queries and/or Datalog programs. Then we compare the approaches taken by AT&T Labs' "Information Manifold" and the Stanford "Tsimmis"; project in these terms.

A new kind of data model has recently emerged in which the database is not constrained by a conventional schema. Systems like ACeDB, which has become very popular with biologists, and the recent Tsimmis proposal for data integration organize data in tree-like structures whose components can be used

and are discussed briefly at the end of this abstract. For the following description of the TSIMMIS architecture refer to Figure 1. Translators and Common Model where the string "temp-in-Fahrenheit"; is a humanreadable label, the type "int"; indicates an integer value, and "80&quot

The tsimmis project [2] provides an architecture and tools for accessing multiple heterogeneous information sources by translating source information into a common self-describing object model, called the Object Exchange Model (OEM) [3]. tsimmis provides integrated access to heterogeneous sources

languages designed for well structured data are inappropriate in such environments. Starting with a "lightweight"; object model adopted for the TSIMMIS project at Stanford, in this paper we describe a query language and object repository designed specifically for semistructured data. Our language

the data should be "packaged"; into objects. We have implemented the Web extractor using the Python programming language stressing efficiency and ease-of-use. We also describe various ways of improving the functionality of our current prototype. The prototype is installed and running