The work on data bases has been very much concerned with a concept called data independence. The aim of this work is to enable programs to be written independently of the logical structure of the data they would interact with. The independence takes the following form, should the file structure overnight be changed from an inverted to a serial file the program should remain unaffected. This independence is achieved by interposing a data model between the user and the data base. The user sees the data model rather than the data base, and all his programs communicate with the model. The user therefore has no interest in the structure of the file.

There is a school of thought that says that says that applications in library automation and information retrieval should follow this path as well[6,7]. And so it should. Unfortunately, there is still much debate about what a good data model should look like. Furthermore, operational implementations of some of the more advanced theoretical systems do not exist yet. So any suggestion that an IR system might be implemented through a data base package should still seem premature. Also, the scale of the problems in IR is such that efficient implementation of the application still demands close scrutiny of the file structure to be used.

Nevertheless, it is worth taking seriously the trend away from user knowledge of file structures, a trend that has been stimulated considerably by attempts to construct a theory of data[8,9]. There are a number of proposals for dealing with data at an abstract level. The best known of these by now is the one put forward by Codd[8], which has become known as the relational model. In it data are described by n-tuples of attribute values. More formally if the data is described by relations, a relation on a set of domains D1, . . . , Dn can be represented by a set of ordered n-tuples each of the form (d1, . . . , dn) where di [[propersubset]] Di. As it is rather difficult to cope with general relations, various levels (three in fact) of normalisation have been introduced restricting the kind of relations allowed.

A second approach is the hierarchical approach. It is used in many existing data base systems. This approach works as one might expect: data is represented in the form of hierarchies. although it is more restrictive than the relational approach it often seems to be the natural way to proceed. It can be argued that in many applications a hierarchic structure is a good approximation to the natural structure in the data, and that the resulting loss in precision of representation is worth the gain in efficiency and simplicity of representation.

The third approach is the network approach associated with the proposals by the Data Base Task Group of CODASYL. Here data items