Descriptive data about taxa at one level of the taxonomic hierarchy may be inferred from representative data referable to another level. The process is bi-directional. Data agglomeration enables taxon characteristics to be derived from the characteristics of a subordinate level and data propagation enables taxon characteristics to be derived from the characteristics of a superior taxonomic level. This applies to any form of descriptive taxonomic data (e.g. morphological, cytological, distributional, uses, etc.) and at all levels of the taxonomic hierarchy. Examples taken from a revision for the production of DELTA format descriptions and distribution data are discussed. The major advantages of implementing these processes in a database system are: products and queries are based directly on representative data; they can be derived automatically from the data set without the necessary intervention of a taxonomist; less work is required to synthesize products or answer queries; there is greater guarantee of database integrity; data redundancy is reduced and thus storage space is conserved. The use of these processes should play a central part in any development of taxonomically intelligent database management systems.
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