Large organizations need to exchange information among many separately-developed systems. In order for this exchange to be useful, the individual systems must agree on the meaning of their exchanged data. That is, the organization must ensure semantic interoperability. This paper provides a theory of semantic values as a unit of exchange that facilitates semantic interoperability between heterogeneous information systems. We show how semantic values can either be stored explicitly or defined by environments. A system architecture is presented that allows autonomous components to share semantic values. The key component in this architecture is called the context mediator, whose job is to identify and construct the semantic values being sent, determine when the exchange is meaningful, and convert the semantic values to the form required by the receiver. Our theory is then applied to the relational model. We provide an interpretation of standard SQL queries in which context conversions and manipulations occur completely transparently to the user. We also introduce an extension of SQL, called Context-SQL (C-SQL), in which the context of a semantic value can be accessed and updated explicitly. Finally, we describe the implementation of a prototype context mediator for a relational C-SQL system.

to The use of inference rules to support intelligent data processing is an increasingly important tool in many areas of computer science. In database systems, rules are used in semantic query optimization as a method for reducing query processing costs. The savings is dependent on the ability of experts to supply a set of useful rules and the ability of the optimizer to quickly find the appropriate transformations generated by these rules. Unfortunately, the most useful rules are not always those that would or could be specified by an expert. This paper describes the architecture of a system having two interrelated components: a combined conventional/semantic query optimizer, and an automatic rule deriver.Our automatic rule derivation method uses intermediate results from the optimization process to direct the search for learning new rules. Unlike a system employing only user-specified rules, a system with an automatic capability can derive rules that may be true only in the current state of the database and can modify the rule set to reflect changes in the database and its usage pattern.This system has been implemented as an extension of the EXODUS conventional query optimizer generator. We describe the implementation, and show how semantic query optimization is an extension of conventional optimization in this context.

Specialization hierarchies typically are treated as type-level constructs and are used to define various inheritance mechanisms. In this paper we consider specialization at the level of objects. We show that doing so creates a more flexible and powerful notion of inheritance by allowing objects to define their own inheritance path. Object specialization can also be used to model certain forms of versioning, implement data abstraction, and provide a "classless" prototype-based language interface to the user.

Abstract. Many database applications require the storage and manipulation of different versions of data objects. To satisfy the diverse needs of these applications, current database systems support versioning at a very low level. This article demonstrates that application-independent versioning can be supported at a significantly higher level. In particular, we extend the EXTRA data model and EXCESS query language so that configurations can be specified conceptually and non-procedurally. We also show how version sets can be viewed multidimensionally, thereby allowing configurations to be expressed at a higher level of abstraction. The resulting model integrates and generalizes ideas in CAD systems, CASE systems, and temporal databases.

We extend SQL's grant/revoke model to handle all administration of permissions in a distributed database. The key idea is to "factor" permissions into simpler decisions that can be administered separately, and for which we can devise sound inference rules. The model enables us to simplify administration via separation of concerns (between technical DBAs and domain experts), and to justify fully automated inference for some permission factors. We show how this approach would coexist with current practices based on SQL permissions.