Gao, Lei;
Irani, Pourang;
Subramanian, Sriram;
Prabhakar, Gowdham;
Martinez Plasencia, Diego;
Hirayama, Ryuji;
(2023)
DataLev: Mid-air Data Physicalisation Using Acoustic Levitation.
In:
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.
Association for Computing Machinery (ACM): Stratford, ON, Canada.
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Abstract
Data physicalisation is a technique that encodes data through the geometric and material properties of an artefact, allowing users to engage with data in a more immersive and multi-sensory way. However, current methods of data physicalisation are limited in terms of their reconfgurability and the types of materials that can be used. Acoustophoresis—a method of suspending and manipulating materials using sound waves—ofers a promising solution to these challenges. In this paper, we present DataLev, a design space and platform for creating reconfgurable, multimodal data physicalisations with enriched materiality using acoustophoresis. We demonstrate the capabilities of DataLev through eight examples and evaluate its performance in terms of reconfgurability and materiality. Our work ofers a new approach to data physicalisation, enabling designers to create more dynamic, engaging, and expressive artefacts.
| Type: | Proceedings paper |
|---|---|
| Title: | DataLev: Mid-air Data Physicalisation Using Acoustic Levitation |
| Event: | CHI '23: CHI Conference on Human Factors in Computing Systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3544548.3581016 |
| Publisher version: | https://doi.org/10.1145/3544548.3581016 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10169092 |
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