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Is Your Database System a Semantic Web Reasoner

机译:您的数据库系统是语义Web推理器吗?

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摘要

Databases and semantic technologies are an excellent match in scenarios requiring the management of heterogeneous or incomplete data. In ontology-based query answering, application knowledge is expressed in ontologies and used for providing better query answers. This enhancement of database technology with logical reasoning remains challenging - performance is critical. Current implementations use time-consuming pre-processing to materialise logical consequences or, alternatively, compute a large number of large queries to be answered by a database management system (DBMS). Recent research has revealed a third option using recursive query languages to "implement" ontological reasoning in DBMS. For lightweight ontology languages, this is possible using the popular Semantic Web query language SPARQL 1.1, other cases require more powerful query languages like Datalog, which is also seeing a renaissance in DBMS today. Herein, we give an overview of these areas with a focus on recent trends and results.
机译:在需要管理异构或不完整数据的情况下,数据库和语义技术是很好的匹配。在基于本体的查询回答中,应用程序知识以本体表示,并用于提供更好的查询答案。通过逻辑推理来增强数据库技术仍然具有挑战性-性能至关重要。当前的实现使用费时的预处理来实现逻辑结果,或者替代地,计算大量的大型查询以由数据库管理系统(DBMS)回答。最近的研究表明,使用递归查询语言在DBMS中“实现”本体论推理的第三种选择。对于轻量级本体语言,可以使用流行的语义Web查询语言SPARQL 1.1来实现,而其他情况则需要更强大的查询语言,例如Datalog,如今在DBMS中也正在兴起。在此,我们以最近的趋势和结果为重点,对这些领域进行了概述。

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