With the rise of big data, the quality of datasets has become a crucial factor affecting the
performance of machine learning models. High-quality datasets are essential for the …

High-quality data is key to interpretable and trustworthy data analytics and the basis for
meaningful data-driven decisions. In practical scenarios, data quality is typically associated …

In this paper, we develop a visual analysis method for interactively improving the quality of
labeled data, which is essential to the success of supervised and semi-supervised learning …

While big data benefits are numerous, the use of big data requires, however, addressing
new challenges related to data processing, data security, and especially degradation of data …

Data quality management and assessment play a vital role for ensuring the trust in the data
and its fitness-of-use for subsequent analysis. The transformation history of a data wrangling …

Low quality automatic identification system (AIS) data often mislead analysts to a
misunderstanding of ship behavior analysis and to making incorrect navigation risk …

In customer relationship management (CRM), high-quality customer data is at the heart of
reliable data analysis and is the foundation for data-driven decisions that impact business …

The importance of context in data quality (DQ) was shown many years ago and nowadays is
widely accepted. Early approaches and surveys defined DQ as fitness for use and showed …

The widespread adoption of big data has ushered in a new era of data-driven decision-
making, transforming numerous industries and sectors. However, the efficacy of these …

From dirty data to intentional deception, there are many threats to the validity of data-driven
decisions. Making use of data, especially new or unfamiliar data, therefore requires a …