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Most major discoveries in astronomy have come from unplanned discoveries madeby surveying the Universe in a new way, rather than by testing a hypothesis orconducting an investigation with planned outcomes. Next generation radiocontinuum surveys such as the Evolutionary Map of the Universe (EMU: the radiocontinuum survey on the new Australian SKA Pathfinder telescope), willsignificantly expand the volume of observational phase space, so we can bereasonably confident that we will stumble across unexpected new phenomena ornew types of object. However, the complexity of the instrument and the largedata volumes mean that it may be non-trivial to identify them. On the otherhand, if we don't, then we may be missing out on the most exciting scienceresults from EMU. We have therefore started a project called "WTF", whichexplicitly aims to mine EMU data to discover unexpected science that is notpart of our primary science goals, using a variety of machine-learningtechniques and algorithms. Although targeted specifically at EMU, we expectthis approach will have broad applicability to astronomical survey data.

WTF? Discovering the Unexpected in next-generation radio continuum surveys