@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 = nov,
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",
note = "2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2019 ; Conference date: 05-11-2019",
}