Ontology Database: A New Method for Semantic Modeling and an Application to Brainwave Data
Ontology Database: A New Method for Semantic Modeling and an Application to Brainwave Data
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DOI：
10.1007/978-3-540-69497-7_21
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发表时间：
2008-07
期刊：
影响因子：
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通讯作者：
P. LePendu;D. Dou;G. Frishkoff;Jiawei Rong
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文献类型：
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作者：
P. LePendu;D. Dou;G. Frishkoff;Jiawei Rong
我们提出了一种对关系数据库进行建模的自动方法，该方法使用 SQL 触发器和外键来有效地回答有关语义 Web 本体的基础实例的肯定语义查询。与现有的基于知识的方法相比，我们在数据库中花费额外的空间来减少查询时的推理。此实现允许系统在运行时忽略完整性约束和其他类型的推理，从而显着缩短查询响应时间。我们的方法的令人惊讶的结果是加载时间似乎不受影响，即使对于中等大小的本体也是如此。我们将我们的方法应用于脑电图（EEG 和 ERP）数据的研究。本案例研究展示了如何使用我们的方法来主动推动基于 EEG/ERP 本体的知识设计、存储和交换。
We propose an automatic method for modeling a relational database that uses SQL triggers and foreign-keys to efficiently answer positive semantic queries about ground instances for a Semantic Web ontology. In contrast with existing knowledge-based approaches, we expend additional space in the database to reduce reasoning at query time. This implementation significantly improves query response time by allowing the system to disregard integrity constraints and other kinds of inferences at run-time. The surprising result of our approach is that load-time appears unaffected, even for medium-sized ontologies. We applied our methodology to the study of brain electroencephalographic (EEG and ERP) data. This case study demonstrates how our methodology can be used to proactively drive the design, storage and exchange of knowledge based on EEG/ERP ontologies.