Interactive visual study for residential energy consumption data
<p>Interactive data visualization tools for residential energy data are instrumental indicators for analyzing end user behavior. These visualizations can be used as continuous home feedback systems and can be accessed from mobile devices using touch-based applications. Visualizations have to b...
محفوظ في:
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2022
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| الموضوعات: | |
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إضافة وسم
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| _version_ | 1864513536510656512 |
|---|---|
| author | Ayman Al-Kababji (16870080) |
| author2 | Abdullah Alsalemi (6951986) Yassine Himeur (14158821) Rachael Fernandez (17545686) Faycal Bensaali (12427401) Abbes Amira (6952001) Noora Fetais (16084859) |
| author2_role | author author author author author author |
| author_facet | Ayman Al-Kababji (16870080) Abdullah Alsalemi (6951986) Yassine Himeur (14158821) Rachael Fernandez (17545686) Faycal Bensaali (12427401) Abbes Amira (6952001) Noora Fetais (16084859) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ayman Al-Kababji (16870080) Abdullah Alsalemi (6951986) Yassine Himeur (14158821) Rachael Fernandez (17545686) Faycal Bensaali (12427401) Abbes Amira (6952001) Noora Fetais (16084859) |
| dc.date.none.fl_str_mv | 2022-09-15T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.jclepro.2022.132841 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Interactive_visual_study_for_residential_energy_consumption_data/24720372 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Information and computing sciences Data management and data science Human-centred computing Data and knowledge visualization Energy-aware systems Energy efficiency Mobile applications Evaluation studies Visualizations comparison |
| dc.title.none.fl_str_mv | Interactive visual study for residential energy consumption data |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>Interactive data visualization tools for residential energy data are instrumental indicators for analyzing end user behavior. These visualizations can be used as continuous home feedback systems and can be accessed from mobile devices using touch-based applications. Visualizations have to be carefully selected in order for them to partake in the behavioral transformation that end users are encouraged to adopt. In this paper, six energy data visualizations are evaluated in a randomized controlled trial fashion to determine the optimal data visualization tool. Conventional visualizations, namely bar, line, and stacked area, are compared against enhanced charts, namely spiral, heatmap, and stacked bar, in terms of effectiveness, aesthetic, understandability, and three analysis questions. The study is conducted through a questionnaire in a mobile application. The application, created through React Native, is circulated to participants in multiple countries, collecting 133 responses. From the received responses, conventional plots scored higher understandability (by 22.74%), effectiveness (by 13.44%), and aesthetic (by 10.54%) when compared with the enhanced visualizations. On the flipside, enhanced plots generated higher correct analysis questions’ responses by 8% compared to the conventional counterparts. From the 133 collected responses, and after applying the unpaired t-test, conventional energy data visualization plots are considered superior in terms of understandability, effectiveness, and aesthetic.</p><h2>Other Information</h2> <p> Published in: Journal of Cleaner Production<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jclepro.2022.132841" target="_blank">https://dx.doi.org/10.1016/j.jclepro.2022.132841</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7663d9dae359f876ee4d3e79287f70ce |
| identifier_str_mv | 10.1016/j.jclepro.2022.132841 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24720372 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Interactive visual study for residential energy consumption dataAyman Al-Kababji (16870080)Abdullah Alsalemi (6951986)Yassine Himeur (14158821)Rachael Fernandez (17545686)Faycal Bensaali (12427401)Abbes Amira (6952001)Noora Fetais (16084859)EngineeringElectrical engineeringInformation and computing sciencesData management and data scienceHuman-centred computingData and knowledge visualizationEnergy-aware systemsEnergy efficiencyMobile applicationsEvaluation studiesVisualizations comparison<p>Interactive data visualization tools for residential energy data are instrumental indicators for analyzing end user behavior. These visualizations can be used as continuous home feedback systems and can be accessed from mobile devices using touch-based applications. Visualizations have to be carefully selected in order for them to partake in the behavioral transformation that end users are encouraged to adopt. In this paper, six energy data visualizations are evaluated in a randomized controlled trial fashion to determine the optimal data visualization tool. Conventional visualizations, namely bar, line, and stacked area, are compared against enhanced charts, namely spiral, heatmap, and stacked bar, in terms of effectiveness, aesthetic, understandability, and three analysis questions. The study is conducted through a questionnaire in a mobile application. The application, created through React Native, is circulated to participants in multiple countries, collecting 133 responses. From the received responses, conventional plots scored higher understandability (by 22.74%), effectiveness (by 13.44%), and aesthetic (by 10.54%) when compared with the enhanced visualizations. On the flipside, enhanced plots generated higher correct analysis questions’ responses by 8% compared to the conventional counterparts. From the 133 collected responses, and after applying the unpaired t-test, conventional energy data visualization plots are considered superior in terms of understandability, effectiveness, and aesthetic.</p><h2>Other Information</h2> <p> Published in: Journal of Cleaner Production<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jclepro.2022.132841" target="_blank">https://dx.doi.org/10.1016/j.jclepro.2022.132841</a></p>2022-09-15T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.jclepro.2022.132841https://figshare.com/articles/journal_contribution/Interactive_visual_study_for_residential_energy_consumption_data/24720372CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247203722022-09-15T06:00:00Z |
| spellingShingle | Interactive visual study for residential energy consumption data Ayman Al-Kababji (16870080) Engineering Electrical engineering Information and computing sciences Data management and data science Human-centred computing Data and knowledge visualization Energy-aware systems Energy efficiency Mobile applications Evaluation studies Visualizations comparison |
| status_str | publishedVersion |
| title | Interactive visual study for residential energy consumption data |
| title_full | Interactive visual study for residential energy consumption data |
| title_fullStr | Interactive visual study for residential energy consumption data |
| title_full_unstemmed | Interactive visual study for residential energy consumption data |
| title_short | Interactive visual study for residential energy consumption data |
| title_sort | Interactive visual study for residential energy consumption data |
| topic | Engineering Electrical engineering Information and computing sciences Data management and data science Human-centred computing Data and knowledge visualization Energy-aware systems Energy efficiency Mobile applications Evaluation studies Visualizations comparison |