Information Integration from Semantically Heterogeneous Biological Data Sources.

Doina Caragea, Jie Bao, Jyotishman Pathak, Adrian Silvescu, Carson Andorf, Drena Dobbs, Vasant Honavar
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引用次数: 13

Abstract

We present the first prototype of INDUS (Intelligent Data Understanding System), a federated, query-centric system for information integration and knowledge acquisition from distributed, semantically heterogeneous data sources that can be viewed (conceptually) as tables. INDUS employs ontologies and inter-ontology mappings, to enable a user to view a collection of such data sources (regardless of location, internal structure and query interfaces) as though they were a collection of tables structured according to an ontology supplied by the user. This allows INDUS to answer user queries against distributed, semantically heterogeneous data sources without the need for a centralized data warehouse or a common global ontology.

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语义异构生物数据源的信息集成。
我们提出了INDUS(智能数据理解系统)的第一个原型,这是一个以查询为中心的联邦系统,用于从分布式、语义异构的数据源中进行信息集成和知识获取,这些数据源可以(概念上)视为表。INDUS采用本体和本体间映射,使用户能够查看此类数据源的集合(无论位置、内部结构和查询接口如何),就好像它们是根据用户提供的本体构建的表的集合一样。这使得INDUS能够针对分布式、语义异构的数据源回答用户查询,而无需集中式数据仓库或通用全局本体。
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Information Integration from Semantically Heterogeneous Biological Data Sources.
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