A quality evaluation approach for OLAP metadata of multidimensional OLAP data

The quality of metadata in OnLine Analytical Processing(OLAP) process has remarkable influence on the stability and reliability of OLAP tools. Model-driven metadata integration approach introduces the metadata management concept based on the object oriented paradigm for modeling and querying OLAP metadata of multidimensional data. In this model, the basic concepts of the object oriented model including object, class, and relationship between objects are applied to describe objects of multidimensional data and the OLAP operations. Thus the metadata of multidimensional OLAP data is modeled as a fact and a set of elements that are organized into class hierarchy. However, the quality evaluation of OLAP metadata which describes multidimensional data is difficult because of the structural essential of the metadata. In this paper, we propose a quality evaluation approach for model-driven OLAP metadata. This approach depends on a static formalization mechanism, various reasoning procedures supported by the formalization can be used for the quality evaluation tasks.