Database Semantic Interoperability based on Information Flow Theory and Formal Concept Analysis

Guanghui Yang, Junkang Feng

Research output: Contribution to journalArticle

Abstract

As databases become widely used, there is a growing need to translate information between multiple databases. Semantic interoperability and integration has been a long standing challenge for the database community and has now become a prominent area of database research. In this paper, we aim to answer the question how semantic interoperability between two databases can be achieved by using Formal Concept Analysis (FCA for short) and Information Flow (IF for short) theories. For our purposes, firstly we discover knowledge from different databases by using FCA, and then align what is discovered by using IF and FCA. The development of FCA has led to some software systems such as TOSCANA and TUPLEWARE, which can be used as a tool for discovering knowledge in databases. A prototype based on the IF and FCA has been developed. Our method is tested and verified by using this prototype and TUPLEWARE.
Original languageEnglish
Pages (from-to)33-43
JournalInternational Journal of Information Technology and Computer Science(IJITCS)
Volume4
Issue number7
Publication statusPublished - 2012

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Formal concept analysis
Interoperability
Semantics

Cite this

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abstract = "As databases become widely used, there is a growing need to translate information between multiple databases. Semantic interoperability and integration has been a long standing challenge for the database community and has now become a prominent area of database research. In this paper, we aim to answer the question how semantic interoperability between two databases can be achieved by using Formal Concept Analysis (FCA for short) and Information Flow (IF for short) theories. For our purposes, firstly we discover knowledge from different databases by using FCA, and then align what is discovered by using IF and FCA. The development of FCA has led to some software systems such as TOSCANA and TUPLEWARE, which can be used as a tool for discovering knowledge in databases. A prototype based on the IF and FCA has been developed. Our method is tested and verified by using this prototype and TUPLEWARE.",
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