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Learning Objectives:
Differentiate among modeling uncertainty for entire datasets, for features, and for individual data values
Describe SQL extensions for querying uncertainty information in databases
Describe extensions to relational DBMS to represent different types of uncertainty in attributes, including both vagueness/fuzziness and error-based uncertainty
Discuss the role of metadata in representing and communicating dataset-level uncertainty
Create a GIS database that models uncertain information
Identify whether it is important to represent uncertainty in a particular GIS application
Describe the architecture of data models (both field- and object-based) to represent feature-level and datum-level uncertainty
Evaluate the advantages and disadvantages of existing uncertainty models based on storage efficiency, query performance, ease of data entry, and ability to implement in existing software
You are currently viewing an archived version of Topic . If updates or revisions have been published you can find them at .