Multidimensional Data Formats
The term “multidimensional data” is used in two different ways in data management. In the first sense, it refers to data aggregates created by different groupings of relational data for on-line analytical processing. In the second sense, the term refers to data that can be described as arrays over heterogeneous data types together with metadata to describe them.
Example: HDF (Hierarchical Data Format) and NetCDF (network Common Data Form) are well known multidimensional data formats used in scientific applications.
The goal of a multidimensional data format is to enable random access to very large, very complex, heterogeneous data, such that the data is self describing, sharable, compact, extendible, and archivable. For example, a composite of 900 files from a seismic simulation has been organized in HDF5 format to create a terabyte-sized dataset. One can mix tables, images, small metadata, streams of data from instruments, and structured grids all in the same HDF...
- 1.Home page of the HDF group. Available at: http://hdf.ncsa.uiuc.edu/.
- 2.Home page of the NetCDF group. Available at: http://www.unidata.ucar.edu/software/netcdf/.
- 3.Wu K, Otoo EJ, Shoshani A. “An efficient compression scheme for bitmap indices”. Technical Report LBNL-49626, Lawrence Berkeley National Laboratory, Berkeley, 2002.Google Scholar