ENERGY/Vis Project

Commons Game

Table of Contents

  1. About ENERGY/Vis
  2. Product and Contribution
  3. Data
  4. Our Experiments
  5. Perception and Interpretation Experiments
  6. Behavioural Game Studies Focused on Action
  7. Lab Studies with Eye Tracking
  8. Publications
  9. Our Researchers

About ENERGY/Vis

Social Perceptions in Home Energy Graphs

Our information is increasingly data based and our decisions are increasingly guided by data graphs, charts and visualizations. Yet, the dominantly individualist data presentation perspectives utilized in current feedback systems have failed to leverage social behavioral theories to design technologically mediated feedback that could enhance individuals' awareness of and their willingness to cooperate with the digitally interconnected others.

The ENERGY/Vis Project was created to gain deeper insight into how the visual structure of a data graph affects the interpretation and comprehension of the data the chart represents and how they might nudge us to more cooperative choices. Little research has examined the role data visualization design plays in shaping behavior in the context of collective action (e.g., recycling, energy conservation, public protest, juries or organizational committees) that require cooperation and pooling of efforts of individual members, often on a voluntary basis. In such dilemmas, everybody is better off if individuals align with the group goal; however, these tasks typically fail because many do not align with the group’s goal. In addition to visual encoding patterns to enhance individuals' social awareness and cooperation, this project will offer resources for new cognitive and perceptual experiments.

Products and Contributions:

A. One (1) home energy monitoring app. Product 1 - demo app

B. One (1) set of unifying design patterns. Product 2 - gestalt placeholder

C. One (1) new infovis game model. Product 3 - vis game

D. 10s of new D3.js graphs. Product 4 - D3 graphs

E. 10s of behavioral games. Product 5 - many games

F. 10s of lab studies. Product 6 - lab study

G. 100s of on Amazon Mechanical Turk workers. Product 7 - Amazon Turk


A. 100s of annotations. Product 8 - annotations

B. 100s of perceived group unity measurements. Product 9 - unity measurements

C. 1,000s of graph descriptions. Product 10 - descriptions

D.1,000s of graph based decisions Product 11 - decisions

E. 10,000 of eye fixations Product 12 - eyetracking data

F. 10,000s of code lines( see our Github) Product 13 - code

Request our data: Email

Our Experiments

Research has shown that data based feedback has the potential to make people more aware and cognizant of their synergy decisions. What is lacking is the consideration of the subtle ways in which design details of data based charts frame how people perceive, understand and act in response to the feedback charts.

We extend visual perception theory by borrowing from group identity literature, which suggests that perceiving a unified group is required for group alignment and continued commitment. So, we hypothesize that seeing and identifying with a perceivably unified group can sustain users' energy conservation efforts. We use social computational methods to study the effects of visual graph structures and motion effects on graph perceptions, interpretations and user actions and consolidate a set of design patterns.

Perception and Interpretation Experiments.

We marry theories of visual perception and group identity to deliver theory driven chart designs that support collective awareness. Our perceptual experiments explore how these visual graph structures increase the perception of group unity.

Explore our Gestalt Graphs

Behavioural Game Studies Focused on Action.

We build on existing behavioral game literature and propose a new visualization oriented game framework. We use the behavioral game to explore how the visual graph structures nudge individuals to more cooperative behaviors.

Demo our behavioral game

Lab Studies with Eye Tracking.

We seek to better understand the link between perceiveinng a data visualization and how interpretinng the unnderlying data is mediated by visual graph structures.

Explore our Motion Graphs


When using our work please cite our papers


A Framework for Eco-Feedback Design For Home Energy Interactions

Marlen Promann, and Sabine Brunswicker (2018) ACM Transactions on Computer-Human Interaction, (forthcoming).

Promann, M., & Brunswicker, S. (2017). AIS Electronic Library (AISeL) - AMCIS 2017 Proceedings: Affordances Of Eco-Feedback Design in Home Energy Context.


1. The Effect of Enclosure in Group Charts on Perceived Unity.

Marlen Promann, and Sabine Brunswicker (forthcoming) CSCW, New Jersey, NY, USA, November 3-7

2. The Effect of Proximal Data Structure on Perceived Group Unity

Marlen Promann, and Sabine Brunswicker (forthcoming) IEEEVis VAST, Berlin, Germany, October.

3. Affordances of Eco-Feedback Design in Home Energy Context

Marlen Promann, and Sabine Brunswicker (2017) AMCIS, Boston, MA, USA, 10-12 August.

Say, Hi!

Please reach out to us with feedback, suggestions, data and collaboration requests.

We love this inspiring track of civic design work and look forward to hearing from you.

Our Researchers

Dr. Sabine Brunswicker - Associate Professor, Director Research Center for Digital Innovation (RCODI) | Profile

Marlen Promman - PhD Design Researcher, RCODI Research Fellow | Profile

Jesus Enrique

Aldana Sigona Game Developer, RCODI Research Fellow | aldana.sigona(at)gmail(dot)com

Daniel Fernando

Santos Bustos - Software Engineer, RCODI Research Fellow | dfsantosbu(at)unal(dot)edu(dot)co

Note: For graph and game codes, please visit out GitHub repository.


This work has been supported in part by the National Science Foundation (NSF) under Smart and Connected Communities grant, Office of the Executive Vice President for Research at Purdue University, and Purdue Discovery Park’s Big Idea Challenge awards. This work has also been made possible by the critical feedback of RCODI team at large.


My research interests include distributed digital innovation, AI, crowdsourcing, and open source software