An Essay on the Role and Evolution of Data(base) Semntics

Abstract

ion by which the real world may be observed and the simplicity of the resulting representation, both in domain modeling and in functional specification of the system to be built [Ke78] [So84]. An immediate consequence is that system designers and builders must be able to place perfect trust in the — now implicit— agreements on correct implementations of those primitives. Note that this is exactly what we do when we trust e.g. the computer hardware to add and multiply accurately, or the DBMS to store facts correctly. In [ISO82/90] one may find an early description of a layered modeling architecture (the onion model, albeit without implementation!) that could result from this, where each higher layer uses the primitives and constructions of its underlying layers. Any analytic treatment so far however leads to tough problems in commonsense reasoning, see for example [GO94]. We have repeatedly introduced the external observers as the necessary intelligent agents of the agreement (e.g. under the form of axioms) without which no sensible starting point exists for a realworld semantics definition. (Some mathematicians of the Platonic persuasion might disagree with this.) The problem in practice is, that these agreements, while usually well-behaved locally, i.e. within one system or system component, need be static nor even consistent on a global system level. This latter aspect becomes especially apparent when we need to connect heterogeneous autonomous systems with the purpose of interoperation. A well-known seemingly trivial example of this problem is captured by what is sometimes called Schoenmaker's Conundrum [Scho86], in which (simplified here for brevity) one witness only tells a judge but keeps to himself that not q , while a second witness independently only tells the judge if p then q but also keeps to herself that not q. Each witness is consistent, but the judge is able to derive q, supposedly thereby hanging a hapless victim. Finally, relatively few research results are available on the methodological and formal problems that arise when groups of fallible and individually motivated agents/observers need to reach agreements — on which important design decisions will be taken. Each of observers in fact may define its own version of the real world, as we have seen necessarily consistent with others. It is even entirely possible that the same individual agent agrees on opposite facts depending on the she participates in, making a workable definition of group logic quite hard. Some work in distributed AI, e.g. [Mo90] may however prove relevant here.