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Semantic conflict resolution ontology (SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts

机译:语义冲突解决本体(SCROL):用于检测和解决数据和模式级语义冲突的本体

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摘要

Establishing semantic interoperability among heterogeneous information sources has been a critical issue in the database community for the past two decades. Despite the critical importance, current approaches to semantic interoperability of heterogeneous databases have not been sufficiently effective. We propose a common ontology called semantic conflict resolution ontology (SCROL) that addresses the inherent difficulties in the conventional approaches, i.e., federated schema and domain ontology approaches. SCROL provides a systematic method for automatically detecting and resolving various semantic conflicts in heterogeneous databases. SCROL provides a dynamic mechanism of comparing and manipulating contextual knowledge of each information source, which is useful in achieving semantic interoperability among heterogeneous databases. We show how SCROL is used for detecting and resolving semantic conflicts between semantically equivalent schema and data elements. In addition, we present evaluation results to show that SCROL can be successfully used to automate the process of identifying and resolving semantic conflicts.
机译:在过去的二十年中,在异构信息源之间建立语义互操作性一直是数据库社区中的关键问题。尽管至关重要,但当前用于异构数据库的语义互操作性的方法还不够有效。我们提出了一种通用的本体,称为语义冲突解决本体(SCROL),该本体解决了传统方法(即联合模式和领域本体方法)中的固有困难。 SCROL提供了一种系统的方法来自动检测和解决异构数据库中的各种语义冲突。 SCROL提供了一种动态的机制来比较和处理每个信息源的上下文知识,这对于实现异构数据库之间的语义互操作性很有用。我们将展示SCROL如何用于检测和解决语义上等效的架构与数据元素之间的语义冲突。此外,我们提供的评估结果表明,SCROL可以成功地用于自动化识别和解决语义冲突的过程。

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