There has been considerable interest in the ability of big data-sets to reach across large populations of people and things, often capturing glimpses of their actions, interactions, and transactions in geographical context and in massive volume. The breadth of the reach, and the rapidity of update that big data afford have presented a range of new opportunities for geosimulation. Concurrently, however, there is a burgeoning shift in the availability "small data": data-sets on one single individual person or thing, in massive detail, with rapid refresh, and with valuable geographical context. In this paper we focus on the ability of small data to support rich modeling of individual agents in geosimulation and we discuss the potential utility of GIS for small data in the particular context of motion capture.
Torrens, Paul, and Hai Lan. 2015. "Micro Big Data and Geosimulation." Presented at the Association of American Geographers Annual Meeting, Chicago. http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=65136