Jean-Pierre Chanet

Agronomic taxon

In this paper, we describe the development of the first ontology module for observation of pest attacks in crop production. We applied the NeOn methodology and more particularly the ontology engineering method based on Ontology Design Pattern.

SKOS Sources Transformations for Ontology Engineering: Agronomical Taxonomy Use Case

Sources like thesauri or taxonomies are already used as input in ontology development process. Some of them are also published on the LOD using the SKOS format. Reusing this type of sources to build an ontology is not an easy task. The ontology developer has to face different syntax and different modelling goals. We propose in this paper a new methodology to transform several non-ontological sources into a single ontology. We take into account: the redundancy of the knowledge extracted from sources in order to discover the consensual knowledge and Ontology Design Patterns (ODPs) to guide the transformation process. We have evaluated our methodology by creating an ontology on wheat taxonomy from three sources: Agrovoc thesaurus, TaxRef taxonomy, NCBI taxonomy.

Les ontologies en agriculture

Les ontologies ont ete utilisees ces dernieres annees pour resoudre un certain nombre de problemes et en particulier pour ameliorer l’interoperabilite dans les systemes d’information. Les objectifs de cet article sont de presenter differents types d’ontologies utilisees en agriculture et d’expliquer comment les systemes d’information utilisent ces ontologies pour resoudre leurs problemes d’interoperabilite.

Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA System

We propose a method for building a knowledge base addressing specific issues such as covering end-users’ needs. After designing an ontology module representing the knowledge needed, we enrich and populate it automatically with knowledge extracted from existing sources such as thesauri or classifications. The originality of our proposition is to propose ontological object candidates from existing sources according to their relatedness to the ontological module and to their trust score. This paper describes the trust measures we propose which are obtained by analysing the consensus found in existing sources. We consider that knowledge is more reliable if it has been extracted from several sources. Our measures has been evaluated on a real case study with experts from the agriculture domain.

Dealing with Incompatibilities During a Knowledge Bases Fusion Process

More and more data sets are published on the linked open data. Reusing these data is a challenging task as for a given domain, several data sets built for specific usage may exist. In this article we present an approach for existing knowledge bases fusion by taking into account incompatibilities that may appear in their representations. Equivalence mappings established by an alignment tool are considered in order to generate a subset of compatible candidates. The approach has been evaluated by domain experts on datasets dealing with agriculture.