AlzPharm: integration of neurodegeneration data using RDF.
AlzPharm: integration of neurodegeneration data using RDF.
复制标题
Alzpharm：使用RDF积分神经退行性数据。
DOI：
10.1186/1471-2105-8-s3-s4
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发表时间：
2007-05-09
影响因子：
3
通讯作者：
Cheung, Kei-Hoi
中科院分区：
文献类型：
--
作者：
Lam, Hugo Y K;Marenco, Luis;Clark, Tim;Gao, Yong;Kinoshita, June;Shepherd, Gordon;Miller, Perry;Wu, Elizabeth;Wong, Gwendolyn T;Liu, Nian;Crasto, Chiquito;Morse, Thomas;Stephens, Susie;Cheung, Kei-Hoi
神经科学家经常需要访问分布在互联网上的各种数据集。然而，这些数据集通常既不集成也不互操作，导致回答复杂的神经科学研究问题的障碍。领域本体可以使查询异构数据集，但它们是不够的，因为感兴趣的数据通常跨越多个研究领域的神经科学。为此，e-Neuroscience旨在为神经科学家提供一个集成平台，通过无缝集成各种类型的神经科学数据来发现新知识。在这里，我们提出了一个语义Web的方法来建立这个电子神经科学框架，通过使用资源描述框架（RDF）和它的词汇描述语言，RDF模式（RDFS），作为一个标准的数据模型，以方便表示和集成的数据。我们使用RDFS为BrainPharm（SenseLab的子集）构建了一个试点本体，然后根据本体结构将BrainPharm数据的子集转换为RDF。我们还将转换后的BrainPharm数据与现有的RDF假设和SWAN（神经医学中的语义网应用）试点版本的出版物数据相结合。我们的实现使用的RDF数据模型在Oracle数据库10 g版本2的数据集成，查询和推理，而我们的Web界面允许用户查询数据和检索结果在一个方便的方式。访问和集成跨多个学科的生物医学数据对于神经科学研究人员来说将变得越来越不可或缺且有益。我们采用的语义Web方法已经证明了一种很有前途的方法，可以在语义上集成独立创建的数据集。它还展示了如何在集成数据上执行高级查询和推理，这是使用传统数据集成方法难以实现的。我们的试点结果表明，我们的语义网的方法是适合实现电子神经科学和通用足以应用于其他生物医学领域。
Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.