An empirical investigation of domestic energy data visualizations

[1]  Cleotilde Gonzalez,et al.  The Relationships between Cognitive Ability and Dynamic Decision Making. , 2005 .

[2]  M. Sheelagh T. Carpendale,et al.  Personal Visualization and Personal Visual Analytics , 2015, IEEE Transactions on Visualization and Computer Graphics.

[3]  W. G. V. Balchin,et al.  GRAPHICACY SHOULD BE THE FOURTH ACE IN THE PACK , 1966 .

[4]  Ian Walker,et al.  A laboratory test of the efficacy of energy display interface design , 2012 .

[5]  Eric C. Larson,et al.  Disaggregated End-Use Energy Sensing for the Smart Grid , 2011, IEEE Pervasive Computing.

[6]  Yvonne Rogers,et al.  Contrasting lab-based and in-the-wild studies for evaluating multi-user technologies , 2013 .

[7]  Yolande A. A. Strengers,et al.  Designing eco-feedback systems for everyday life , 2011, CHI.

[8]  Jeffrey Heer,et al.  Crowdsourcing graphical perception: using mechanical turk to assess visualization design , 2010, CHI.

[9]  Julian Padget,et al.  'just enough' sensing to ENLITEN: a preliminary demonstration of sensing strategy for the 'energy literacy through an intelligent home energy advisor' (ENLITEN) project , 2013, e-Energy '13.

[10]  Philip M. Johnson,et al.  Energy Feedback for Smart Grid Consumers: Lessons Learned from the Kukui Cup , 2013 .

[11]  Steven Pinker,et al.  A theory of graph comprehension. , 1990 .

[12]  W. Kempton,et al.  The consumer's energy analysis environment , 1994 .

[13]  Willett Kempton,et al.  Folk quantification of energy , 1982 .

[14]  Mario Berges,et al.  Unsupervised disaggregation of appliances using aggregated consumption data , 2011 .

[15]  Peter C.-H. Cheng,et al.  Unlocking conceptual learning in mathematics and science with effective representational systems , 1999, Comput. Educ..

[16]  Yoram Chisik,et al.  An Image of Electricity: Towards an Understanding of How People Perceive Electricity , 2011, INTERACT.

[17]  Johnny Rodgers,et al.  Exploring Ambient and Artistic Visualization for Residential Energy Use Feedback , 2011, IEEE Transactions on Visualization and Computer Graphics.

[18]  Mark W. Newman,et al.  Making sustainability sustainable: challenges in the design of eco-interaction technologies , 2014, CHI.

[19]  Niklas Elmqvist,et al.  Graphical Perception of Multiple Time Series , 2010, IEEE Transactions on Visualization and Computer Graphics.

[20]  M. Dekay,et al.  Public perceptions of energy consumption and savings , 2010, Proceedings of the National Academy of Sciences.

[21]  Haimonti Dutta,et al.  NILMTK: an open source toolkit for non-intrusive load monitoring , 2014, e-Energy.

[22]  Sarvapali D. Ramchurn,et al.  Understanding domestic energy consumption through interactive visualisation: a field study , 2012, UbiComp.

[23]  Paul A. Cairns,et al.  Wattsup?: motivating reductions in domestic energy consumption using social networks , 2010, NordiCHI.

[24]  G. Soutar,et al.  Energy saving behaviours: Development of a practice-based model , 2013 .

[25]  Steven Franconeri,et al.  ISOTYPE Visualization: Working Memory, Performance, and Engagement with Pictographs , 2015, CHI.

[26]  Sarah C. Darby,et al.  Making it Obvious: Designing Feedback into Energy Consumption , 2001 .

[27]  Tadj Oreszczyn,et al.  Watts your usage? A field study of householders’ literacy for residential electricity data , 2018 .

[28]  Rebecca E. Grinter,et al.  Getting to green: understanding resource consumption in the home , 2008, UbiComp.

[29]  Jack Kelly,et al.  Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature , 2016, ArXiv.

[30]  Sung-Hee Kim,et al.  How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking , 2016, IEEE Transactions on Visualization and Computer Graphics.

[31]  Federico Cabitza,et al.  Static and interactive infographics in daily tasks: A value-in-use and quality of interaction user study , 2017, Comput. Hum. Behav..

[32]  W. Cleveland,et al.  Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods , 1984 .

[33]  Corinna Fischer Feedback on household electricity consumption: a tool for saving energy? , 2008 .

[34]  Katharina Reinecke,et al.  How WEIRD is HCI?: Extending HCI Principles to other Countries and Cultures , 2015, CHI Extended Abstracts.

[35]  Lt Lorna McCalley,et al.  Energy conservation through product-integrated feedback: The roles of goal-setting and social orientation , 2002 .

[36]  Jan DeWaters,et al.  Energy literacy of secondary students in New York State (USA): A measure of knowledge, affect, and behavior , 2011 .

[37]  Jing Liao,et al.  Measuring the energy intensity of domestic activities from smart meter data , 2016 .

[38]  K. Armel,et al.  Is disaggregation the holy grail of energy efficiency? The case of electricity , 2013 .

[39]  Gabrielle Wong-Parodi,et al.  Creating an in-home display: Experimental evidence and guidelines for design , 2013 .

[40]  Filipe Quintal,et al.  What-a-Watt: exploring electricity production literacy through a long term eco-feedback study , 2015, 2015 Sustainable Internet and ICT for Sustainability (SustainIT).

[41]  Barbara Mettler-Meibom,et al.  Informationsstand und Einstellung als Verhaltensregulative , 1982 .

[42]  Tom Hargreaves,et al.  Practice-ing behaviour change: Applying social practice theory to pro-environmental behaviour change , 2011 .

[43]  Jean-Daniel Fekete,et al.  A Principled Way of Assessing Visualization Literacy , 2014, IEEE Transactions on Visualization and Computer Graphics.

[44]  Pedro Álvarez,et al.  ACTITUDES AMBIENTALES Y CONDUCTAS SOSTENIBLES. IMPLICACIONES PARA LA EDUCACIÓN AMBIENTAL , 2009 .

[45]  Tadj Oreszczyn,et al.  Does data visualization affect users’ understanding of electricity consumption? , 2018 .

[46]  M. Galesic,et al.  Graph Literacy , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.

[47]  Tom Hargreaves Beyond energy feedback , 2018 .

[48]  Jack Kelly,et al.  The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes , 2014, Scientific Data.