  Investment in brighter sources and larger detectors has resulted in an
explosive rise in the data collected at synchrotron facilities. Currently,
human experts extract scientific information from these data, but they cannot
keep pace with the rate of data collection. Here, we present three on-the-fly
approaches - attribute extraction, nearest-neighbor distance, and cluster
analysis - to quickly segment x-ray diffraction (XRD) data into groups with
similar XRD profiles. An expert can then analyze representative spectra from
each group in detail with much reduced time, but without loss of scientific
insights. On-the-fly segmentation would, therefore, result in accelerated
scientific productivity.
