Data Edibilization: Representing Data with Food

@inproceedings{Wang2016DataER,
  title={Data Edibilization: Representing Data with Food},
  author={Yun Wang and Xiaojuan Ma and Qiong Luo and Huamin Qu},
  booktitle={CHI Extended Abstracts},
  year={2016}
}
Data communication is critical in data science. We propose data edibilization, i.e., encoding data with edible materials, as a novel approach to leverage multiple sensory channels to convey data stories. We conduct a preliminary data tasting workshop to explore how users interact with and interpret data edibilization. Based on the participants' feedback, we summarize the advantages of edibilization in terms of attractiveness, richness, memorability, affectiveness, and sociability. We also… CONTINUE READING
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