Data models in geographic information systems
Communications of the ACM
The ordered weighted averaging operators: theory and applications
The ordered weighted averaging operators: theory and applications
Uncertainty Management in Information Systems: From Needs to Solutions
Uncertainty Management in Information Systems: From Needs to Solutions
Case Method: Entity Relationship Modelling
Case Method: Entity Relationship Modelling
Principles and Applications
Converting a Fuzzy Data Model to an Object-Oriented Design for Managing GIS Data Files
IEEE Transactions on Knowledge and Data Engineering
Evolution of entity-relationship modelling
Data & Knowledge Engineering
A system of types and operators for handling vague spatial objects
International Journal of Geographical Information Science
Data & Knowledge Engineering
Extracting knowledge from fuzzy relational databases with description logic
Integrated Computer-Aided Engineering
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Geographic information systems manage a wide variety of data. Some of these data are stored in traditional databases, but much more is not. We developed a model, based on the concept of aggregating data into sets, to manage a wide variety of diverse data formats as a single logical entity. Because it manages descriptive information (metadata) about sets rather than the data files themselves, this model will be able to accommodate new data formats as they are developed in the future. The model was initially annotated as an entity relation diagram. It was then extended with concepts from fuzzy set theory in order to deal with problems that occur when selecting among similar sets with overlapping data. The new fuzzy notations developed in this research are generally applicable to all entity relation data modeling and provide the basis for a new, more robust and descriptive type of modeling methodology.