Motivation for Designing a Data Representation Model
It isn't practical to try to define data models for all possible types of data and their attributes.
Need a different approach to design a model that can be applied easily to the many different kinds of environmental data, while still being general enough to be understood by many different applications.
Key Principles
- Separating the semantics of what something represents from the "data primitives" used to represent it
- Factoring out the common syntax and semantics of data models used to represent similar things
Combining these two principles gives us the tools to create a single schema to represent an endless variety of data models: the SEDRIS Data Representation Model.