Data validation is the activity where one decides whether or not a particular data set is fit for a given purpose. Formalizing the requirements that drive this decision process allows for unambiguous communication of the requirements, automation of the decision process, and opens up ways to maintain and investigate the decision process itself. The purpose of this article is to formalize the definition of data validation and to demonstrate some of the properties that can be derived from this definition. In particular, it is shown how a formal view of the concept permits a classification of data quality requirements, allowing them to be ordered in increasing levels of complexity. Some subtleties arising from combining possibly many such requirements are pointed out as well.
翻译:数据验证是确定某一数据集是否适合某一特定目的的活动; 正式确定驱动这一决策过程的要求,允许毫不含糊地通报要求,使决定过程自动化,并开辟维护和调查决定过程本身的方法; 本条的目的是正式确定数据验证的定义,并表明可从这一定义中得出的一些属性; 特别要说明的是,对这一概念的正式看法如何允许对数据质量要求进行分类,从而能够以越来越复杂的程度来命令进行分类; 还指出了将可能的许多这类要求结合起来所产生的一些微妙之处。