A data physicalization pipeline enhanced with augmented reality

Official URL: http://risc01.sabanciuniv.edu/record=b1653900 (Table of Contents)

Data visualization is an indispensable methodology for interpretation of information. The key purpose of traditional data visualization methods is to convert observed records into meaningful visuals to ease the cognition of trends. This virtual, passive technique on a display o↵ers flexibility to create wide range of di↵erent visualization designs utilizing, however, only visual perception. Physical visualizations, on the other hand, enable sensations other than mere visual input, thus enhancing the experience and the impact. Although physical visualizations have some certain proven benefits over traditional visualizations, generating them is not as e↵ective and quick. In that regard, need of physical models shaped around well-defined design rules are a prerequisite. Moreover, digital construction of the designed solid models for manufacturing is the next step to be achieved. However, even for a small set of data, constructing several models becomes a discouraging and highly time consuming task. This main problem is covered in this thesis by the implementation of an authoring tool. The introduced tool alleviates the burden of physical model generation process. Predefined models under design rules are generated in accordance with both the data input and adjusted parameters by the user. Utilization of digital fabrication techniques that are nowadays becoming widespread and easy to access is the key for physicalization. In order for an ”Overview first, detail on demand” approach, an augmented reality tool is also introduced to work with designed models so as to retain the physicality while presenting more detailed information such as exact values of data points along with augmented graphics if desired.