Information Integration Through Events
PI: Kate Beard
Environmental data collections are increasing and there is a growing interest in integrating such data to investigate ecological phenomena and their interactions. Understanding space-time interactions of variables and processes is key to improving understanding of ecosystem dynamics yet these interactions are difficult to capture and assimilate across heterogeneous data streams.
Ocean observing systems (OOS) are a subset of monitoring systems that collect space-time series on ocean related variables. Different measurement protocols, variations in the space time regimes of the sensing streams, and variations in the media, formats, and quality of the sensing streams challenge the ability to integrate and synthesize this data. Exploration and analysis has tended to be constrained to individual observation data streams rather than across observation streams limiting a more encompassing view of ecological processes. This project investigated an information integration approach that involves transformation of information content from disparate observation streams to a common higher-level data type: a space-time event. The project:
- worked with domain scientists in oceanography to construct an ontology of events and event behaviors,
- developed data mining strategies to detect events in ocean related time and space-time series
- developed theory, methodology and tools to model, explore, visualize and analyze spatial-temporal events.