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.
Visualization encompasses the display of quantities or qualities of visible or invisible phenomena through the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, color, and animation. The objectives of visualization are to provoke insights and expand comprehension of information by revealing complex relationships among data. Geographical information is visualized in the form of maps. Recent concern over the accuracy and reliability of spatial information in geographic information systems has raised an interest in applying visualization tools to comprehend and communicate the reliability of GIS information and products. This paper develops design requirements for visualization of spatial data quality based on characterizations of quality, a range of quality assessment tasks, and different contexts under which data quality might be investigated.
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