Preserving Semantics of Owl 2 Ontologies in Relational Databases Using Hybrid Approach

Vyšniauskas, Ernestas; Nemuraite, Lina; Paradauskas, Bronius

doi:10.5755/j01.itc.41.2.833

Cited by 7 publications

(12 citation statements)

References 24 publications

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“…Consequently, for checking the consistency of ontology, we need to have an ontology model with the set of individuals sufficient for verifying the satisfiability of all axioms of the ontology. The methodology for engineering ontologies, normalization of ontology schemas and checking their consistency, as well as estimation of the required number of individuals for that purpose, was analysed in our previous work [26], which in turn is based on the works of eminent researchers in the field of ontology engineering. Shortly, we need to have a sufficient number of individuals for each primitive (non-inferable) class in order to compute all inferable classifications; a sufficient number of assertions for each property, which can be possessed by corresponding individuals, and a sufficient number of data values for each data property for computing all restrictions, classifications and realizations.…”

Section: Evaluation Of Sbvr To Owl 2 Transformation: Methodology and mentioning

confidence: 99%

“…Therefore, it is difficult to choose the best transformation rules as well as to compare existing solutions. On the base of analysed methodologies for conceptual modelling [10], [19], ontology engineering [20], [21], [22], [23], and our previous works [24], [25], [26], we have stated the following criteria for the SBVR to OWL 2 transformation:…”

Section: Introductionmentioning

confidence: 99%

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Experimental Investigation of Transformations From SBVR Business Vocabularies and Business Rules to Owl 2 Ontologies

Karpovic¹,

Ablonskis²,

Nemuraite³

et al. 2016

ITC

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The goal of the paper is to analyse the relevance of the proposed transformation from business vocabularies and business rules, based on Semantics of Business Vocabulary and Business Rules (SBVR), to the corresponding OWL 2 ontologies. The transformation was aimed to be model driven, lossless and reversible; adaptable to English, Lithuanian and other similar natural languages; covering transformable SBVR concepts and as much as possible OWL 2 concepts, especially those that are important for inference, and supporting the consistency and normalization of resulting ontologies. The paper presents a detailed comparison of the proposed solution with the most advanced, to our knowledge, related works and the experimental investigation of the implemented transformation prototype with nine SBVR business vocabularies and business rule sets with regards to the defined desirable criteria.

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Section: Evaluation Of Sbvr To Owl 2 Transformation: Methodology and mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Transformations From SBVR Business Vocabularies and Business Rules to Owl 2 Ontologies

Karpovic¹,

Ablonskis²,

Nemuraite³

et al. 2016

ITC

Self Cite

View full text Add to dashboard Cite

show abstract

“…Only a few from the tools support bi-directional transformations, e.g. [19] (OWL2 -relational database translations).…”

Section: Related Workmentioning

confidence: 99%

“…As reusable assets, they have many possible practical applications, also in the area of software engineering, e.g. for domain knowledge extraction [6], database design [19], or source code generation [17]. They can be effectively used in all stages of software development, from requirement specification through analysis, design and implementation to testing.…”

Section: Introductionmentioning

confidence: 99%

Universal Framework for OWL2 Ontology Transformations

Hnatkowska

Woroniecki²

2018

Foundations of Computing and Decision Sciences

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Domain ontologies are valuable knowledge assets with many potential applications, e.g. in software engineering. Their content is often a subject of bi-directional transformations. Unfortunately, a centralized transformation service which can be easily extended with new mappers is not available for ontology users. In consequence, they have to deal with many different translation programs, which have to be installed and learned separately. The paper presents a framework for universal ontology processing, dedicated to ontologies expressed in OWL2. The framework usefulness was verified by a proof-of-concept implementation, for which an existing OWL2 to Groovy translator was adapted. During the integration process, the translator functionality was enhanced with ontology individuals mapping. The exemplary implementation confirmed that the framework with plug-in architecture is flexible and easy for customization. The ontology stakeholders should benefit from the reduced cognitive load and more satisfying transformation process.

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“…Ouyang Dan-tong et al, [9] presents a set of constraint axioms called IC-mapping axioms, based on these a special Ontology with integrity constraint, which is adapted to map Ontology knowledge to data in relational databases. Ernestas Vysniauskas et al, [10] proposed an algorithm and generates a tool for transformation of domain Ontology described in OWL to RDB. Guntars Bumans [11] Mapping engine relational tables can be processed using SQL to generate RDF triples for OWL class and property instances.…”

Section: Related Workmentioning

confidence: 99%

A framework for OWL DL based Ontology Construction from Relational Database using Mapping and Semantic Rules

Ramathilagam¹,

Valarmathi²

2013

IJCA

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World Wide Web (WWW) is capable of retrieving the results only through location finding of search terms, where as Semantic web retrieves by analysing the keywords because of the machine accessible nature of semantic data. One such Semantic data format is Ontology. Ontologies are the web documents generated by Web Ontology Language to provide more precise web content, thus by improving the performance of information retrieval. Semantic web requires data either in terms of manual creation or through conversion from existing data. Ontologies lack semantically rich data because the manual construction of these documents are time consuming and also the domain experts need to understand the syntax and semantics of Ontology development languages. One alternate to compensate for the rich set of data is to take the contents of Relational Data Base (RDB) for domain related applications in the Semantic Web. This is possible by mapping the RDB constructs into Ontology constructs. This paper proposes an RDB to Ontology mapping system framework which can generate an Ontology based on the proposed Mapping Rules for a Banking domain. The Mapping rules are generated both for, 1) direct mapping 2) integrity constraints mapping. Direct mapping is, RDB components like table, attribute, data are mapped to the corresponding Ontology components. Integrity constraints mapping covers primary key, foreign key and column constraints mapped to the relevant Ontology components. This is the direct translation of RDB structure. This paper also proposes additional Semantic Rules for the generated Ontology to provide richer semantics. This in turn provides more expressiveness in Ontology representation and also efficient reasoning power.

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Preserving Semantics of Owl 2 Ontologies in Relational Databases Using Hybrid Approach

Cited by 7 publications

References 24 publications

Experimental Investigation of Transformations From SBVR Business Vocabularies and Business Rules to Owl 2 Ontologies

Experimental Investigation of Transformations From SBVR Business Vocabularies and Business Rules to Owl 2 Ontologies

Universal Framework for OWL2 Ontology Transformations

A framework for OWL DL based Ontology Construction from Relational Database using Mapping and Semantic Rules

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