Do Metadata Models meet IQ Requirements?

Research has recognized the importance of analyzing information quality (IQ) for many different applications: The success of data integration greatly depends on the quality of the individual data. In statistical applications poor data quality often leads to wrong conclusions. High information quality is literally a vital property of hospital information systems. Poor data quality of stock price information services can lead to economically wrong decisions. Several projects have analyzed this need for IQ metadata and have proposed a set of IQ criteria or attributes which can be used to properly assess information quality. In this paper we survey and compare these approaches. In a second step we take a look at existing prominent proposals of metadata models, especially those on the Internet. Then, we match these models to the requirements of information quality modeling. Finally, we propose a quality assurance procedure for the assurance of metadata models