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2019 | OriginalPaper | Chapter

GeCoLan: A Constraint Language for Reasoning About Ecological Networks in the Semantic Web

Authors : Gianluca Torta, Liliana Ardissono, Marco Corona, Luigi La Riccia, Adriano Savoca, Angioletta Voghera

Published in: Knowledge Discovery, Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

Ecological Networks (ENs) describe the structure of existing real ecosystems and help planning their expansion, conservation and improvement. While various mathematical models of ENs have been defined, to our knowledge they focus on simulating ecosystems, but none of them deals with verifying whether any transformation proposals, as those collected in participatory decision-making processes for public policy making, are consistent with land usage restrictions.

As an attempt to fill this gap, we developed a model to represent the specifications for the local planning of ENs in a way that can support both the detection of constraint violations within new proposals of expansion, and the reasoning about improvements of the networks. In line with the GeoSpatial Semantic WEB, our model is based on an OWL ontology for the representation of ENs. Moreover, we define a language, GeCoLan, supporting constraint-based reasoning on semantic data. Even though this paper focuses on EN validation, our language can be employed to enable more complex tasks, such as the generation of proposals for improving ENs.

The present paper describes our ontological specification of ENs, the GeCoLan language for reasoning about specifications, and the tools we developed to support data acquisition and constraint verification on ENs.

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Title: GeCoLan: A Constraint Language for Reasoning About Ecological Networks in the Semantic Web
Authors: Gianluca Torta
Liliana Ardissono
Marco Corona
Luigi La Riccia
Adriano Savoca
Angioletta Voghera
Publisher: Springer International Publishing
Book: Knowledge Discovery, Knowledge Engineering and Knowledge Management
Print ISBN: 978-3-030-15639-8

Electronic ISBN: 978-3-030-15640-4

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-15640-4_14

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