VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery

Liu Xiufeng; Zhibin Niu; Linda Yang; Junqi Wu; Dawei Cheng; Xin Wang

doi:10.5441/002/edbt.2020.68

VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery

Liu Xiufeng, Zhibin Niu, Linda Yang, Junqi Wu, Dawei Cheng, Xin Wang

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

In the context of urbanization and the rapid growth of energy demand, understanding the spatial and temporal dynamics of urban energy use is crucial for identifying energy-saving potentials. In this demo, we present a visual analysis tool, VAP, that allows users to explore the dynamics of urban energy use at different spatial and temporal scales. In contrast to traditional statistical and machine learning methods, the visual analysis based tool focuses on analytical thinking, user interactions and answering business questions by examining different visual analysis views. In the demonstration, conference attendees will interact with VAP and learn its capabilities in discovering typical consumption patterns and spatio-temporal shift patterns from a real-world case study of electricity.

Original language	English
Title of host publication	EDBT 2020
Subtitle of host publication	23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings
Editors	Angela Bonifati, Yongluan Zhou, Marcos Antonio Vaz Salles, Alexander Böhm, Dan Olteanu, George Fletcher, Arijit Khan, Bin Yang
Publisher	OpenProceedings.org
Pages	579-582
ISBN (Electronic)	978-3-89318-083-7
DOIs	https://doi.org/10.5441/002/edbt.2020.68
Publication status	Published - 2 Apr 2020
Event	International Conference on Extending Database Technology - Scandic Falkoner Congress Center, Copenhagen, Denmark Duration: 30 Mar 2020 → 2 Apr 2020 Conference number: 23rd https://diku-dk.github.io/edbticdt2020/?contents=main.html

Publication series

Name	Advances in Database Technology
Publisher	OpenProceedings.org
ISSN (Electronic)	2367-2005

Conference

Conference	International Conference on Extending Database Technology
Abbreviated title	EDBT 2020
Country/Territory	Denmark
City	Copenhagen
Period	30/03/20 → 2/04/20
Internet address	https://diku-dk.github.io/edbticdt2020/?contents=main.html

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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© 2020 Copyright held by the owner/author(s). Published in Proceedings of the 23rd International Conference on Extending Database Technology (EDBT), March 30-April 2, 2020, ISBN 978-3-89318-083-7 on OpenProceedings.org. Distribution of this paper is permitted under the terms of the Creative Commons license CC-by-nc-nd 4.0.
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https://openproceedings.org/html/pages/2020_edbt.html

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Xiufeng, L., Niu, Z., Yang, L., Wu, J., Cheng, D., & Wang, X. (2020). VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery. In A. Bonifati, Y. Zhou, M. A. Vaz Salles, A. Böhm, D. Olteanu, G. Fletcher, A. Khan, & B. Yang (Eds.), EDBT 2020: 23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings (pp. 579-582). (Advances in Database Technology). OpenProceedings.org. https://doi.org/10.5441/002/edbt.2020.68

Xiufeng, Liu ; Niu, Zhibin ; Yang, Linda et al. / VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery. EDBT 2020: 23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings. editor / Angela Bonifati ; Yongluan Zhou ; Marcos Antonio Vaz Salles ; Alexander Böhm ; Dan Olteanu ; George Fletcher ; Arijit Khan ; Bin Yang. OpenProceedings.org, 2020. pp. 579-582 (Advances in Database Technology).

@inproceedings{f7467b7eca50452aaea50cc51fa1611b,

title = "VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery",

abstract = "In the context of urbanization and the rapid growth of energy demand, understanding the spatial and temporal dynamics of urban energy use is crucial for identifying energy-saving potentials. In this demo, we present a visual analysis tool, VAP, that allows users to explore the dynamics of urban energy use at different spatial and temporal scales. In contrast to traditional statistical and machine learning methods, the visual analysis based tool focuses on analytical thinking, user interactions and answering business questions by examining different visual analysis views. In the demonstration, conference attendees will interact with VAP and learn its capabilities in discovering typical consumption patterns and spatio-temporal shift patterns from a real-world case study of electricity.",

author = "Liu Xiufeng and Zhibin Niu and Linda Yang and Junqi Wu and Dawei Cheng and Xin Wang",

year = "2020",

month = apr,

day = "2",

doi = "10.5441/002/edbt.2020.68",

language = "English",

series = "Advances in Database Technology",

publisher = "OpenProceedings.org",

pages = "579--582",

editor = "Angela Bonifati and Yongluan Zhou and {Vaz Salles}, {Marcos Antonio} and Alexander B{\"o}hm and Dan Olteanu and George Fletcher and Arijit Khan and Bin Yang",

booktitle = "EDBT 2020",

note = "International Conference on Extending Database Technology, EDBT 2020 ; Conference date: 30-03-2020 Through 02-04-2020",

url = "https://diku-dk.github.io/edbticdt2020/?contents=main.html",

}

Xiufeng, L, Niu, Z, Yang, L, Wu, J, Cheng, D & Wang, X 2020, VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery. in A Bonifati, Y Zhou, MA Vaz Salles, A Böhm, D Olteanu, G Fletcher, A Khan & B Yang (eds), EDBT 2020: 23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings. Advances in Database Technology, OpenProceedings.org, pp. 579-582, International Conference on Extending Database Technology, Copenhagen, Denmark, 30/03/20. https://doi.org/10.5441/002/edbt.2020.68

VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery. / Xiufeng, Liu; Niu, Zhibin; Yang, Linda et al.
EDBT 2020: 23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings. ed. / Angela Bonifati; Yongluan Zhou; Marcos Antonio Vaz Salles; Alexander Böhm; Dan Olteanu; George Fletcher; Arijit Khan; Bin Yang. OpenProceedings.org, 2020. p. 579-582 (Advances in Database Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery

AU - Xiufeng, Liu

AU - Niu, Zhibin

AU - Yang, Linda

AU - Wu, Junqi

AU - Cheng, Dawei

AU - Wang, Xin

N1 - Conference code: 23rd

PY - 2020/4/2

Y1 - 2020/4/2

N2 - In the context of urbanization and the rapid growth of energy demand, understanding the spatial and temporal dynamics of urban energy use is crucial for identifying energy-saving potentials. In this demo, we present a visual analysis tool, VAP, that allows users to explore the dynamics of urban energy use at different spatial and temporal scales. In contrast to traditional statistical and machine learning methods, the visual analysis based tool focuses on analytical thinking, user interactions and answering business questions by examining different visual analysis views. In the demonstration, conference attendees will interact with VAP and learn its capabilities in discovering typical consumption patterns and spatio-temporal shift patterns from a real-world case study of electricity.

AB - In the context of urbanization and the rapid growth of energy demand, understanding the spatial and temporal dynamics of urban energy use is crucial for identifying energy-saving potentials. In this demo, we present a visual analysis tool, VAP, that allows users to explore the dynamics of urban energy use at different spatial and temporal scales. In contrast to traditional statistical and machine learning methods, the visual analysis based tool focuses on analytical thinking, user interactions and answering business questions by examining different visual analysis views. In the demonstration, conference attendees will interact with VAP and learn its capabilities in discovering typical consumption patterns and spatio-temporal shift patterns from a real-world case study of electricity.

U2 - 10.5441/002/edbt.2020.68

DO - 10.5441/002/edbt.2020.68

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A2 - Zhou, Yongluan

A2 - Vaz Salles, Marcos Antonio

A2 - Böhm, Alexander

A2 - Olteanu, Dan

A2 - Fletcher, George

A2 - Khan, Arijit

A2 - Yang, Bin

PB - OpenProceedings.org

T2 - International Conference on Extending Database Technology

Y2 - 30 March 2020 through 2 April 2020

ER -

Xiufeng L, Niu Z, Yang L, Wu J, Cheng D, Wang X. VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery. In Bonifati A, Zhou Y, Vaz Salles MA, Böhm A, Olteanu D, Fletcher G, Khan A, Yang B, editors, EDBT 2020: 23rd International Conference on Extending Database Technology Copenhagen, Denkmark, March 30–April 2, 2020 Proceedings. OpenProceedings.org. 2020. p. 579-582. (Advances in Database Technology). doi: 10.5441/002/edbt.2020.68

VAP: a visual analysis tool for energy consumption spatio-temporal pattern discovery

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UN SDGs

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