Nowadays, the importance of achieving and maintaining a high standard of data quality is
widely recognized by both practitioners and researchers. Based on its impact on …

The literature provides a wide range of techniques to assess and improve the quality of data.
Due to the diversity and complexity of these techniques, research has recently focused on …

Nowadays, IoT is being used in more and more application areas and the importance of IoT
data quality is widely recognized by practitioners and researchers. The requirements for …

The term data quality refers to measuring the fitness of data regarding the intended usage.
Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could …

Various techniques have been proposed to enable organisations to assess the current
quality level of their data. Unfortunately, organisations have many different requirements …

ABSTRACT We present a Heterogenous Data Quality Methodology (HDQM) for Data Quality
(DQ) assessment and improvement that considers all types of data managed in an …

This paper provides a comprehensive description of the current literature on data fusion,
with an emphasis on Information Quality (IQ) and performance evaluation. This literature …

For organizations data quality is a prerequisite for automated decision making and agility. To
provide high quality data, numerous tools have emerged that support the different steps of …

While survey data has long been the focus of quantitative social science analyses,
observational and content data, although long-established, are gaining renewed attention; …

Data is one of the most valuable assets of an organization and has a tremendous impact on
its long-term success and decision-making processes. Typically, organizational data error …