  As an open and collaborative knowledge graph created by users and bots, it is
possible that the knowledge in Wikidata is biased in regards to multiple
factors such as gender, race, and country of citizenship. Previous work has
mostly studied the representativeness of Wikidata knowledge in terms of genders
of people. In this paper, we examine the race and citizenship bias in general
and in regards to STEM representation for scientists, software developers, and
engineers. By comparing Wikidata queries to real-world datasets, we identify
the differences in representation to characterize the biases present in
Wikidata. Through this analysis, we discovered that there is an
overrepresentation of white individuals and those with citizenship in Europe
and North America; the rest of the groups are generally underrepresented. Based
on these findings, we have found and linked to Wikidata additional data about
STEM scientists from the minorities. This data is ready to be inserted into
Wikidata with a bot. Increasing representation of minority race and country of
citizenship groups can create a more accurate portrayal of individuals in STEM.
