This work presents a method for detecting statisticallysignificant temporal hotspots, i.e. the date and time of events,which is useful for improved planning of response activities.Temporal hotspots are calculated using Local Indicators ofSpatial Association (LISA) statistics. The temporal data is ina 7x24 matrix that represents a temporal resolution of weekdaysand hours-in-the-day. Swedish residential burglary events areused in this work for testing the temporal hotspot detectionapproach. Although, the presented method is also useful forother events as long as they contain temporal information, e.g.attack attempts recorded by intrusion detection systems. Byusing the method for detecting significant temporal hotspotsit is possible for domain-experts to gain knowledge about thetemporal distribution of the events, and also to learn at whichtimes mitigating actions could be implemented.