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DA-11 - GIS&T and the Digital Humanities

This entry reviews the use of GIS&T in the digital humanities and in the spatial humanities, highlighting opportunities for interdisciplinary collaborations between GIScientists and humanities scholars, including in history, archeology, and literary studies. Challenges are highlighted as well, including epistemological and ontological differences between the spatial, abstract, and quantitative view of the world of GIS&T and GIScience and the humanities emphasis on place and qualitative methods. The potential of mixed methods to bring together different epistemological perspectives is discussed in this context. Scale is identified as a promising geographical framework for humanities research, both in its metaphorical aspects and as intended in cartography. Examples of the use of GIS&T and GIScience in the humanities are provided, including historical GIS, geohistorical gazetteers, archeology and GIS, and GIS in literary studies. The entry is framed historically, with reference to the work of Bakhtin, Braudel, and Hägerstrand, who are early influencers of the spatial turn in the humanities. Among the research directions briefly explored are the GIS of place, deep maps, and qualitative GIS, which exemplify how the collaboration between GIScience and the humanities can be strengthened.

AM-80 - Capturing Spatiotemporal Dynamics in Computational Modeling

We live in a dynamic world that includes various types of changes at different locations over time in natural environments as well as in human societies. Modern sensing technology, location-aware technology and mobile technology have made it feasible to collect spatiotemporal tracking data at a high spatial and temporal granularity and at affordable costs. Coupled with powerful information and communication technologies, we now have much better data and computing platforms to pursue computational modeling of spatiotemporal dynamics. Researchers have attempted to better understand various kinds of spatiotemporal dynamics in order to predict, or even control, future changes of certain phenomena. A simple approach to representing spatiotemporal dynamics is by adding time (t) to the spatial dimensions (x,y,z) of each feature. However, spatiotemporal dynamics in the real world are more complex than a simple representation of (x,y,z,t) that describes the location of a feature at a given time. This article presents selected concepts, computational modeling approaches, and sample applications that provide a foundation to computational modeling of spatiotemporal dynamics. We also indicate why the research of spatiotemporal dynamics is important to geographic information systems (GIS) and geographic information science (GIScience), especially from a temporal GIS perspective.