Abstract
Recent developments in service-oriented and distributed computing have created exciting opportunities for the integration of models in service chains to create the Model Web. This offers the potential for orchestrating web data and processing services, in complex chains; a flexible approach which exploits the increased access to products and tools, and the scalability offered by the Web. However, the uncertainty inherent in data and models must be quantified and communicated in an interoperable way, in order for its effects to be effectively assessed as errors propagate through complex automated model chains. We describe a proposed set of tools for handling, characterizing and communicating uncertainty in this context, and show how they can be used to 'uncertainty- enable' Web Services in a model chain. An example implementation is presented, which combines environmental and publicly-contributed data to produce estimates of sea-level air pressure, with estimates of uncertainty which incorporate the effects of model approximation as well as the uncertainty inherent in the observational and derived data.
Original language | English |
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Title of host publication | Accuracy 2010 |
Subtitle of host publication | Proceedings of the 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences |
Editors | Nicholas J. Tate, Peter F. Fisher |
Publication status | Published - 2010 |
Event | 9th international symposium on spatial accuracy - Leicester, United Kingdom Duration: 20 Jul 2010 → 23 Jul 2010 |
Conference
Conference | 9th international symposium on spatial accuracy |
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Abbreviated title | Accuracy 2010 |
Country/Territory | United Kingdom |
City | Leicester |
Period | 20/07/10 → 23/07/10 |
Keywords
- uncertainty propagation
- probability
- web services