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Associating HDF5 dataspaces with MINC dimensions

NetCDF defines a named-dimension abstraction which permits a dimension and its length to be associated with a text symbol. This dimension may then be used to define any number of NetCDF variables. MINC 1.0 relies on this feature to link the dimensionality of related objects. Unfortunately, HDF5 does not implement a comparable dimension abstraction. Instead, all HDF5 data objects (datasets and attributes) are associated with an HDF5 construct called a ``dataspace''. A dataspace in HDF5 may either be of one of two classes, ``scalar'' or ``simple''. Simple dataspaces consist of an ordered list of dimension lengths. Dataspaces in HDF5 are not global entities, and cannot be assigned symbolic names - every data object is associated with its own dataspace.

Since the structure of the dataspace alone is insufficient to allow software to discover the relationships between the dimensions of associated data objects, MINC 2.0 defines a dimorder attribute that makes these relationships explicit. Every data object that is non-scalar must have an associated dimorder attribute.

The dimorder attribute's value is a character string which consists of an ordered, comma-separated list of the mnemonic names associated with the dimensions. This provides an adequate, if imperfect, replacement for the named dimensions of NetCDF.


next up previous contents
Next: Standard dimension names Up: Coordinates and Dimensions Previous: Dimension variables   Contents
Robert VINCENT 2005-05-10