CyberGIS-Jupyter for spatially explicit agent-based modeling: A case study on influenza transmission

Jeon Young Kang, Jared Aldstadt, Alexander Michels, Rebecca Vandewalle, Shaowen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Despite extensive efforts on achieving reproducible agent-based models (ABMs) to improve the capability of this widely adopted methodology, it remains challenging to reproduce and replicate pre-existing ABMs, due to a number of factors such as diverse computing resources and ABMs platforms. In this study, we propose to employ CyberGIS-Jupyter for spatially explicit ABMs. CyberGIS-Jupyter is a cyberGIS framework to achieve data-intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on advanced cyberinfrastructure. Influenza transmission in the city of Miami, Florida, USA was used as a case study. In the model, Influenza is transmitted through the contact networks of individual human agents, which are constructed based on commuting behaviors. CyberGIS-Jupyter can support one not only to conduct collaborative and transparent modeling, but also to perform modeling simulation on advanced cyberinfrastructure resources. It may contribute to boosting the reproducibility and replicability of ABMs.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019
EditorsHamdi Kavak, Joon-Seok Kim, Sarah Wise
PublisherAssociation for Computing Machinery, Inc
Pages32-35
Number of pages4
ISBN (Electronic)9781450369565
DOIs
StatePublished - Nov 5 2019
Event2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019 - Chicago, United States
Duration: Nov 5 2019 → …

Publication series

NameProceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019

Conference

Conference2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019
CountryUnited States
CityChicago
Period11/5/19 → …

Fingerprint

Computer simulation

Keywords

  • Agent-Based Modeling
  • CyberGIS
  • Influenza
  • Replicability
  • Reproducibility

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

Cite this

Kang, J. Y., Aldstadt, J., Michels, A., Vandewalle, R., & Wang, S. (2019). CyberGIS-Jupyter for spatially explicit agent-based modeling: A case study on influenza transmission. In H. Kavak, J-S. Kim, & S. Wise (Eds.), Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019 (pp. 32-35). (Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3356470.3365531

CyberGIS-Jupyter for spatially explicit agent-based modeling : A case study on influenza transmission. / Kang, Jeon Young; Aldstadt, Jared; Michels, Alexander; Vandewalle, Rebecca; Wang, Shaowen.

Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019. ed. / Hamdi Kavak; Joon-Seok Kim; Sarah Wise. Association for Computing Machinery, Inc, 2019. p. 32-35 (Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kang, JY, Aldstadt, J, Michels, A, Vandewalle, R & Wang, S 2019, CyberGIS-Jupyter for spatially explicit agent-based modeling: A case study on influenza transmission. in H Kavak, J-S Kim & S Wise (eds), Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019, Association for Computing Machinery, Inc, pp. 32-35, 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019, Chicago, United States, 11/5/19. https://doi.org/10.1145/3356470.3365531
Kang JY, Aldstadt J, Michels A, Vandewalle R, Wang S. CyberGIS-Jupyter for spatially explicit agent-based modeling: A case study on influenza transmission. In Kavak H, Kim J-S, Wise S, editors, Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019. Association for Computing Machinery, Inc. 2019. p. 32-35. (Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019). https://doi.org/10.1145/3356470.3365531
Kang, Jeon Young ; Aldstadt, Jared ; Michels, Alexander ; Vandewalle, Rebecca ; Wang, Shaowen. / CyberGIS-Jupyter for spatially explicit agent-based modeling : A case study on influenza transmission. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019. editor / Hamdi Kavak ; Joon-Seok Kim ; Sarah Wise. Association for Computing Machinery, Inc, 2019. pp. 32-35 (Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019).
@inproceedings{92e8a3fef54b4954a628703f2bdb54aa,
title = "CyberGIS-Jupyter for spatially explicit agent-based modeling: A case study on influenza transmission",
abstract = "Despite extensive efforts on achieving reproducible agent-based models (ABMs) to improve the capability of this widely adopted methodology, it remains challenging to reproduce and replicate pre-existing ABMs, due to a number of factors such as diverse computing resources and ABMs platforms. In this study, we propose to employ CyberGIS-Jupyter for spatially explicit ABMs. CyberGIS-Jupyter is a cyberGIS framework to achieve data-intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on advanced cyberinfrastructure. Influenza transmission in the city of Miami, Florida, USA was used as a case study. In the model, Influenza is transmitted through the contact networks of individual human agents, which are constructed based on commuting behaviors. CyberGIS-Jupyter can support one not only to conduct collaborative and transparent modeling, but also to perform modeling simulation on advanced cyberinfrastructure resources. It may contribute to boosting the reproducibility and replicability of ABMs.",
keywords = "Agent-Based Modeling, CyberGIS, Influenza, Replicability, Reproducibility",
author = "Kang, {Jeon Young} and Jared Aldstadt and Alexander Michels and Rebecca Vandewalle and Shaowen Wang",
year = "2019",
month = "11",
day = "5",
doi = "10.1145/3356470.3365531",
language = "English (US)",
series = "Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "32--35",
editor = "Hamdi Kavak and Joon-Seok Kim and Sarah Wise",
booktitle = "Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019",

}

TY - GEN

T1 - CyberGIS-Jupyter for spatially explicit agent-based modeling

T2 - A case study on influenza transmission

AU - Kang, Jeon Young

AU - Aldstadt, Jared

AU - Michels, Alexander

AU - Vandewalle, Rebecca

AU - Wang, Shaowen

PY - 2019/11/5

Y1 - 2019/11/5

N2 - Despite extensive efforts on achieving reproducible agent-based models (ABMs) to improve the capability of this widely adopted methodology, it remains challenging to reproduce and replicate pre-existing ABMs, due to a number of factors such as diverse computing resources and ABMs platforms. In this study, we propose to employ CyberGIS-Jupyter for spatially explicit ABMs. CyberGIS-Jupyter is a cyberGIS framework to achieve data-intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on advanced cyberinfrastructure. Influenza transmission in the city of Miami, Florida, USA was used as a case study. In the model, Influenza is transmitted through the contact networks of individual human agents, which are constructed based on commuting behaviors. CyberGIS-Jupyter can support one not only to conduct collaborative and transparent modeling, but also to perform modeling simulation on advanced cyberinfrastructure resources. It may contribute to boosting the reproducibility and replicability of ABMs.

AB - Despite extensive efforts on achieving reproducible agent-based models (ABMs) to improve the capability of this widely adopted methodology, it remains challenging to reproduce and replicate pre-existing ABMs, due to a number of factors such as diverse computing resources and ABMs platforms. In this study, we propose to employ CyberGIS-Jupyter for spatially explicit ABMs. CyberGIS-Jupyter is a cyberGIS framework to achieve data-intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on advanced cyberinfrastructure. Influenza transmission in the city of Miami, Florida, USA was used as a case study. In the model, Influenza is transmitted through the contact networks of individual human agents, which are constructed based on commuting behaviors. CyberGIS-Jupyter can support one not only to conduct collaborative and transparent modeling, but also to perform modeling simulation on advanced cyberinfrastructure resources. It may contribute to boosting the reproducibility and replicability of ABMs.

KW - Agent-Based Modeling

KW - CyberGIS

KW - Influenza

KW - Replicability

KW - Reproducibility

UR - http://www.scopus.com/inward/record.url?scp=85075601851&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85075601851&partnerID=8YFLogxK

U2 - 10.1145/3356470.3365531

DO - 10.1145/3356470.3365531

M3 - Conference contribution

AN - SCOPUS:85075601851

T3 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019

SP - 32

EP - 35

BT - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019

A2 - Kavak, Hamdi

A2 - Kim, Joon-Seok

A2 - Wise, Sarah

PB - Association for Computing Machinery, Inc

ER -