In this thesis we have created a mechanism by which users can represent documents in a natural and expandable fashion. We have determined the nature of documents in terms of document state, and creating a data model to represent this state within Haystack. Furthermore we have shown the system context in which this data model resides.
Through Haystack a user is now capable of indexing documents in a powerful fashion. Haystack heuristically extracts a variety of information properties from the document and indexes those through a number of means.
We have also shown that information systems individually are incapable of answering the full set of questions a user may ask. Databases provide us with ``what you ask for is what you get'' functionality. Information Retrieval systems attempt to extract semantic meaning in textual documents. Finally, associative information systems facilitate the creation (both manual and automatic) of associations between documents. In combination these information systems are capable of handling the full spectrum of user queries.
In this thesis we have described mechanism to convert Haystack's internal data model to each of these systems.