Including a space-time perspective in geospatial data modeling is especially relevant for anyone working in a domain where dynamics, e.g., change or movement, are relevant and there is a desire to represent and analyze these dynamics. This entry discusses two key dynamics, events and processes, that have been identified by geospatial scientists as being relevant for many different geospatial applications. Events may be formally distinguished from objects, and events and processes may also be distinguished from each other, and researchers have formalized sets of relations that hold for each type of dynamic. With regard to geospatial computing and analyses with events and processes, researchers have used spatial and space-time clustering and time series analyses among other methods to understand the distribution of events over time and the impact of sequences of events or processes for a domain.
For many years, collaboration has been a key cornerstone in the success of efforts achieved by the geospatial community. When paired with governance, collaborative efforts often lead to sustainability and have the effect of broadening the benefits that can be achieved. The following text shares how the geospatial community uses collaboration and governance as tools to achieve benefits across the community. Case studies are provided to illustrate the process and the outcomes achieved.