Heinrich, Bernd and Klier, Mathias (2015) Metric-based data quality assessment - Developing and evaluating a probability-based currency metric. DECISION SUPPORT SYSTEMS, 72. pp. 82-96. ISSN 0167-9236, 1873-5797
Full text not available from this repository. (Request a copy)Abstract
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). (C) 2015 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | INFORMATION-SYSTEMS; MANAGEMENT; PRODUCT; Data quality; Data quality assessment; Data quality metric; Currency of data |
| Subjects: | 300 Social sciences > 330 Economics |
| Divisions: | Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik II (Prof. Dr. Bernd Heinrich) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 23 Jul 2019 12:04 |
| Last Modified: | 23 Jul 2019 12:04 |
| URI: | https://pred.uni-regensburg.de/id/eprint/5737 |
Actions (login required)
![]() |
View Item |

