上下文和数据质量评估
Contexts and Data Quality Assessment
摘要：
数据的质量取决于上下文。从这种直觉和经验出发，我们提出并开发了一个概念框架，以正式的术语捕获“上下文相关的数据质量”的概念。首先，我们提出了一个通用的和抽象的概念的背景下，它的用途，一般和数据管理特别。在此基础上，我们调查“数据质量评估”和“质量查询回答”作为上下文相关的活动。用于评估手头的数据库D的上下文被建模为外部数据库模式，其可能具有物化或虚拟数据以及到外部数据源的连接。数据库D通过到上下文模式的映射被置于上下文中，这产生D的备选干净版本的集合C。D的质量是用它到C的距离来衡量的。类C}还用于定义和执行“质量查询应答”。所提出的模型允许自然扩展，如使用数据质量谓词，优化访问的上下文到外部数据源，也表示上下文通过更有表现力的本体。
英文摘要：
The quality of data is context dependent. Starting from this intuition and experience, we propose and develop a conceptual framework that captures in formal terms the notion of "context-dependent data quality". We start by proposing a generic and abstract notion of context, and also of its uses, in general and in data management in particular. On this basis, we investigate "data quality assessment" and "quality query answering" as context-dependent activities. A context for the assessment of a database D at hand is modeled as an external database schema, with possibly materialized or virtual data, and connections to external data sources. The database D is put in context via mappings to the contextual schema, which produces a collection C of alternative clean versions of D. The quality of D is measured in terms of its distance to C. The class C} is also used to define and do "quality query answering". The proposed model allows for natural extensions, like the use of data quality predicates, the optimization of the access by the context to external data sources, and also the representation of contexts by means of more expressive ontologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
