Section: 3 The "Classic" NetCDF Data Model

3.0	Models, Conventions, and Formats Data models, conventions, and formats are at different levels of abstraction.
3.1	What Is a Data Model? Data models are useful abstractions.
3.2	The "Classic" NetCDF Data Model The classic netCDF data model uses dimensions, variables, and attributes, to capture the meaning of array-oriented scientific data.
3.3	CDL CDL (Common Data Language) is text notation for netCDF objects and data.
3.4	A Simple Example A concrete example of netCDF dimensions, variables, and attributes.
3.5	NetCDF Files NetCDF files are containers for Dimensions, Variables, and Global Attributes.
3.6	Dimensions Dimensions are used to specify variable shapes, common grids, and coordinate systems.
3.7	Variables Variables hold data values. In the classic netCDF data model, a variable can hold a multidimensional array of values of the same type.
3.8	Variable Methods Things you can do with a netCDF variable include getting information about it, putting data values into it, and getting data values out of it.
3.9	Coordinate Variables Coordinate Variables contain the coordinate values for a dimension.
3.10	An Example of Coordinate Variables A concrete example of simple coordinate variables.
3.11	Attributes Attributes hold metadata (data about data). An attribute contains information about properties of a variable or dataset.
3.12	Attribute Methods Things you can do with a netCDF attribute include inquiring about its type or length, defining its value, and getting its value.
3.13	Variables Versus Attributes When should you use variables or attributes?
3.14	Classic NetCDF Model Limitations The classic netCDF data model used for netCDF-3 has some limitations.