  High-resolution solar spectroscopy provides a wealth of information from
photospheric and chromospheric spectral lines. However, the volume of data
easily exceeds hundreds of millions of spectra on a single observation day.
Therefore, methods are needed to identify spectral signatures of interest in
multidimensional datasets. Background-subtracted activity maps (BaSAMs) have
previously been used to locate features of solar activity in time series of
images and filtergrams. This research note shows how this method can be
extended and adapted to spectral data.
