  Data reduction techniques published so far for the CoRoT N2 data product were
targeted primarily on the detection of extrasolar planets. Since the whole
dataset has been released, specific algorithms are required to process the
lightcurves from CoRoT correctly. Though only unflagged datapoints must be
chosen for scientific processing, some flags might be reconsidered. The
reduction of data along with improving the signal-to-noise ratio can be
achieved by applying a one dimensional drizzle algorithm. Gaps can be filled by
linear interpolated data without harming the frequency spectrum. Magnitudes
derived from the CoRoT color channels might be used to derive additional
information about the targets. Depending on the needs, various filters in the
frequency domain remove either the red noise background or high frequency
noise. The autocorrelation function or the least squares periodogram are
appropriate methods to identify periodic signals.The methods described here are
not strictly limited to CoRoT data but may also be applied on Kepler data or
the upcoming Plato mission.
