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

Shashi ShekharContact Information, Ranga Raju Vatsavai5, 6 Contact Information, Sanjay ChawlaContact Information and Thomas E. BurkContact Information

(5)  Computer Science Department, University of Minnesota, EE/CS 4-192, 200 Union St. SE., Minneapolis, MN, 55455
(6)  Department of Forest Resources, University of Minnesota, 115 Green Hall, St. Paul, MN, 55108
Abstract
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.

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


Contact Information Shashi Shekhar
Email: shekhar@cs.umn.edu
URL: http://www.cs.umn.edu/research/shashi-group/

Contact Information Ranga Raju Vatsavai
Email: vatsavai@cs.umn.edu

Contact Information Sanjay Chawla
Email: chawla@cs.umn.edu

Contact Information Thomas E. Burk
Email: tburk@forestry.umn.edu
URL: http://terrasip.gis.umn.edu/
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  1. Gandhi, Vijay, 2008
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