Transactional and Incremental Type Inference from Data Updates | Zendy

Yu Liu | Zendy; Peter McBrien | Zendy

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Transactional and Incremental Type Inference from Data Updates

Author(s) -

Yu Liu,

Peter McBrien

Publication year - 2016

Publication title -

the computer journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.319

H-Index - 64

eISSN - 1460-2067

pISSN - 0010-4620

DOI - 10.1093/comjnl/bxw048

Subject(s) - computer science , atomicity , relational database , ontology , consistency (knowledge bases) , database transaction , web ontology language , inference , relational model , database , property (philosophy) , information retrieval , programming language , data mining , semantic web , artificial intelligence , philosophy , epistemology

A distinctive property of relational database systems is the ability to perform data updates and queries in atomic blocks called transactions, with the well known ACID properties. To date, the ability of systems performing reasoning to maintain the ACID properties, even over data held within a relational database, has been largely ignored. This article studies an approach to reasoning over data from OWL 2 RL ontologies held in a relational database, where the ACID properties of transactions are maintained. Taking an incremental approach to maintaining materialised views of the result of reasoning, the approach is demonstrated to support a query and reasoning performance comparable to or better than other OWL reasoning systems, yet adding the important benefit of supporting transactions

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