Information quality research challenge

Abstract

There are many challenging issues in the field of Information Quality (IQ), and experience has taught us that they are not all technical. As Thomas Redman points out, “Veterans also know that it is not the hard, technical issues that stymie an organization’s efforts to better manage and utilize its data and information assets, but rather the soft organizational, political, and social issues” [Redman 2008, p. 159–160]. Doan et al. cite a similar issue with data integration, that many projects fail simply because the data owners do not want to cooperate [Doan et al. 2012]. Most current IQ methodologies and frameworks now acknowledge and incorporate this reality, for example, the McGilvray Framework for IQ posits that in addition to the what (i.e., data) and how (i.e., processes and technology) context, the who (people and organizations) must also be considered in order to effectively address IQ problems [McGilvray 2008]. The impact of organizational and social issues on the success of IQ programs is now well recognized. For example, knowledge and skills in project and change management are seen as essential elements of IQ practice. New organizational positions, such as the Chief Data Officer, are evolving as data and data governance issues capture corporate attention [Lee et al. 2014]. However, the research on social and political IQ issues has primarily been qualitative, based on what worked/did not work in a given organization or two. Just as defining data quality dimensions and formulating metrics to quantify the impact of poor data quality was a focus of early IQ research, a new round of research is