High-quality data are the precondition for analyzing and using big data and for guaranteeing
the value of the data. Currently, comprehensive analysis and research of quality standards …

This book is the result of a study path that started in 2006, when the two authors of this book
published the book Data Quality: Concepts, Methodologies and Techniques. After 8 years …

RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in
many areas of biology, including studies into gene regulation, development and disease. Of …

The assessment of content quality (CQ) in social media adds a layer of complexity over
traditional information quality assessment frameworks. Challenges arise in accurately …

Cognitive automation (CA) moves beyond rule-based business process automation to target
cognitive knowledge and service work. This allows the automation of tasks and processes …

The growing relevance of data quality has revealed the need for adequate measurement
since quantifying data quality is essential for planning quality measures in an economic …

Purpose–The purpose of this paper is to identify quality issues with using historical work
order (WO) data from computerised maintenance management systems for reliability …

AI-driven journalism refers to various methods and tools for gathering, verifying, producing,
and distributing news information. Their potential is to extend human capabilities and create …

The essence of an information system lies in the data; if it is not of good quality or not
sufficiently protected, the consequences will undoubtedly be harmful. Quality and Security …

Due to the importance of using up-to-date data in information systems, this article analyzes
how the data-quality dimension currency can be quantified. Based on several requirements …