  The partial information decomposition (PID) framework is concerned with
decomposing the information that a set of (two or more) random variables (the
sources) has about another variable (the target) into three types of
information: unique, redundant, and synergistic. Classical information theory
alone does not provide a unique way to decompose information in this manner and
additional assumptions have to be made. One often overlooked way to achieve
this decomposition is using a so-called measure of union information - which
quantifies the information that is present in at least one of the sources -
from which a synergy measure stems. In this paper, we introduce a new measure
of union information based on adopting a communication channel perspective,
compare it with existing measures, and study some of its properties. We also
include a comprehensive critical review of characterizations of union
information and synergy measures that have been proposed in the literature.
