Visualizing Uncertainty in Environmental Work-Flows and Sensor Streams

Environmental data and models are uncertain by nature. The lack of knowledge about, for example, the magnitude of potential measurement errors may lead to unforeseen consequences. This makes it difficult to assess the data's or model's usefulness for critical applications. The authors present an approach for the visualization of uncertainty coming from in-situ environmental sensors. The visualization component is part of a Web-enabled environmental modeling platform which also supports the specification of processing work flows. The concept of uncertainty and means for its encoding as part of the environmental data are introduced. The individual components in the processing work flows propagate and update the uncertainty information.

Provided by: University of Muenster Topic: Big Data Date Added: Apr 2011 Format: PDF

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