Querying database knowledge

ABSTRACT

The role of database knowledge is usually limited to the evaluation of data queries. In this paper we argue that when this knowledge is of substantial volume and complexity, there is genuine need to query this repository of information. Moreover, since users of the database may not be able to distinguish between information that is data and information that is knowledge, access to knowledge and data should be provided with a single, coherent instrument. We provide an informal review of various kinds of knowledge queries, with possible syntax and semantics. We then formalize a framework of knowledge-rich databases, and a simple query language consisting of a pair of retrieve and describe statements. The retrieve statement is for querying the data (it corresponds to the basic retrieval statement of various knowledge-rich database systems). The describe statement is for querying the knowledge. Essentially, it inquires about the meaning of a concept under specified circumstances. We provide algorithms for evaluating sound and finite knowledge answers to describe queries, and we demonstrate them with examples.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.4 Systems
          Subjects: Query processing

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.1 Logical Design
          Subjects: Data models
      H.2.3 Languages
          Subjects: Query languages

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

General Terms:
Algorithms, Design, Languages