Metric-based data quality assessment — Developing and evaluating a probability-based currency metric

•We propose a well-founded probability-based data quality metric for currency.•The metric values can be used in a decision calculus to support decision-making.•The metric has successfully been applied in several real-use situations.•The metric has significant advantages and can yield substantial practical benefit.

Data quality assessment has been discussed intensively in the literature and is critical in business. The importance of using up-to-date data in business, innovation, and decision-making processes has revealed the need for adequate metrics to assess the currency of data in information systems. In this paper, we propose a data quality metric for currency that is based on probability theory. Our metric allows for a reproducible configuration and a high level of automation when assessing the currency of attribute values. The metric values represent probabilities and can be integrated into a decision calculus (e.g., based on decision theory) to support decision-making. The evaluation of our metric consists of two main steps: (1) we define an instantiation of the metric for a real-use situation of a German mobile services provider to demonstrate both the applicability and the practical benefit of the approach; (2) we use publicly available real world data provided by the Federal Statistical Office of Germany and the German Institute of Economic Research to demonstrate its feasibility by defining an instantiation of the metric and to evaluate its strength (compared to existing approaches).