semantics of data

Ontology, by way of formal specification of share concepts, provides a method to resolve the semantic heterogeneous, since it can be used to express the semantics of data sources, identify and construct the semantic relationship of the concepts, compass the semantic consistency.

本体作为共享概念的形式化说明，用于表达数据源的语义、识别和建立概念间的语义关联、达成语义一致，提供了语义异构问题的解决途径。

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In other words, an ontology provides an explicit conceptualization that describes semantics of data, providing a shared and common understanding of a domain.

另一个说法，本体提供了用来描述数据的含义的显式概念，从而提供了对某个领域的共享的和公共的理解。

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The great difference in syntax and semantics of data collected is a tough problem for management platform.

语法和语义异构的数据采集是网络管理平台的基础和难题。

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Information sharing requires the interoperation among metadata exchange format, tags, content structure and semantics of data elements, etc. A complete framework of standard is thus necessary.

信息共享需要在元数据的交换格式、标记格式、元素内容结构、元素语义和数据元等方面能够互操作，需要建立一套完整的标准体系。

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That how to organize it is discussed also. Four kinds of rules are designed especially to dig out hidden semantics of data deeply. ( 3) Design the algorithm of querying on large scale of data source, which called DSQ.

论述了如何构建语义信息资源目录，尤其是如何深度发掘数据暗含语义，设计了四类规则促进语义的发掘。（3）设计了在大规模数据源上进行语义查询的DSQ算法。

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On Program Semantics of Dynamic Data Structures

论动态数据结构的程序语义

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In order to inquiry into function dependency in data base, the formal definition and semantics of dependency of knowledge are also discussed in the paper.

为了研究数据库中的函数依赖性，我们还将介绍数据的依赖性的形式化定义及依赖性的语义因素等。

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XML and ontology as the key technologies solves the problem of the syntax and semantics of data heterogeneous. This model shields the differences of physical and logical of the data source to the upper layer users, achieves transparent access.

XML和本体作为系统采用的关键技术分别从语法、语义两个方面解决了数据的异构问题，对上层用户屏蔽了底层数据源物理和逻辑的差异性，实现了应用层的透明访问。

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