Shaping Plant-Like Shape-Changing Interfaces as Vertical Charts: Maximizing Readability, Aesthetics, and Naturalness
Elodie Bouzekri, Guillaume Riviere
TLDR
This paper explores and evaluates plant-like shape-changing interfaces as vertical charts for environmental data, optimizing readability, aesthetics, and naturalness.
Key contributions
- Explores design space for plant-like shape-changing vertical charts.
- Compares four prototypes for conveying renewable energy forecasts.
- Evaluates physical charts vs. graphical for readability and aesthetics.
- Finds physical charts worthwhile, offering naturalness and public installability.
Why it matters
This paper addresses the growing need for effective environmental data visualization to encourage eco-friendly lifestyles. It proposes novel physical, plant-like charts that enhance naturalness and can be publicly installed without explanations, offering a more engaging way to communicate sustainability.
Original Abstract
Conveying environmental data has grown interest in encouraging the adoption of eco-friendly lifestyles through data-driven strategies. This scope appeals to data visualizations representing the environmental purpose. For example, previous work has already proposed nature-inspired counters, gauges, and bitmaps, but data series remains to be explored. Therefore, could we design and implement effective plant-like charts? This paper brings answers through a research-through-design approach that explores a design space to maximize readability and aesthetics. It then compares four prototypes of charts over modality and material dimensions by asking users about scenarios involving renewable energy forecasts. The results examine whether implementing physical charts is worth it instead of graphical charts and the advantages of using meaningful materials that evocate sustainability and enhance naturalness. The results also reexamine, with physical charts, the previous results on graphical infographics of slightly lower clarity and readability but higher aesthetics of embellishment. In addition, learnability is examined for encoding rates through folded shapes. This paper shows that physical plant-like charts are worthwhile because of promising performance and best-of-breed naturalness when materials allow low-tech aspects' perception and because being installable in public places without explanations if folded shapes encode rates ranging from 0 to a maximum value.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.