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

Abstract

Semantic web rule language (SWRL) combines web ontology language (OWL) ontologies with horn logic rules of the rule markup language (RuleML) 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.

Enhancing Forest Fire Risk Assessment: An Ontology-Based Approach with Improved Continuous Apriori Algorithm

“…Ontology Web Language (OWL) is an ontology expression language recommended by The World Wide Web Consortium (W3C) [28], and Semantic web rule language (SWRL) is a rule expression language built on the OWL language [29]. By combining SWRL and OWL, rule-based automated reasoning has been achieved to support forest fire risk assessment.…”

An Agent-Based Social Simulation for Citizenship Competences and Conflict Resolution Styles

“…Our extension was inspired by the work by (Polhill, 2015), who developed a NetLogo extension that allows extracting ontologies from simulations based on NetLogo. The queries to the ontology are executed using SPARQL (Bassiliades, 2020).…”

Inferencing Relational Database Tuning Actions with OnDBTuning Ontology

“…It is supported by widespread tools such as ontology editors, rule engines, and ontology reasoners. However, it has never become a W3C recommendation [Bassiliades 2020].…”

“…According to [Bassiliades 2020], SPIN is a de-facto industry standard to represent rules and constraints on the Semantic Web, built based on the SPARQL query language, commonly used for querying and processing Linked Open Data. SPIN specification 5 defines a vocabulary as a collection of RDF properties to represent SPARQL queries as RDF triples.…”

“…Moreover, SPARQL could be more expressive than SWRL since it offers operators such as FILTER, OPTIONAL, UNION, and the possibility of defining new functions and templates in SPIN, besides spin built-in functions. Another feature is related to the performance of the rule engines: with SPIN, the rules are checked when new instances or changes occur, while in SWRL we need to check all the rules at each execution [Bassiliades 2020].…”