Abstract
This article explores haptic data representation of people’s daily activities. The haptic data representation employs haptic properties of artifacts to represent data. However, the data types represented by haptic properties appear to be constrained, with frequency and average value accounting for the majority. Many other valuable types of information, such as variance, trend, and sample size, are under-represented. These data types are important for people to make decisions and reflect on their activities. To explore the potentials of expressing multiple data types through various haptic properties of artifacts, a user study was conducted to investigate people’s mental mappings of haptic properties to numerous aspects of data. The results suggested a common pattern of people’s preferences for interpreting haptic properties, which supported specific mappings between haptic properties and data types. A design workshop was then conducted to demonstrate the feasibility and benefits of holistically representing multiple data types of people’s activities.
Keywords
empirical studies; haptic; haptic properties; mappings
DOI
https://doi.org/10.21606/iasdr.2023.145
Citation
Wei, X., Siyuan, L., Hao, J., Shengdong, Z.,and Lingyun, S.(2023) Play with data: Using haptic properties of artifacts to augment data representation, in De Sainz Molestina, D., Galluzzo, L., Rizzo, F., Spallazzo, D. (eds.), IASDR 2023: Life-Changing Design, 9-13 October, Milan, Italy. https://doi.org/10.21606/iasdr.2023.145
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
fullpapers
Included in
Play with data: Using haptic properties of artifacts to augment data representation
This article explores haptic data representation of people’s daily activities. The haptic data representation employs haptic properties of artifacts to represent data. However, the data types represented by haptic properties appear to be constrained, with frequency and average value accounting for the majority. Many other valuable types of information, such as variance, trend, and sample size, are under-represented. These data types are important for people to make decisions and reflect on their activities. To explore the potentials of expressing multiple data types through various haptic properties of artifacts, a user study was conducted to investigate people’s mental mappings of haptic properties to numerous aspects of data. The results suggested a common pattern of people’s preferences for interpreting haptic properties, which supported specific mappings between haptic properties and data types. A design workshop was then conducted to demonstrate the feasibility and benefits of holistically representing multiple data types of people’s activities.