Ontology versus Database

Sir, Michal; Bradáč, Zdeněk; Fiedler, Petr

doi:10.1016/j.ifacol.2015.07.036

Cited by 31 publications

(23 citation statements)

References 2 publications

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“…Ontology can be theoretically based on FCA, but it is not absolutely necessary. The semantic richness of ontology is much more than that of relational database [5].…”

Section: Ontology Discovery Methods In Database Relationship Between Rmentioning

confidence: 99%

Relational Database Ontology Discovery Method Based on Formal Concept Analysis

Gao¹,

Liang²,

Qiao³

2017

Proceedings of the 3rd Annual International Conference on Mechanics and Mechanical Engineering (MME 2016)

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Abstract. This paper elaborates how to use the formal concept analysis method to map contents in the database to the ontology, in order to provide the big data application with high-quality data source by virtue of integrating the database with Semantic Web. In recent times, a mass of data is stored in the relational database, but such data with low share usage fails to play its full role. On account that the big data application has grown by leaps and bounds, a large number of shared data is urgently needed. By mapping the data in the relational database into the ontology, the technology of Semantic Web can provide a lot of semantic data to the big data application, which is conducive to big data analysis and use. In this paper, the ontology is built by taking the formal concept as the intermediate model and converting the logic structure of database into Hasse graph and context table, and then combining with the domain knowledge. The ontology in the knowledge domain can be found from the database by applying the formal concept analysis method, which takes full advantage of logical structure information of the database and is beneficial for automation found by the ontology. Eventually, ontology method and problems found in the relational database by virtue of the formal concept analysis are summarized herein..

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“…Ontology can be theoretically based on FCA, but it is not absolutely necessary. The semantic richness of ontology is much more than that of relational database [5].…”

Section: Ontology Discovery Methods In Database Relationship Between Rmentioning

confidence: 99%

Relational Database Ontology Discovery Method Based on Formal Concept Analysis

Gao¹,

Liang²,

Qiao³

2017

Proceedings of the 3rd Annual International Conference on Mechanics and Mechanical Engineering (MME 2016)

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“…The database is based on the relational model in the storage and retrieval of data and semantic concept is not important. Another difference is that the ontology reuses existing ones, while a new database must be created for each application domain [10]. Another point of difference lies in the way knowledge is represented: ontology uses the open world assumption, while the database operates on a closed world assumption [10].…”

Section: Comparison Between the Ontology And The Relational Databasementioning

confidence: 99%

OMU: An Ontology For Mosul University

Mustafa¹,

Adnan²

2020

AL-Rafidain Journal of Computer Sciences and Mathematics

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Nowadays, data from different real-time data streams are coming in. The classical relational database systems cannot manage such big data. Big data should be managed in a way that keeps the semantic relations between different concepts. Ontology is a powerful tool that comes from the concept of the semantic web, can formulate data schema as semantically connected objects. Ontology can be shared and reused across different domains and sites. In this paper, an ontology that captures the main concepts and their relationships in Mosul university is proposed. The main steps for OMU (ontology for Mosul University) development are showen using protégé ontology editor. Also, several queries are implemented to show how we can use inference engine to infer new and implicit knowledge from ontologies. visualization tools are used to visualize OMU ontology.

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“…Reiter, 1977 In practical terms, missing information in a database returns the value "0", while in ontology the lack of a data is considered an "unknown" value. (Sir et al, 2015) Other features are different between two methods, such as how to compile or the dependency of properties. There is several literatures on relational database, all these proposal have marked the lacks of relational database about semantic representation.…”

Section: Ontology Versus Databasementioning

confidence: 99%

Bim Process, Ontologies and Interchange Platform for Cultural Architectural Heritage Management: State of Art and Development Perspectives

Pili

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Ontology meaning and its declination in computer science are defined in the contribution. Some experiences of using ontologies for Cultural Heritage frame the state of the art. Specific ontologies for the conservation process allows the definition of classes and their description through attributes. Subjects, means, tools, relationships, and planning of activities, times and costs are included in the process. Ontologies so defined are also the basis for the definition of an interoperability protocol for Cultural Heritage. Interoperability means exchange among the tools, with the guarantee that data and meanings transmitted are correctly interpreted by the receiving system. The paper proposes the kind of informative model for built heritage. Defining the basis for ontologies is the goal. The flow of information in a Common Data Environment, a data exchange platform, is necessary to ensure proper data and process management.

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Ontology versus Database

Cited by 31 publications

References 2 publications

Relational Database Ontology Discovery Method Based on Formal Concept Analysis

Relational Database Ontology Discovery Method Based on Formal Concept Analysis

OMU: An Ontology For Mosul University

Bim Process, Ontologies and Interchange Platform for Cultural Architectural Heritage Management: State of Art and Development Perspectives

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