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.

翻译：数据物理化关注如何通过数据的物理表示来支持沟通、学习与问题解决。作为一个新兴领域，数据物理化研究需要概念基础来支撑对新型数据物理表示的设计与思考。然而，目前尚不明确以下三点：(i) 在构建物理化过程中，设计者可使用哪些编码变量；(ii) 哪些评估标准具有实用价值；(iii) 可采用哪些方法评估物理化效果。本文通过叙述性综述与系统性综述回答上述三个问题。叙述性综述借鉴信息可视化、人机交互与地图学领域文献，提供数据编码变量的整体视角；系统性综述则深入考察可用于评估数据物理化的评估标准与方法。两项综述共同为对设计及研究数据物理化感兴趣的研究者与设计师提供概念框架。