  Mapping Science across countries is a challenging task in the field of
Scientometrics. A number of efforts trying to cope with this task has been
discussed in the state of the art, addressing this challenge by processing
collections of scientific digital libraries and visualizing author-based
measures (for instance, the h-index) or document-based measures (for instance,
the averaged number of citations per document). A major drawback of these
approaches is related to the presence of bias. The bigger the country, the
higher the measure value. We explore the use of an econometric index to tackle
this limitation, known as the Revealed Comparative Advantage measure (RCA).
Using RCA, the diversity and ubiquity of each field of knowledge is mapped
across countries. Then, a RCA-based proximity function is explored to visualize
citation and h-index ubiquity. Science maps relating 27 knowledge areas and 237
countries are introduced using data crawled from Scimago that ranges from 1996
to 2011. Our results shows that the proposal is feasible and can be extended to
ellaborate a global scientific production characterization.
