Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
BMC Bioinformatics. 2009 Oct 1;10 Suppl 10(Suppl 10):S2. doi: 10.1186/1471-2105-10-S10-S2.
The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.
美国国家癌症研究所（NCI）正在开发 caGrid，作为共享癌症相关数据和服务的一种手段。随着更多的数据集在 caGrid 上可用，我们需要有效的方法来访问和整合这些信息。虽然 caGrid 上公开的数据模型在语义上有很好的注释，但目前需要 caGrid 客户端来推断不同模型及其类之间的关系。在本文中，我们提出了一个基于语义网的数据仓库（Corvus），用于在 caGrid 模型之间创建关系。这是通过将语义注释的 caBIG 统一建模语言（UML）信息模型转换为保留这些语义的 Web 本体语言（OWL）本体来实现的。我们通过从两个 caGrid 数据源（caTissue 和 caArray）进行数据的语义提取、转换和加载（SETL），以及在 Corvus 中对这些数据源进行对齐和查询，证明了该方法的有效性。我们认为语义集成对于来自分布式 Web 服务的数据集成是必要的，而 Corvus 是实现这一目标的一种有用方法。我们的方法具有通用性，对于面临类似集成挑战的研究人员具有广泛的实用性。
