Identification & Reconciliation of Semantic Conflicts Using Metadata

随着复杂信息系统的发展，不同系统的集成，以及大量在线计算机数据源的可用，开发考虑在这些系统中使用的数据的意义的方法变得越来越重要。例如，需要以美元表示的财务数据的应用程序不能从以另一种货币报告的来源接收数据，这一点很重要。由于数据的含义可能随时发生变化，这一问题变得更加复杂。要解决这一问题，信息系统必须具有表示数据语义、检测和自动解决语义冲突的能力。本研究的重点是数据语义(即元数据)的表示和操作。这项研究开发了：(1)基于规则的元数据规范方法，(2)识别语义冲突的查询处理技术，(3)使用转换例程自动解决这些冲突的方法。当应用于源-接收器系统时，这些技术创建了允许数据语义改变的动态系统环境。类似地，在异类信息系统中，这些技术定义了动态模式集成环境，在该环境中，当组件系统独立地修改数据语义时，集成系统可以继续操作。

With the development of complex information systems, the integration of heterogeneous systems, and the availability of numerous online computer data sources, it has become increasingly important that methods be developed that consider the meaning of the data used in these systems. For example, it is important that an application requiring financial data in US dollars does not receive data from a source that reports in another currency. This problem is further complicated by the fact that the meaning of data may change at any time. To deal with this problem, information systems must have the ability to represent data semantics and detect and automatically resolve semantic conflicts. This research focuses on the representation and manipulation of data semantics (i.e., metadata). This research develops: (1) a rule-based approach to metadata specification, (2) query processing techniques that identify semantic conflicts, (3) methods that use conversion routines to automatically resolve these conflicts. When applied to source-receiver systems, these techniques create a dynamic system environment that permits changes in data semantics. Similarly, in heterogeneous information systems these techniques define a dynamic schema integration environment where the integrated system can continue to operate as the component systems independently modify data semantics.