Law, MatthewRollins, SamiBanerjee, NilanjanJoshi, AlarkE. Bertini and J. Kennedy and E. Puppo2015-05-242015-05-242015https://doi.org/10.2312/eurovisshort.20151131Motivated by both cost savings and environmental concerns, managing energy in the home has become increasingly important. Though both user-driven and automated solutions have shown promise, a deeper understanding of the characteristics of energy usage behavior is necessary to inform the design of such systems. In this work, we present the results of a study that explores the insights and characteristics participants are able to derive using two well-known visualization techniques for time series data. We find that participants are able to extract a variety of relevant features and explain general and anomalous patterns of behavior. We also find that the preferred visualization is both user- and task-dependent. These findings may be used as the basis for new systems for home energy management.H.1.2 [Information Systems]User/Machine SystemsHuman Information Processing10.2312/eurovisshort.2015113191-95