  Data challenges are emerging as powerful tools with which to answer
fundamental astronomical questions. Time-domain astronomy lends itself to data
challenges, particularly in the era of classification and anomaly detection.
With improved sensitivity of wide-field surveys in optical and radio
wavelengths from surveys like the Large Synoptic Survey Telescope (LSST) and
the Canadian Hydrogen Intensity Mapping Experiment (CHIME), we are entering the
large-volume era of transient astronomy. I highlight some recent time-domain
challenges, with particular focus on the Photometric LSST Astronomical Time
series Classification Challenge (PLAsTiCC), and describe metrics used to
evaluate the performance of those entering data challenges.
