Bouali, N. (2022, April). Physicalizing sustainable development goals data: an example with SDG 7 (affordable and clean energy). In CHI Conference on Human Factors in Computing Systems Extended Abstracts (pp. 1-7).
- Ranasinghe, C., & Degbelo, A. (2023). Encoding Variables, Evaluation Criteria and Evaluation Methods for Data Physicalizations: A Review. arXiv preprint arXiv:2305.03476.
- Ranasinghe, C., & Bults, R. (2023). Position Paper: Physicalization of Human Body Sensing Data., CHI 2023 Workshop on Data Physicalization across Domains.