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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: Standard dimension names
Up: Coordinates and Dimensions
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Robert VINCENT
2005-05-10