A new approach to measure believability dimension of data quality

Todayʹs methodologies for data quality assessment and improvement are considerably aimed at reducing costs. Data quality comprises different dimensions, each having certain methods and techniques to assess and improve data quality. One of the most controversial dimensions is data believability in which less attention has been paid by scholars and researchers, because of its ambiguous nature. This is categorized under the "intrinsic data quality" dimensions. The current paper offers a precise and comprehensive definition of such quality dimension, and provides some parameters to understand it. In order to calculate these parameters, furthermore, different methods are discussed.