A Framework for Visualization and Exploration of Events

Abstract

The expanding deployment of sensor systems that capture location, time, and multiple thematic variables is increasing the need for exploratory spatio-temporal data analysis tools. Geographic information systems (GIS) and time series analysis tools support exploration of spatial and temporal patterns respectively and independently, but tools for the exploration of both dimensions within a single system are relatively rare. The contribution of this research is a framework for the visualization and exploration of spatial, temporal, and thematic dimensions of sensor-based data. The unit of analysis is an event, a spatio-temporal data type extracted from sensor data. The conceptual framework suggests an approach for design layout that can be flexibly modified to explore spatial and temporal trends, temporal relationships among events, periodic temporal patterns, the timing of irregularly repeating events, event–event relationships in terms of thematic attributes, and event patterns at different spatial and temporal granularities. Flexible assignment of spatial, temporal, and thematic categories to a set of graphical interface elements that can be easily rearranged provides exploratory power as well as a generalizable design layout structure. The framework is illustrated with events extracted from Gulf of Maine Ocean Observing System data but the approach has broad application to other domains and applications in which time, space, and attributes need to be considered in conjunction.

Web-based spatiotemporal visualization of marine environment data

“…In addition, the field-object model is used to represent thermal layer (such as temperature thermal layer, salinity thermal layer, density thermal layer and acoustic thermal layer), eddy (such as cold eddy and warm eddy), frontal surface, water mass, and other marine phenomena. There are a lot of previous visualization researches based on these expression models [11][12][13][14][15][16].…”

From movement tracks through events to places: Extracting and characterizing significant places from mobility data

“…Extraction of events from movement data. The possibility of extracting spatial events from different types of spatio-temporal data is discussed in [6] but concrete methods are not presented. Moving object databases [17] compute various dynamic attributes (numeric functions and predicates) and provide a powerful query language for extracting parts of trajectories based on these attributes.…”

“…We adhere to Kim's definition of events as exemplifications of properties or relationships at some times [22]. Spatial events are events localized in space [6].…”

“…As noted in [6] and [30], there are many definitions of the term event. We adhere to Kim's definition of events as exemplifications of properties or relationships at some times [22].…”

“…We adhere to Kim's definition of events as exemplifications of properties or relationships at some times [22]. Spatial events are events localized in space [6].The event-based view of movement is particularly suitable for applications and tasks where analysts are interested in occurrences of certain movement characteristics such as very high or very low speeds. Each occurrence is a spatial event.…”