  Data catalogs play a crucial role in modern data-driven organizations by
facilitating the discovery, understanding, and utilization of diverse data
assets. However, ensuring their quality and reliability is complex, especially
in open and large-scale data environments. This paper proposes a framework to
automatically determine the quality of open data catalogs, addressing the need
for efficient and reliable quality assessment mechanisms. Our framework can
analyze various core quality dimensions, such as accuracy, completeness,
consistency, scalability, and timeliness, offer several alternatives for the
assessment of compatibility and similarity across such catalogs as well as the
implementation of a set of non-core quality dimensions such as provenance,
readability, and licensing. The goal is to empower data-driven organizations to
make informed decisions based on trustworthy and well-curated data assets. The
source code that illustrates our approach can be downloaded from
https://www.github.com/jorge-martinez-gil/dataq/.
