This week I am attending the AAG Annual Meeting in Chicago. While here, we organized 3 sessions entitled "Geosimulation and Big Data: A Marriage made in Heaven or Hell?" in which I presented a paper, co-authored with Sarah Wise: "Leveraging Crowdsourced data for Agent-based modeling: Opportunities, Examples and Challenges." The abstract is below:
The rise of crowdsourcing has made new kinds of data available to the geographical community. New forms of data range in their characteristics and purpose. One example is Volunteered Geographical Information (VGI), were users purposely contribute Geographic Information (GI) as in the case of OpenStreetMap; another is Ambient Geographic Information (AGI), where the intention of contributors is not necessarily to provide GI, but GI can be derived, as from Twitter. While much progress has been made in utilizing these new sources of data in GIScience, they have only recently begun to be integrated into agent-based models (ABM). This paper will discuss the opportunities that crowdsourced data provides for ABMs, specifically focusing on how such information gives us a new lens to study the micro-interactions of individuals. Through as series of examples we will demonstrate how such data can be integrated into geographically explicit ABMs. By building on these examples we will showcase how the spatial environment and agent populations can be built using crowdsourced information, and highlight how agent behaviors can be informed and validated by such information. We further discuss the challenges associated with this program of research: using such data is not without its difficulties, including gathering or accessing the data, storing the data, analyzing the collected data, and assessing its validity. Together, this work provides a brief overview of the current state of crowdsourced data-informed ABM.
If you like what is written above, you can have a flick through the slides from the talk or check out one of the movies: