  This paper introduces a no-code, machine-readable documentation framework for
open datasets, with a focus on responsible AI (RAI) considerations. The
framework aims to improve comprehensibility, and usability of open datasets,
facilitating easier discovery and use, better understanding of content and
context, and evaluation of dataset quality and accuracy. The proposed framework
is designed to streamline the evaluation of datasets, helping researchers, data
scientists, and other open data users quickly identify datasets that meet their
needs and organizational policies or regulations. The paper also discusses the
implementation of the framework and provides recommendations to maximize its
potential. The framework is expected to enhance the quality and reliability of
data used in research and decision-making, fostering the development of more
responsible and trustworthy AI systems.
