Name: ASHRAE Global Occupant Behavior Database
Creator: Kaggle
License: https://opendatacommons.org/licenses/by/1-0/index.html

About this Dataset

ASHRAE Global Occupant Behavior Database

Dataset and documentation: https://ashraeobdatabase.com

Context

The ASHRAE Global Occupant Behavior Database was developed by Wei Mu, Yapan Liu and Bing Dong (Syracuse University), Tianzhen Hong (LBNL), Bjarne W. Olesen (Technical University of Denmark), Tom Lawrence (University of Georgia) and Zheng O’Neill (Texas A&M University) as part of the ASHRAE MTG.OBB research grant URP-1883.

Content

Study_ID	Behavior_Type	Publication
1	Door_Status	Korsavi, S. S., Montazami, A., & Brusey, J. (2018). Developing a design framework to facilitate adaptive behaviours. Energy and Buildings, 179, 360-373. https://doi.org/10.1016/j.enbuild.2018.09.011
	Fan_Status
	Occupant_Number
	Occupancy
	Shading_Status
	Window_Status
2	Appliance_Usage	Rafsanjani, H. N., Ahn, C. R., & Chen, J. (2018). Linking building energy consumption with occupants' energy-consuming behaviors in commercial buildings: Non-intrusive occupant load monitoring (NIOLM). Energy and Buildings, 172, 317-327. https://doi.org/10.1016/j.enbuild.2018.05.007
3	Door_Status	Kumar, S., Singh, M. K., Kukreja, R., Chaurasiya, S. K., & Gupta, V. K. (2019). Comparative study of thermal comfort and adaptive actions for modern and traditional multi-storey naturally ventilated hostel buildings during monsoon season in India. Journal of Building Engineering, 23, 90-106. https://doi.org/10.1016/j.jobe.2019.01.020
	Fan_Status
	Window_Status
4	HVAC_Measurement	Schwee, J. H., Johansen, A., Jørgensen, B. N., Kjærgaard, M. B., Mattera, C. G., Sangogboye, F. C., & Veje, C. (2019). Room-level occupant counts and environmental quality from heterogeneous sensing modalities in a smart building. Scientific data, 6(1), 1-11. https://doi.org/10.1038/s41597-019-0274-4
	Occupant_Number
5	Appliance_Usage	Piselli, C., & Pisello, A. L. (2019). Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance. Energy, 176, 667-681. https://doi.org/10.1016/j.energy.2019.04.005
	Door_Status
	Window_Status
8	Door_Status	Touchie, M. F., & Pressnail, K. D. (2014). Using suite energy-use and interior condition data to improve energy modeling of a 1960s MURB. Energy and buildings, 80, 184-194. http://doi.org/10.1016/j.enbuild.2014.05.014
	Window_Status
9	Lighting_Status	Bursill, J. (2020). An Approach to Data-Driven Sensing and Predictive Supervisory Control for Commercial Buildings with In-Situ Evaluation (Doctoral dissertation, Carleton University). https://doi.org/10.22215/etd/2020-14103
	Occupancy
10	Appliance_Usage	Mora, D., Fajilla, G., Austin, M. C., & De Simone, M. (2019). Occupancy patterns obtained by heuristic approaches: cluster analysis and logical flowcharts. A case study in a university office. Energy and Buildings, 186, 147-168. https://doi.org/10.1016/j.enbuild.2019.01.023
	Door_Status
	HVAC_Measurement
	Occupancy
	Occupant_Number
	Window_Status
11	Occupancy	Dong, B., Li, Z., & Mcfadden, G. (2015). An investigation on energy-related occupancy behavior for low-income residential buildings. Science and Technology for the Built Environment, 21(6), 892-901. http://doi.org/10.1080/23744731.2015.1040321
13	HVAC_Measurement	Bandurski, K., Hamerla, M., Szulc, J., & Koczyk, H. (2017). The influence of multifamily apartment building occupants on energy and water consumption-the preliminary results of monitoring and survey campaign. In E3S Web of Conferences (Vol. 22, p. 00010). EDP Sciences. https://doi.org/10.1051/e3sconf/20172200010
18	Appliance_Usage	Das, A., Annaqeeb, M. K., Azar, E., Novakovic, V., & Kjærgaard, M. B. (2020). Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods. Applied Energy, 269, 115135. https://doi.org/10.1016/j.apenergy.2020.115135
	Occupancy
19	Fan_Status	Lipczynska, A., Schiavon, S., & Graham, L. T. (2018). Thermal comfort and self-reported productivity in an office with ceiling fans in the tropics. Building and Environment, 135, 202-212. https://doi.org/10.1016/j.buildenv.2018.03.013
	HVAC_Measurement
	Window_Status
20	Appliance_Usage	Mahdavi, A., Berger, C., Tahmasebi, F., & Schuss, M. (2019). Monitored data on occupants' presence and actions in an office building. Scientific data, 6(1), 1-5. https://doi.org/10.1038/s41597-019-0271-7
22	Appliance_Usage	Sonta, A., Dougherty, T. R., & Jain, R. K. (2021). Data-driven optimization of building layouts for energy efficiency. Energy and Buildings, 238, 110815. https://doi.org/10.1016/j.enbuild.2021.110815
23	HVAC_Measurement	Neves, L. O., Hopes, A. P., Chung, W. J., & Natarajan, S. (2020). "Mind reading" building operation behaviour. Energy for Sustainable Development, 56, 1-18. https://doi.org/10.1016/j.esd.2020.02.003
	Window_Status
24	Occupancy	Schweiker, M., Kleber, M., & Wagner, A. (2019). Long-term monitoring data from a naturally ventilated office building. Scientific data, 6(1), 1-6. https://doi.org/10.1038/s41597-019-0283-3
	Window_Status
25	HVAC_Measurement	Rupp, Ricardo Forgiarini; Andersen, R.K.; Toftum, J.; Ghisi, E. (2021). Occupant behaviour in mixed-mode office buildings in a subtropical climate: Beyond typical models of adaptive actions https://doi.org/10.1016/j.buildenv.2020.107541
26	Door_Status	Langevin, J. (2019). Longitudinal dataset of human-building interactions in US offices. Scientific data, 6(1), 1-10. https://doi.org/10.1038/s41597-019-0273-5
	Fan_Status
	HVAC_Measurement
	Shading_Status
	Window_Status
27	Other_HeatWave	Andrews, Clinton & Mainelis, Gediminas & (co-Pi, Richard & Sorensen Allacci, Maryann & Plotnik, Deborah & Senick, Jennifer & Feygina, Irina & Autote, Olga & Ramkumar, Swetha & Pryce, Tiffany & Marathe, Rewa & Ding, Jiayi. (2013). Expanding the Definition of Green - Impacts of Green and Active Living Design on Health in Low Income Housing: Added Value of Behavioral Interventions as part of an Integrated Service Delivery Model.
28	Other_Role of habits in consumption	Andrews, Clinton & Mainelis, Gediminas & (co-Pi, Richard & Sorensen Allacci, Maryann & Plotnik, Deborah & Senick, Jennifer & Feygina, Irina & Autote, Olga & Ramkumar, Swetha & Pryce, Tiffany & Marathe, Rewa & Ding, Jiayi. (2013). Expanding the Definition of Green - Impacts of Green and Active Living Design on Health in Low Income Housing: Added Value of Behavioral Interventions as part of an Integrated Service Delivery Model.
29	Other_IAQ in Affordable Housing	Andrews, Clinton & Mainelis, Gediminas & (co-Pi, Richard & Sorensen Allacci, Maryann & Plotnik, Deborah & Senick, Jennifer & Feygina, Irina & Autote, Olga & Ramkumar, Swetha & Pryce, Tiffany & Marathe, Rewa & Ding, Jiayi. (2013). Expanding the Definition of Green - Impacts of Green and Active Living Design on Health in Low Income Housing: Added Value of Behavioral Interventions as part of an Integrated Service Delivery Model.
30	Occupancy	Park, J. Y., Dougherty, T., Fritz, H., & Nagy, Z. (2019). LightLearn: An adaptive and occupant centered controller for lighting based on reinforcement learning. Building and Environment, 147, 397-414. https://doi.org/10.1016/j.buildenv.2018.10.028
	Lighting_Status
31	Door_Status	Malik, J., Bardhan, R., Hong, T., & Piette, M. A. (2020). Contextualising adaptive comfort behaviour within low-income housing of Mumbai, India. Building and Environment, 177, 106877. https://doi.org/10.1016/j.buildenv.2020.106877
	Fan_Status
	HVAC_Measurement
	Light_Status
	Window_Status
32	Occupant_Number	Wang, Z., Hong, T., Piette, M. A., & Pritoni, M. (2019). Inferring occupant counts from Wi-Fi data in buildings through machine learning. Building and Environment, 158, 281-294. https://doi.org/10.1016/j.buildenv.2019.05.015

License:

This ASHRAE Global Occupant Behavior Database is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.

Acknowledgments:

The authors wish to acknowledge the generous contributions made by all dataset contributors. If you intend to use the research data contained in this database, please ensure that you give appropriate acknowledgment (e.g. citation) to the original researchers. We would also like to acknowledge the sponsorship from ASHRAE, Building Technologies Office of the U.S. Department of Energy, and kind support from IEA Annex 79 to make this possible.

Tables

Study 8 Window Status

@kaggle.claytonmiller_ashrae_global_occupant_behavior_database.study_8_window_status

239.31 kB
113,424 rows
5 columns

CREATE TABLE study_8_window_status (
  "date_time" TIMESTAMP,
  "window_status_0_closed_1_open" BIGINT  -- Window Status[0-Closed;1-Open],
  "window_id" BIGINT,
  "room_id" BIGINT,
  "building_id" BIGINT
);

Study 9 Occupancy Measurement

@kaggle.claytonmiller_ashrae_global_occupant_behavior_database.study_9_occupancy_measurement

446.11 kB
48,292 rows
4 columns

CREATE TABLE study_9_occupancy_measurement (
  "date_time" TIMESTAMP,
  "occupancy_measurement_0_unoccupied_1_occupied" BIGINT  -- Occupancy Measurement[0-Unoccupied;1-Occupied],
  "room_id" BIGINT,
  "building_id" BIGINT
);

Study 9 Static Info

@kaggle.claytonmiller_ashrae_global_occupant_behavior_database.study_9_static_info

4.73 kB
26 rows
6 columns

CREATE TABLE study_9_static_info (
  "country" VARCHAR,
  "city" VARCHAR,
  "building_type" VARCHAR,
  "room_type" VARCHAR,
  "building_id" BIGINT,
  "room_id" BIGINT
);