An empirical investigation of domestic energy data visualizations

• Published in: International journal of human-computer studies Vol. 152; p. 102660
• Main Authors: Herrmann, Melanie R., Brumby, Duncan P., Cheng, Longmin, Gilbert, Xavier M.P., Oreszczyn, Tadj
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2021
• Subjects: Disaggregation; Graphical literacy; Information visualization; Smart metering; Time series data; Disaggregation; Information visualization; Smart metering; Graphical literacy; Time series data
• ISSN: 1071-5819; 1095-9300
• DOI: 10.1016/j.ijhcs.2021.102660

•Investigates how the choice of information visualization influences people in making sense of data for domestic electricity consumption.•Results of experiment suggest that by using an area-based data visualization, people can gain a more accurate understanding of how much electricity different domestic appliances use.•These results are important because the information display of current smart meters tend to use time-series data visualization, which we show to be less effective for enabling users to develop an understanding of domestic electricity consumption. Which device in your home uses the most electricity? Many people have a poor understanding of their domestic energy consumption. In this paper, we evaluated three data visualizations used to deliver feedback. These were: (1) an aggregated line graph – showing changes in total electricity consumption over time, (2) a disaggregated line graph – showing changes in electricity consumed over time but separated out at the appliance-level, and (3) an area-based visualization – showing the cumulative energy consumed by different appliances over a given time period. In an experiment, 65 participants used one of these three visualizations to make sense of the same pattern of domestic electricity data. Participants who used the area-based visualization gained a more accurate understanding of how much electricity different domestic appliances were using compared to participants who were shown time series data. These results suggest that the choice of data visualization will impact people's understanding from smart metering systems, and that appliance-wise disaggregation offers the most promising approach for visualizing domestic electricity consumption data.