Rapid Benchmarking for Semantic Web Knowledge Base Systems

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.

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Domain Ontology, an Instrument of Semantic Web Knowledge Management in e-Learning

International Journal of Advanced Corporate Learning (iJAC) ◽

10.3991/ijac.v5i4.2288 ◽

2012 ◽

Vol 5 (4) ◽

Cited By ~ 2

Author(s):

Anatoly Jasonovich Gladun ◽

Julia Vitalijevna Rogushina ◽

Jeanne Schreurs

Keyword(s):

Knowledge Management ◽

Semantic Web ◽

Domain Ontology ◽

E Learning ◽

Web Knowledge

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Meta-Programming for Knowledge Base Systems

Wissensbasierte Systeme - Informatik-Fachberichte ◽

10.1007/978-3-642-75182-0_2 ◽

1989 ◽

pp. 12-16 ◽

Cited By ~ 1

Author(s):

J. W. Lloyd

Keyword(s):

Knowledge Base ◽

Meta Programming ◽

Knowledge Base Systems

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SWRLx

Information Retrieval and Management ◽

10.4018/978-1-5225-5191-1.ch016 ◽

2018 ◽

pp. 348-367

Author(s):

Souad Bouaicha ◽

Zizette Boufaida

Keyword(s):

Semantic Web ◽

Knowledge Base ◽

Object Oriented ◽

Web Ontology Language ◽

Rule Engine ◽

Ontology Language ◽

New Knowledge ◽

Semantic Web Rule Language

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.

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