Accounting for quality in data integration systems: a completeness-aware integration approach

Ensuring the quality of integrated data is undoubtedly one of the main problems of integrated data systems. When focusing on multi-national and historical data integration systems, where the “space” and “time” dimensions play a relevant role, it is very much important to build the integration layer in such a way that the final user accesses a layer that is “by design” as much complete as possible. In this paper, we propose a method for accessing data in multipurpose data infrastructures, like data integration systems, which has the properties of (i) relieving the final user from the need to access single data sources while, at the same time, (ii) ensuring to maximize the amount of the information available for the user at the integration layer. Our approach is based on a completeness-aware integration approach which allows the user to have ready available all the maximum information that can get out of the integrated data system without having to carry out the preliminary data quality analysis on each of the databases included in the system. Our proposal of providing data quality information at the integrated level extends then the functions of the individual data sources, opening the data infrastructure to additional uses. This may be a first step to move from data infrastructures towards knowledge infrastructures. A case study on the research infrastructure for the science and innovation studies shows the usefulness of the proposed approach.