  Knowledge Graphs (KGs), and Linked Open Data in particular, enable the
generation and exchange of more and more information on the Web. In order to
use and reuse these data properly, the presence of accountability information
is essential. Accountability requires specific and accurate information about
people's responsibilities and actions. In this article, we define KGAcc, a
framework dedicated to the assessment of RDF graphs accountability. It consists
of accountability requirements and a measure of accountability for KGs. Then,
we evaluate KGs from the LOD cloud and describe the results obtained. Finally,
we compare our approach with data quality and FAIR assessment frameworks to
highlight the differences.
