Common data model for neuroscience data and data model exchange
Common data model for neuroscience data and data model exchange
复制标题
神经科学数据和数据模型交换的通用数据模型
DOI：
10.1136/jamia.2001.0080017
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发表时间：
2001-01-01
影响因子：
6.4
通讯作者：
Gardner, EP
中科院分区：
文献类型：
--
作者：
Gardner, D;Knuth, KH;Gardner, EP
目的：概括两个原型神经生理学数据库的数据模型，描述并提出公共数据模型(CDM)作为联合广泛的不同神经科学信息资源的框架。设计：CDM的每个组件来自五个超类中的一个--数据、站点、方法、模型和参考--或它们之间定义的关系。元数据的分层属性值方案支持与可变树深度的互操作性，以服务于特定的域内或域间查询。为了协调不同系统之间的数据交换，作者提出了一组基于XML的派生模式，不仅用于描述数据集，还用于描述数据模型。其中包括生物物理描述标记语言(BDML)，它通过为CDM提供元描述来协调数据资源之间的互操作性。结果：这组超类潜在地跨越了当代神经科学的数据需求。从神经生理学时间序列和直方图数据中提取的数据元素表示在维度和一致性上不同的数据集。部位元素超越神经元来描述亚细胞隔间、回路、区域或切片；非神经解剖部位包括患者的序列。方法和模型与领域高度相关。结论：真正的数据资源联合需要用元语言对每个数据资源的内容、查询方法、数据格式和数据模型进行明确的公开描述。任何可以从定义的超类派生的数据模型都可能是一致的，并且可以通过识别BDML描述的兼容性来实现互操作性。这种元描述可以缓冲技术上的变化。
Objective: Generalizing the data models underlying two prototype neurophysiology databases, the authors describe and propose the Common Data Model (CDM) as a framework for federating a broad spectrum of disparate neuroscience information resources.Design: Each component of the CDM derives from one of five superclasses-data, site, method, model, and reference-or from relations defined between them. A hierarchic attribute-value scheme for metadata enables interoperability with variable tree depth to serve specific intra- or broad interdomain queries. To mediate data exchange between disparate systems, the authors propose a set of XML-derived schema for describing not only data sets but data models. These include biophysical description markup language (BDML), which mediates interoperability between data resources by providing a meta-description for the CDM.Results: The set of superclasses potentially spans data needs of contemporary neuroscience. Data elements abstracted from neurophysiology time series and histogram data represent data sets that differ in dimension and concordance. Site elements transcend neurons to describe subcellular compartments, circuits, regions, or slices; non-neuroanatomic sites include sequences to patients. Methods and models are highly domain-dependent.Conclusions: True federation of data resources requires explicit public description, in a metalanguage, of the contents, query methods, data formats, and data models of each data resource. Any data model that can be derived from the defined superclasses is potentially conformant and interoperability can be enabled by recognition of BDML-described compatibilities. Such meta-descriptions can buffer technologic changes.