Managing heterogeneous information systems through discovery and retrieval of generic concepts

• Published in: Journal of the American Society for Information Science 2000, Vol.51 (8), p.707-723
• Main Authors: Srinivasan, Uma, Ngu, Anne H.H., Gedeon, Tom
• Format: Article
• Language: English
• Subjects: Academic Achievement; Algorithms; Artificial intelligence; Cluster Based Retrieval; Computer architecture; Computer science; Concept Mapping; Conceptual Integration; Data Mining; Database Management Systems; Exact sciences and technology; Generic concepts; Heterogeneous data; Information and communication sciences; Information management; Information processing and retrieval; Information Retrieval; Information retrieval. Man machine relationship; Information science. Documentation; Information Systems; Knowledge; Legacy systems; Management Systems; Metadata; Object oriented programming; Online information retrieval; Reengineering; Research process. Evaluation; Sciences and techniques of general use; Searching; Semantics; Semiotics; Use statistics; User groups
• ISSN: 0002-8231; 2330-1635; 1097-4571; 2330-1643
• DOI: 10.1002/(SICI)1097-4571(2000)51:8<707::AID-ASI30>3.0.CO;2-C

Autonomy of operations combined with decentralized management of data gives rise to a number of heterogeneous databases or information systems within an enterprise. These systems are often incompatible in structure as well as content and, hence, difficult to integrate. Depsite heterogeneity, the unity of overall purpose within a common application domain, nevertheless, provides a degree of semantic similarity that manifests itself in the form of similar data structures and common usage patterns of existing information systems. This article introduces a conceptual integration approach that exploits the similarity in metalevel information in existing systems and performs metadata mining on database objects to discover a set of concepts that serve as a domain ion and provide a conceptual layer above existing legacy systems. This conceptual layer is further utilized by an information reengineering framework that customizes and packages information to reflect the unique needs of different user groups within the application domain. The architecture of the information reengineering framework is based on an object‐oriented model that represents the discovered concepts as customized application objects for each distinct user group.