  The Islamic State of Iraq and al-Sham (ISIS) is a dominant insurgent group
operating in Iraq and Syria that rose to prominence when it took over Mosul in
June, 2014. In this paper, we present a data-driven approach to analyzing this
group using a dataset consisting of 2200 incidents of military activity
surrounding ISIS and the forces that oppose it (including Iraqi, Syrian, and
the American-led coalition). We combine ideas from logic programming and causal
reasoning to mine for association rules for which we present evidence of
causality. We present relationships that link ISIS vehicle-bourne improvised
explosive device (VBIED) activity in Syria with military operations in Iraq,
coalition air strikes, and ISIS IED activity, as well as rules that may serve
as indicators of spikes in indirect fire, suicide attacks, and arrests.
