Spatio-Temporal Dynamics (STD) Data Model

The proposed innovative research represents geographic dynamics in spatio-temporal data models, positing that spatio-temporal data are samples of geographic dynamics and that understanding the drivers and outcomes of these dynamics is the ultimate goal of a spatio-temporal GIS. Our proposed expressive data model and enabling algorithms make it possible to query, analyze, understand, and predict with increasing accuracy how activities, events and processes manifest across space and time, so as to extract meaningful information and synthesize actionable intelligence. Impact Computing proposes development of an open source implementation of the Spatio-Temporal Dynamics (STD) data model, based on the pioneering work and research of Dr. May Yuan of the University of Oklahoma. Through its component-based architecture, our STD module may serve as an extension to existing GIS databases and tools, thereby facilitating integration with existing DoD systems and frameworks. Key innovations of the STD data model and research include: 1. a comprehensive ontology for activities, events, processes and states that emphasizes change, history, movement, and mutation; 2. the conceptual abstraction of activities, events and processes, distinct from entities or objects; 3. innovative application of dynamic time warping and other spatio-temporal analytical techniques to support similarity, behavior, and relationship queries