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. |