  Filaments are very common physical phenomena on the Sun and are often taken
as important proxies of solar magnetic activities. The study of filaments has
become a hot topic in the space weather research. For a more comprehensive
understanding of filaments, especially for an understanding of solar activities
of multiple solar cycles, it is necessary to perform a combined multifeature
analysis by constructing a data set of multiple solar cycle data. To achieve
this goal, we constructed a centennial data set that covers the H$\alpha$ data
from five observatories around the world. During the data set construction, we
encountered varieties of problems, such as data fusion, accurate determination
of the solar edge, classifying data by quality, dynamic threshold, and so on,
which arose mainly due to multiple sources and a large time span of data. But
fortunately, these problems were well solved. The data set includes seven types
of data products and eight types of feature parameters with which we can
implement the functions of data searching and statistical analyses. It has the
characteristics of better continuity and highly complementary to space
observation data, especially in the wavelengths not covered by space
observations, and covers many solar cycles (including more than 60 yr of
high-cadence data). We expect that this new comprehensive data set as well as
the tools will help researchers to significantly speed up their search for
features or events of interest, for either statistical or case study purposes,
and possibly help them get a better and more comprehensive understanding of
solar filament mechanisms.
