Text mining was used to extract technical intelligence from the global open nanotechnology
and nanoscience research literature. An extensive nanotechnology/nanosciene-focuse query (300+term) was
applied to the SCI/SSCI database. A novel addition was the use of phrase auto correlation maps to show
technical thrust areas based on phrase co-occurrence in Abstracts, and the use of phrase-phrase crosscorrelation
maps to show technical thrust areas based on phrase relations due to the sharing of common cooccurring
phrases. The use of factor matrices quantified further the strength of the linkages among
institutions and among countries, and validated the co-publishing networks shown graphically on the maps.

World-wide collaboration in high-energy physics (HEP) is a tradition which dates back several
decades, with scientific publications mostly coauthored by scientists from different countries. This coauthorship
phenomenon makes it difficult to identify precisely the“ share” of each country in HEP scientific production.
One year’s worth of HEP scientific articles published in peer-reviewed journals is analysed and their authors
are uniquely assigned to countries. This method allows the first correct estimation on a pro rata basis of the
share of HEP scientific publishing among several countries and institutions. The results provide an interesting
insight into the geographical collaborative patterns of the HEP community. The HEP publishing landscape is
further analysed to provide information on the journals favoured by the HEP community and on the
geographical variation of their author bases. These results provide quantitative input to the ongoing debate on
the possible transition of HEP publishing to an Open Access model.