Qualitative causal modeling in temporal GIS

  • Eric Allen
  • Geoffrey Edwards
  • Yvan Bédard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 988)

Abstract

A generic model for explicitly representing causal links within a spatiotemporal GIS is presented. The current litterature on causal modeling within the fields of geomatics, computer science and geography, is surveyed. The contributions of several major philosophers to the theory of causality are also briefly summarised. Based on the lessons extracted from such earlier work, the elements of the new model are presented. The model consists of a small number of elements which are presented via a conceptual data model using an extended Entity-Relationship formalism. These elements include the following entities — Objects and their States, Events, Agents, and Conditions — as well as the relations Produces, Is Part Of, Conditions. Both objects and events may have spatial representations, and all entities may have temporal representations. The model is simple but hierarchical. A specific means of modeling uncertainty has been included in the development of the model. An example of the model proposed applied to data related to environmental impact assessment is shown, using a formal visual language designed to help understand the linkages implicit in the model. Furthermore, the relative strengths and weaknesses of the model are outlined and its relationship to previous work is also discussed.

Key words

causality temporal GIS events databases models simulation object-oriented design uncertainty 

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Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Eric Allen
    • 1
    • 2
  • Geoffrey Edwards
    • 1
    • 2
  • Yvan Bédard
    • 1
  1. 1.Chaire industrielle en géomatique appliquée à la foresterieCanada
  2. 2.Centre de recherche en géomatiqueUniversité LavalSainte-Foy

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