 To see how this fits with the information-as-correlation view, consider again the example of planes being monitored by radars. As before, each monitoring situation will be modelled as having only two parts, now indexed by the members of \(Comp = \{ screen, plane\}\). The actual instances of screening situations would correspond to global states, which in this case — where we have only two components — can be thought of as pairs \((s, b)\) where \(s\) is a particular screen and \(b\) a particular plane. Hence, global states connect instances of parts, so representing instances of a whole system. But then a crucial restriction comes into play, because not all screens are connected with all planes, only with those belonging to the same monitoring situation. The set \(C\) selects only such permissible pairs, thus playing a role similar to that of a channel in  section 1.  Finally, Pred classifies global states into types, similar to the classification relations of  section 2.3. 