Kaunas University of Technology  
 

s2o: SBVR to OWL 2 Converter - description

 
 

About the s2o converter

The s2o converter is a demonstration version of SBVR 1.2/1.3 to OWL 2 transformation tool, created as a part of the PhD research of Jaroslav Karpovič (a.k.a. Jaroslav Karpovic) with intention to prove that the SBVR vocabulary and rules are suitable for OWL 2 ontology creation.

Please be aware: this is the prototype only! The current version of the s2o converter does not cover all SBVR or OWL 2 concepts. There is no SBVR syntax highlighting in the demonstration version also, so validation of vocabulary and rules occurs only during transformation process. It is suggested to use external SBVR editors and to paste validated vocabularies and rules into the s2o converter.

Since its first public release on 15th of May 2014 s2o conversion tool is first online SBVR to OWL 2 converter.

The "s2o" name of SBVR to OWL 2 conversion tool is just even more shortened version of the commonly used in the scientific community abbreviation type (like "sbvr2uml", "bpmn2owl" etc.) for "sbvr2owl".

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Description of the transformation process

Please be aware that transformation process can take some time as it consists of several steps.

s2o: SBVR to OWL 2 transformation process

The figure above represents the process of SBVR to OWL 2 transformation: in the first step, SBVR XMI is created from the SBVR vocabulary and rules; then the SBVR XMI is transformed to the OWL 2 XMI using ATL transformation engine; finally, the OWL 2 XMI is transformed to the OWL 2 functional style syntax using XSLT transformation rules.

The proposed transformation rules and concept mapping can be found in the publications:

  1. Karpovič, Jaroslav; Nemuraitė, Lina. Analysis of possibilities for representing SBVR business vocabularies in Web Ontology Language. Proceedings of Master and PhD students conference on informatic: 15-osios tarpuniversitetinės magistrantų ir doktorantų konferencijos "Informacinė visuomenė ir universitetinės studijos" (IVUS 2010) medžiaga, 2010 m. gegužės 13 d, Kaunas, Lietuva / [Vytauto Didžiojo universitetas, Kauno technologijos universitetas, Vilniaus universitetas]. Kaunas: Vytauto Didžiojo universitetas. ISSN 2029-249X. 2011, nr. 15, p. 63-67.
  2. Karpovič, Jaroslav; Nemuraitė, Lina. Transforming SBVR business semantics into Web ontology language OWL2: main concepts. In Information Technologies' 2011: proceedings of the 17th international conference on Information and Software Technologies, IT 2011, Kaunas, Lithuania, April 27-29, 2011; Kaunas University of Technology. Kaunas: Technologija. ISSN 2029-0020. 2011, p. 231-238.
  3. Karpovič, Jaroslav; Nemuraitė, Lina; Stankevičienė, Milda. Requirements for semantic business vocabularies and rules for transforming them into consistent OWL 2 ontologies. In Information and software technologies: 18th International Conference, ICIST 2012, Kaunas, Lithuania, September 13-14, 2012: proceedings. Berlin, Heidelberg: Springer, 2012. (Communications in computer and information science, Vol. 319, ISSN 1865-0929). ISBN 9783642333071, p. 420-435.
  4. Karpovič, Jaroslav; Kriščiūnienė, Gintarė; Ablonskis, Linas; Nemuraitė, Lina. The Comprehensive Mapping of Semantics of Business Vocabulary and Business Rules (SBVR) to OWL 2 Ontologies. In Information Technology and Control, 43(3), IT&C 2014. ISSN: 1392-124X, p. 289-302.
  5. Karpovič, Jaroslav; Ablonskis, Linas; Nemuraitė, Lina; Paradauskas, Bronius. Experimental investigation of transformations from SBVR business vocabularies and business rules to owl 2 ontologies. In Information Technology and Control, 45(2), IT&C 2016. ISSN: 1392-124X, p. 195-207.

Second edition of OWL 2 Web Ontology Language was abbreviated as "OWL2" in the first publications of authors. "OWL 2" was used in the last publications as suggested by the W3C Consortium. Please consider "OWL 2" and "OWL2" abbreviations/terms as synonyms for Second Edition of OWL Web Ontology Language.

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Transformation examples (can be used as templates)

The example of SBVR vocabulary and rules from the photo equipment domain is presented for providing the brief outlook of the possibilities of the current prototype of transformation tool.

Please be aware: s2o SBVR to OWL2 transformation tool supports a lot more constructions than enclosed examples hold. The example list will be extended in the near future. Just try anything you need and check if it is supported by the s2o tool.

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Experiment

Several comprehensive examples can be used to better understand possibilities of the s2o converter:

  Lan-
guage
SBVR
vocabulary
SBVR
rules
OWL 2
ontology
OWL 2 ontology
instances
Photo equipment EN voc rules owl 2 inst. owl 2
Loan Contracts EN voc rules owl 2 inst. owl 2
Agentai (agents) LT voc rules owl 2 inst. owl 2
Ekonomika (economy) LT voc rules owl 2 inst. owl 2
Įvykiai (events) LT voc rules owl 2 inst. owl 2
Politika (politics) LT voc rules owl 2 inst. owl 2
SemLT LT voc rules owl 2 inst. owl 2
Viešas sektorius (public sector) LT voc rules owl 2 inst. owl 2
Vietovės (locations) LT voc rules owl 2 inst. owl 2


Please be aware: the attached ontologies are obtained using s2o SBVR to OWL 2 converter version 0.8 and your results may vary.

Also please take attention that not all example vocabularies have namespaces defined. s2o converter applies default namespaces (s2o) for ontologies in such cases. Opening instance ontology with the not-paired main ontology with the same namespace can lead to unpredictable results.

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Requirements for SBVR business vocabulary and business rules

SBVR vocabulary and rules should correctly represent a problem domain under consideration for transforming them into valid OWL 2 ontologies. Therefore, they should be created with regards to the following rules 1-3:
  • Primitive, non-inferable domain concepts should not have more than one primitive parent. Non-inferable generalization hierarchies of the domain should comprise homogeneous disjoint trees, where specializations are based on the same criteria. All sub-concepts of the same parent concept should be disjoint but not necessarily covering the parent whereas values are disjoint and value types may be disjoint or overlapping.
  • Each individual concept must be an instance of exactly one most specific self-standing primitive concept; business rules should be defined in such a way that inferences should never result in making individuals instances of several non-inferable concepts.
  • SBVR metamodel allows using the same preferred names for different concepts, e.g. for roles related via is_property_of verb concept with several general concepts. It means that a corresponding OWL 2 data property will have several domain classes. This will lead to undesirable classifications and inconsistencies during inference performed by ontology reasoners. The safe solution is to give unique preferred names, or purposely formulate right subsumption hierarchies for general concepts, roles, verb concepts, and verb concept roles for avoiding undesirable classifications.
_______________________________
  1. Rector, A.L. Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In John Genari, editor, Knowledge Capture 2003, Sanibel Island, FL, 2003. ACM, pp.121–128.
  2. Rector, A.L. Normalisation of ontology implementations: Towards modularity, re-use, and maintainability. In Proceedings Workshop on Ontologies for Multiagent Systems (OMAS) in conjunction with European Knowledge Acquisition Workshop, 2002.
  3. Nemuraite, L., Paradauskas, B. A methodology for engineering OWL 2 ontologies in practise considering their semantic normalisation and completeness. Electronics and Electrical Engineering, 2012, 4(120), 89-94.

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Vocabulary of SBVR metaconcepts

The additional vocabulary of SBVR metaconcepts, required by the SBVR to OWL 2 transformations, is imported automatically every time transformation is launched. The SBVR metaconcept vocabulary allows extending the SBVR without extension of the original SBVR metamodel. Concepts from the SBVR metaconcept vocabulary occur in the resulting OWL 2 ontology only if they are used in the domain vocabulary and rules under transformation.

The current SBVR metaconcept vocabulary includes concepts:

vocabulary
verb_concept
transitive_verb_concept
    General_concept: verb_concept
symmetric_verb_concept
    General_concept: verb_concept
asymmetric_verb_concept
    General_concept: verb_concept
reflexive_verb_concept
    General_concept: verb_concept
irreflexive_verb_concept
    General_concept: verb_concept
inverse_functional_verb_concept
    General_concept: verb_concept
functional_verb_concept
    General_concept: verb_concept
purely_reflexive_verb_concept
    General_concept: verb_concept
inverse_verb_concept
    General_concept: verb_concept
concept
characteristic
concept incorporates characteristic
concept is concept
concept is_a concept
something
thing
thing is thing

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About the authors / Acknowledgements

Several researchers are related to the creation of the SBVR to OWL 2 transformations.

Prof. Dr. Lina NemuraitėScientific supervisor and co-author.

Jaroslav KarpovičSBVR to OWL 2 transformation author, developer of the transformation chain (SBVR XMI -> OWL 2 XMI -> OWL 2 functional style syntax) and its demonstration prototype (current s2o SBVR to OWL 2 converter).

Algirdas ŠukysDeveloper of the SBVR Structured Language Editor and SBVR XMI generator, used in the SBVR to OWL 2 transformation chain.

ISD reserch teamResearch team of the Department of Information Systems (ISD) of Kaunas University of Technology (KTU), working in the field of ontologies and SBVR since 2008, and in the field of semantics and information systems since its establishment in 1993.

Jesper ZedlitzPerson who shown the right way for transformation from OWL XMI to OWL functional style syntax using XSLT transformation language.

I would like to express my great appreciation to everyone who contributed to this project.
Sincerely Jaroslav Karpovič (a.k.a. Jaroslav Karpovic)

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Source and Copyright (c) Jaroslav Karpovic, Algirdas Sukys, prof. dr. Lina Nemuraite.
Department of Information Systems, Kaunas University of Technology. 2009-2017
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