Encoding Variables, Evaluation Criteria and Evaluation Methods for Data Physicalizations: A Review
May 05, 2023 ยท The Cartographer ยท ๐ Multimodal Technologies and Interaction
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"Title-pattern auto-detect: Encoding Variables, Evaluation Criteria and Evaluation Methods for Data Physicalizations: A Review"
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Authors
Champika Ranasinghe, Auriol Degbelo
arXiv ID
2305.03476
Category
cs.HC: Human-Computer Interaction
Citations
14
Venue
Multimodal Technologies and Interaction
Last Checked
3 days ago
Abstract
Data Physicalization focuses on understanding how physical representations of data can support communication, learning and problem-solving. As an emerging area, Data Physicalization research needs conceptual foundations to support thinking about and designing new physical representations of data. Yet, it remains unclear at the moment (i) what encoding variables are at the designer's disposal during the creation of physicalizations, (ii) what evaluation criteria could be useful, and (iii) what methods can be used to evaluate physicalizations. This article addresses these three questions through a narrative review and a systematic review. The narrative review draws on the literature from Information Visualization, HCI and Cartography to provide a holistic view of encoding variables for data. The systematic review looks closely into the evaluation criteria and methods that can be used to evaluate data physicalizations. Both reviews offer a conceptual framework for researchers and designers interested in designing and studying data physicalizations.
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