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A template-based approach for the specification of 3D topological constraints

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Abstract

Several different models have been defined in literature for the definition of 3D scenes that include a geometrical representation of objects together with a semantical classification of them. Such semantical characterization encapsulates important details about the object properties and behavior and often includes spatial relations that are defined only implicitly or through natural language, such as “an external access shall be in touch with the building only when it is classified as a direct access”. The problem of ensuring the coherence between geometric and semantic information is well known in literature. Many attempts exist which try to extent the OCL to allow the representation of spatial integrity constraints in an UML model. However, this approach requires a deep knowledge of the OCL formalism and the implementation of ad-hoc procedures to validate the constraints specified at conceptual level. Therefore, a new approach is needed that helps designers to define complex OCL constraints and at the same time allows the automatic generation of the code to test them on a given dataset. The aim of this paper is to propose a set of predefined templates to express on the classes of an UML data model, a family of 3D spatial integrity constraints based on topological relations; all this without requiring the knowledge of any formal language by domain experts and supporting their automatic translation into validation procedures.

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Authors and Affiliations

  1. Department of Computer Science, University of Verona, Verona, Italy

    Alberto Belussi & Sara Migliorini

  2. Department of Electronics, Information and Bioengineering, Politecnico of Milan, Milan, Italy

    Mauro Negri & Giuseppe Pelagatti

Authors
  1. Alberto Belussi
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  2. Sara Migliorini
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  3. Mauro Negri
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  4. Giuseppe Pelagatti
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Correspondence to Sara Migliorini.

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Belussi, A., Migliorini, S., Negri, M. et al. A template-based approach for the specification of 3D topological constraints. Geoinformatica 24, 683–712 (2020). https://doi.org/10.1007/s10707-020-00401-2

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  • DOI: https://doi.org/10.1007/s10707-020-00401-2

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