Position Papers

The following position papers were accepted and wiil be presented at the workshop. The authors retain the copyright for all work posted here—please contact them directly for reproduction permissions.

Boxcars on Potatoes: Exploring the Design Language for Tangible Visualizations of Scalar Data Fields on 3D Surfaces
Bridger Herman and Daniel F. Keefe
Full text available: PDF
We present a design-based exploration of the potential to reinterpret glyph-based visualization of scalar fields on 3D surfaces, a traditional scientific visualization technique, as a data physicalization technique. Even with the best virtual reality displays, users often struggle to correctly interpret spatial relationships in 3D datasets; thus, we are motivated to understand the extent to which traditional scientific visualization methods can translate to physical media where users may simultaneously leverage their visual systems and tactile senses to, in theory, better understand and connect with the data of interest. This pictorial traces the process of our design for a specific user study experiment: (1) inspiration, (2) exploring the data physicalization design space, (3) prototyping with 3D printing, (4) applying the techniques to different synthetic datasets. We call our most recent and compelling visual/tactile design boxcars on potatoes, and the next step in the research is to run a user-based evaluation to elucidate how this design compares to several of the others pictured here.

A Classification Schema for Data Physicalizations and a Carbon Footprint Physicalization
Steffen Haesler, Jörn Hurtienne, Franz Ertle and Patricia Theile
Full text available: PDF
Based on previous literature, we propose a classification schema for data physicalizations and apply it in a case study to inspire the design of a carbon footprint machine. We present a high-fidelity interactive prototype that interactively physicalizes a user’s carbon footprint with a balloon-based artifact. We describe the challenge to make different carbon footprints easily comparable. The prototype was shown and evaluated in a university-wide exhibition and the user study revealed the strength of the mapping. This case study shows that beyond the classification schema, issues of variable encoding remain significant and aesthetic, social and contextual factors need to be considered when aiming for a design language of data physicalizations.

Towards a Framework for Dynamic Data Physicalisation
Beat Signer, Payam Ebrahimi, Timothy J. Curtin and Ahmed K.A. Abdullah
Full text available: PDF
Abstract—Advanced data visualisation techniques enable the exploration and analysis of large datasets. Recently, there is the emerging field of data physicalisation, where data is represented in physical space (e.g. via physical models) and can no longer only be explored visually, but also by making use of other senses such as touch. Most existing data physicalisation solutions are static and cannot be dynamically updated based on a user’s  interaction. Our goal is to develop a framework for new forms of dynamic data physicalisation in order to support an interactive exploration and analysis of datasets. Based on a study of the design space for dynamic data physicalisation, we are therefore working on a grammar for representing the fundamental physical operations and interactions that can be applied to the underlying data. Our envisioned extensible data physicalisation framework will enable the rapid prototyping of dynamic data physicalisations and thereby support researchers who want to experiment with new combinations of physical variables or output devices for dynamic data physicalisation as well as designers and application developers who are interested in the development of innovative dynamic data physicalisation solutions.

Embedded Personal Physicalizations
Mathieu Le Goc, Charles Perin, and Sean Follmer
Full text available: PDF
With the emergence of quantified-self, smart devices, Internet of Things and ubiquitous robotics, we envision new opportunities to create dynamic embedded physicalizations. In particular, we see new challenges arising in the context of personal and casual physicalizations at home. In this paper, we discuss the research directions and potential benefits of dynamic embedded physicalizations in the residential context, or Embedded Personal Physicalizations.

ORBACLES
Daniel F. Keefe, Ross Altheimer, Andrea J. Johnson, Mahdieh Mahmoudi, Patrick Moe, Maura Rockcastle, Marc Swackhamer and Aaron Wittkamper
Full text available: PDF
Orbacles is a triad of spherical environments that connect visitors to the reality of climate change through the story of birds in Minnesota and the language of our senses. As both a record and a speculation about the future through the end of the century, Orbacles communicates the current and anticipated shift of birds due to species loss and migration related to climate effects.

Encoding Data through Experiential Material Properties
Lora Oehlberg and Wesley Willett
Full text available: PDF
When discussing encodings for physicalizations, visualization researchers often focus on physical properties that are persistent and clearly visible with our eyes (and occasionally reinforced through touch) including color, size, and texture. However, there are many other physical properties that impact how we perceive and interact with those materials. In this position paper, we explore opportunities for more unusual experiential properties including tactile, ephemeral, and dynamic material characteristics. We also provide both real-world and conceptual examples that illustrate how these properties can be used to encode data. Finally, we identify three opportunities for new research contributions related to experiential material properties: new  types of physicalizations, new audiences for physicalizations, and new authoring tools.

Variables for Data Physicalization Units
Simon Stusak, Andreas Butz, and Aurélien Tabard
Full text available: PDF
We propose a set of variables for unit-based data physicalisation. Variables are symbolic properties that can be applied to data in order to represent information. Unit based data physicalizations are physical representations of data made out of multiple pieces (units), with each units corresponding to a data point. We propose 14 variables grouped in four categories, but focus on nine that are novel and most relevant for data physicalizations: geometric variables (position, orientation, global shape, exact shape), color variables (hue, saturation, luminance, optics), tactile variables (roughness, lay, temperature, compliance), and kinesthetic variables (slipperiness, weight). This set of variables offers a better grasp of the design space, and provides building blocks for the systematic construction of data physicalizations.

Possibilities of Human Data Embodiment: 100% City
Jörn Hurtienne
Full text available: PDF
In this paper we explore the use of living humans to represent statistical data as a new form of data physicalisation. In a case study, we analyse data representation formats and consider strategies for how human data embodiment can be used to “give statistics a face”. This is done at the example of 100% City, a performance directed by Rimini Protokoll, a German documentary theatre group. In this, 100 people statistically represent the population of a whole city and answer questions about their demographic status, politics, work, family, health and more. The results encourage further research into what we might call Computer Augmented Human Data Embodiment (CAHDE). It may also inspire traditional data physicalisations in how data about humans can be made more personally relevant to their audiences.

Haptics as a sustainable proxy for exploring design variables for data physicalization
Christian Frisson, Marcelo M. Wanderley, Wesley Willett and Sheelagh Carpendale
Full text available: PDF
This workshop paper aims at bringing a new perspective to data physicalization by investigating how haptics can help designers explore
design variables. We first introduce data physicalization and physical variables. We then delineate challenges in data physicalization: enabling granular data manipulation, reducing ideation waste. We cover emerging trends in haptics: accessible and modular devices; computable soft haptics materials; usable software frameworks. We propose opportunities in haptics for data physicalization: exploring physical data mappings with haptics; reducing ideation waste by haptic preprint.