Sheny Illescas Martinez, Lisa Ehrlinger, Wolfram Wöß,
"Visualization of Multi-Level Data Quality Dimensions with QuaIIe"
, in Malcolm Crowe, Fritz Laux, Andreas Schmidt, Cosmin Dini: DBKDA 2021, The Thirteenth International Conference on Advances in Databases, Knowledge, and Data Applications, International Academy, Research, and Industry Association, Seite(n) 15-20, 5-2021, ISBN: 978-1-61208-857-0
Original Titel:
Visualization of Multi-Level Data Quality Dimensions with QuaIIe
Sprache des Titels:
Englisch
Original Buchtitel:
DBKDA 2021, The Thirteenth International Conference on Advances in Databases, Knowledge, and Data Applications
Original Kurzfassung:
Data quality assessment is a challenging but necessary task to ensure that business decisions that are derived from data can be trusted. A number of data quality metrics have been developed to measure dimensions like accuracy, completeness, and timeliness. The tool QuaIIe (developed in our previous research) facilitates the calculation of different data quality metrics on both, schema- and data-level, and for heterogeneous information systems. However, to gain meaningful results from the automatically calculated metrics, it is key that humans understand the results of these metrics. This understanding is specifically important when contextual information needs to be considered, which is not encoded in the data. In this paper, we present a visualization approach to enable human-centered data quality assessment across multiple dimensions and arbitrary complex data sources. The approach has been implemented as graphical user interface in QuaIIe.
Sprache der Kurzfassung:
Englisch
Veröffentlicher:
International Academy, Research, and Industry Association
Forschungs-