  The scientific community of researchers in a research specialty is an
important unit of analysis for understanding the field specific shaping of
scientific communication practices. These scientific communities are, however,
a challenging unit of analysis to capture and compare because they overlap,
have fuzzy boundaries, and evolve over time. We describe a network analytic
approach that reveals the complexities of these communities through examination
of their publication networks in combination with insights from ethnographic
field studies. We suggest that the structures revealed indicate overlapping
sub- communities within a research specialty and we provide evidence that they
differ in disciplinary orientation and research practices. By mapping the
community structures of scientific fields we aim to increase confidence about
the domain of validity of ethnographic observations as well as of collaborative
patterns extracted from publication networks thereby enabling the systematic
study of field differences. The network analytic methods presented include
methods to optimize the delineation of a bibliographic data set in order to
adequately represent a research specialty, and methods to extract community
structures from this data. We demonstrate the application of these methods in a
case study of two research specialties in the physical and chemical sciences.
