1 research outputs found
Evaluation of Functional Data Models for Database Design and Use
The problems of design, operation, and maintenance of databases using the three most
popular database management systems (Hierarchical, CQDASYL/DBTG, and Relational) are
well known. Users wishing to use these systems have to make conscious and often complex
mappings between the real-world structures and the data structuring options (data models)
provided by these systems. In addition, much of the semantics associated with the data
either does not get expressed at all or gets embedded procedurally in application programs in
an ad-hoc way.
In recent years, a large number of data models (called semantic data models) have been
proposed with the aim of simplifying database design and use. However, the lack of usable
implementations of these proposals has so far inhibited the widespread use of these concepts.
The present work reports on an effort to evaluate and extend one such semantic model by
means of an implementation. It is based on the functional data model proposed earlier by
Shipman[SHIP81). We call this 'Extended Functional Data Model' (EFDM).
EFDM, like Shipman's proposals, is a marriage of three of the advanced modelling concepts
found in both database and artificial intelligence research: the concept of entity to represent
an object in the real world, the concept of type hierarchy among entity types, and the
concept of derived data for modelling procedural knowledge. The functional notation of the
model lends itself to high level data manipulation languages. The data selection in these
languages is expressed simply as function application. Further, the functional approach makes
it possible to incorporate general purpose computation facilities in the data languages without
having to embed them in procedural languages. In addition to providing the usual database
facilities, the implementation also provides a mechanism to specify multiple user views of the
database