Ecological Networks (ENs) are a way to describe the structures of existing real ecosystems and to plan their expansion, conservation and improvement. In this work, we present a model to represent the specifications for the local planning of ENs in a way that can support reasoning, e.g., to detect violations within new proposals of expansion, or to reason about improvements of the networks. Moreover, we describe an OWL ontology for the representation of ENs themselves. In the context of knowledge engineering, ENs provide a complex, inherently geographic domain that demands for the expressive power of a language like OWL augmented with the GeoSPARQL ontology to be conveniently represented. More importantly, the set of specification rules that we consider (taken from the project for a local EN implementation) constitute a challenging problem for representing constraints over complex geographic domains, and evaluating whether a given large knowledge base satisfies or violates them.

Representing Ecological Network Specifications with Semantic Web Techniques

G. Torta;L. Ardissono;A. Savoca;
2017-01-01

Abstract

Ecological Networks (ENs) are a way to describe the structures of existing real ecosystems and to plan their expansion, conservation and improvement. In this work, we present a model to represent the specifications for the local planning of ENs in a way that can support reasoning, e.g., to detect violations within new proposals of expansion, or to reason about improvements of the networks. Moreover, we describe an OWL ontology for the representation of ENs themselves. In the context of knowledge engineering, ENs provide a complex, inherently geographic domain that demands for the expressive power of a language like OWL augmented with the GeoSPARQL ontology to be conveniently represented. More importantly, the set of specification rules that we consider (taken from the project for a local EN implementation) constitute a challenging problem for representing constraints over complex geographic domains, and evaluating whether a given large knowledge base satisfies or violates them.
2017
KEOD - Int. Conf. on KnowledgeEngineering and Ontology Development
Funchal, Madeira, Portugal
1-3/11-2017
Proc. of Joint Conf. on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017)
SCITEPRESS - Science and Technology Publications, Lda.
2
86
97
978-989-758-272-1
http://www.insticc.org/primoris/node/TechnicalProgram/ic3k/presentationDetails/65735
Geographic Knowledge, Geographical Constraints, GeoSPARQL, Ecological Networks, Urban Planning
Torta, Gianluca; Ardissono, Liliana; La Riccia, L.; Savoca, Adriano; Voghera, A.
File in questo prodotto:
File Dimensione Formato  
keod-2017-copertina.pdf

Accesso aperto

Descrizione: Articolo principale
Tipo di file: PDF EDITORIALE
Dimensione 735.21 kB
Formato Adobe PDF
735.21 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1651404
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? ND
social impact