Various regional agencies record spatial data continuously at fixed time intervals, such as hourly, daily, monthly, and annually. This type of data collection is referred to as a recurrent spatial data collection. The author of this paper reports experiences from the implementation of a recurrent spatial knowledge base for traffic analysis. A database, a function library, and a procedure collection comprise the knowledge base. Knowledge is retrieved directly from the database or calculated using functions from the function library. Procedures stored in the procedure collection can be used for statistical and artificial intelligence analysis. The knowledge base organization is transparent to its users. A scientific analysis language is used to provide a spreadsheet-like interface for the knowledge base. Choosing a suitable data model for the database and its design and implementation is discussed at length. The discussion revolves around issues such as knowledge retrieval, access time, and storage requirements. Some argue that the NF2 relational model offers a better data model for representing the recurrent spatial hierarchy than the relational model. It is found that in terms of access time and storage requirements, the NF2 model is more efficient.


  • English

Media Info

  • Features: Appendices; Figures; References; Tables;
  • Pagination: p. 50-59
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00716515
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 24 1996 12:00AM