Spatial Pictogram Enhanced Conceptual Data Models and Their Translation to Logical Data Models

  • Shashi Shekhar
  • Ranga Raju Vatsavai
  • Sanjay Chawla
  • Thomas E. Burk
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1737)


The successful development of any geographic information system project needs the careful design and implementation of spatial databases via conceptual and logical data-modeling. This involves understanding the underlying spatial data model, spatial data types and operators, spatial query languages and spatial indexing techniques. Conventional entity relationship diagrams have limitations for conceptual spatial data-modeling, since they get cluttered with numerous spatial relationships. In addition the logical data model gets cluttered with redundant tables representing materialization of the M:N spatial relationships. In this paper we present an extension to ER diagrams using pictograms for entities and as well as relationships. This approach effectively reduces the cluttering, as spatial relationships will become implicit. We have provided a complete grammar using “yacc” like syntax to translate the pictogram-extended ER diagram into a SQL3-level logical data model using OGIS-standard spatial data types.


Spatial Databases Pictograms SQL3 OGIS Entity-Relationship Diagrams UML Syntax Directed Translation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Shashi Shekhar
    • 1
  • Ranga Raju Vatsavai
    • 1
    • 2
  • Sanjay Chawla
    • 1
  • Thomas E. Burk
    • 2
  1. 1.Computer Science DepartmentUniversity of MinnesotaMinneapolis
  2. 2.Department of Forest ResourcesUniversity of MinnesotaSt. Paul

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