Contextual Partitioning for Comprehension of OODB Schemas

  • Authors:
  • Huanying Gu;Yehoshua Perl;James Geller;Erich J. Neuhold

  • Affiliations:
  • UMDNJ, Department of Health Informatics, USA;NJIT, Computer Science Department, USA;NJIT, Computer Science Department, USA;Darmstadt, Fraunhofer IPSI, Germany

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2004

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Abstract

Object-oriented databases (OODBs) have been utilized for complex modeling tasks within a variety of application domains. The OODB schema, typically expressed in a graphical notation, can serve as a useful presentation tool for the information contained in the underlying OODB. However, such a schema can be a large, complex network of classes and relationships. This may greatly hinder its effectiveness in helping users gain an understanding of the OODB’s contents and data organization. To facilitate this orientation process, a theoretical framework is presented that guides the refinement\/ of an existing schema’s subclass-of\/ relationship hierarchy – the backbone of any OODB. The framework sets forth three rules which, when satisfied, lead to the establishment of a collection of contexts, each of which exhibits an internal subclass-of\/ tree structure. A formal proof of this result is presented. An algorithmic methodology, involving a human–computer interaction, describes how the approach can be applied to a given OODB schema. An application of the methodology to an example OODB schema is included.