Knowledge-Assisted Visualization of Multi-Level Origin-Destination Flows Using Ontologies

Origin-destination matrices help understand the movement of people within cities. Recently, we published a research work that built upon the premise that different stakeholders need to analyze mobility flows from spatio-temporal perspectives that are appropriate to their context of analysis. Herein we report our findings on building the semantic foundation of knowledge-assisted visualization tools for analyzing OD matrices from multiple stakeholder levels. We propose a set of ontology design patterns for modeling the semantics of OD data, and the relations between the spatio-temporal constructs that stakeholders ought to choose when visualizing urban mobility flows.