  In particle detectors at the Large Hadron Collider, tens of terabytes of data
are produced every second from proton-proton collisions occurring at a rate of
40 megahertz. This data rate is reduced to a sustainable level by a real-time
event filter processing system which decides whether each collision event
should be kept for further analysis or be discarded. We introduce a dataset of
proton collision events which emulates a typical data stream collected by such
a real-time processing system, pre-filtered by requiring the presence of at
least one electron or muon. This dataset could be used to develop novel event
selection strategies and assess their sensitivity to new phenomena. In
particular, by publishing this dataset we intend to stimulate a community-based
effort towards the design of novel algorithms for performing unsupervised New
Physics detection, customized to fit the bandwidth, latency and computational
resource constraints of the real-time event selection system of a typical
particle detector.
