Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T08:23:14.460Z Has data issue: false hasContentIssue false
  • English
  • Français

Re-grouping information in a domain-theoretic data model

Published online by Cambridge University Press:  01 February 1998

HERMANN PUHLMANN
HERMANN PUHLMANN
Affiliation:
Fachbereich Mathematik, Technische Hochschule Darmstadt, D-64289 Darmstadt, Germany
Get access Rights & Permissions [Opens in a new window]

Abstract

In recent years, the problem of incorporating a set-building type-constructor into a domain theoretic data model has been addressed by different authors. In Jung and Puhlmann (1995) and Puhlmann (1995) we have shown why the so-called snack powerdomain is particularly suitable for modelling a set constructor. We obtain a generalized database model that covers the nested relational model.

While, with the snack powerconstruction, the data structure of domain theoretic databases seems clear, suitable operations for the data model are still to be defined.

In this paper we start this task by defining the operations nest and unnest for the passage between different nesting-levels of the snack powerconstruction. These functions are shown to form an embedding-projection pair, a property that the corresponding functions of nested relational databases do not have. This demonstrates the usefulness of the domain-theoretic approach for modelling databases: for the first time we have operators for re-grouping nested data that respect the idea of an information ordering.

The use of the snack powerdomain leads to fairly complex formulas. To help the reader, illustrations and pictorial interpretations of formulas are given throughout the paper.

Type
Research Article
Information
Mathematical Structures in Computer Science , Volume 8 , Issue 1 , February 1998 , pp. 67 - 92
Copyright
1998 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)