A Tool for Transforming Semantic Web Rule Language to SPARQL Infererecing Notation

被引:6
作者
Bassiliades, Nick [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Informat, Thessaloniki, Greece
关键词
Ontologies; OWL; Prolog; Rules; Semantic Web; SPARQL; SPIN; SWRL; Transformation; SWRL RULES; OWL-DL; SYSTEM;
D O I
10.4018/IJSWIS.2020010105
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Semantic web rule language (SWRL) combines web ontology language (OWL) ontologies with horn logic rules of the rule markup language (Ru1eML) family. Being supported by ontology editors, rule engines and ontology reasoners, it has become a very popular choice for developing rule-based applications on top of ontologies. However, SWRL is probably not going to become a WWW Consortium standard, prohibiting industrial acceptance. On the other hand, SPARQL Inferencing Notation (SPIN) has become a de-facto industry standard to represent SPARQL rules and constraints on semantic web models, building on the widespread acceptance of SPARQL (SPARQL Protocol and RDF Query Language). In this article, we argue that the life of existing SWRL rule-based ontology applications can be prolonged by converting them to SPIN. To this end, we have developed the SWRL2SPIN tool in Prolog that transforms SWRL rules into SPIN rules, considering the object-orientation of SPIN, i.e. linking rules to the appropriate ontology classes and optimizing them, as derived by analysing the rule conditions.
引用
收藏
页码:87 / 115
页数:29
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