Stakeholder-centred Identification of Data Quality Issues: Knowledge that Can Save Your Business

The paper presents a study aimed at identifying the most widely occurring data quality issues that affect users' experience with data and their reuse, and presence of which may not only disrupt the willingness to work with data but also cause losses for businesses. The list of defects is intended to be identified as a result of the following activities: first, the list of the most widely occurring data quality requirements and/or dimensions should be established by means of literature analysis. Second, given the diversity and quantity of different data quality requirements and dimensions, this list should be reduced by means of the brainstorming session and DELPHI analysis, which involves 12 experts. The validity of the resulting list should then be verified by applying these requirements to real-world data, more precisely, open government data, which are freely available to every stakeholder. This activity involves 30 users with advanced data quality knowledge. This allows us to define a list of key data quality issues. Both the data holder and the data user with higher degree of confidence can make use of it to make sure that the data are error-free and are a trusted source to be used without losses for business. These requirements serve as part of a specification for the web-based data quality analysis tool to be developed.