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This use case is about the management of rules representing business policies and practices in cases involving multiple organizations and/or multiple units within a single organization. One of the key challenges in dealing with such domains is that some rules that support business policies and practices might not be directly executable by a machine, whereas others, even those dealing with the same situation, are machine executable. Rules that are not directly executable might need something from a person, e.g. a decision or confirmation of an action, at which point the rule execution system might be able to use the rule in a reasoning process. The RIF can help to make such domains more tractable and amenable to machine processing by allowing rules to be labelled with tags that express the necessary meta-level information required to make a reasoned determination as to the intended status of a given rule.

Consider the (fictitious) European Union (EU) based car rental company, EU-Rent. Suppose an EU regulator issues the following directive:

Being a EU based company, EU-Rent comes up with two rules to handle off-site rental returns:

The first rule is immediately executable (at least in cases where the renter makes his/her intention known in advance). The second rule obviously has a part that is for human consumption - somebody from EU-Rent has to recover the car, and confirm to the IT system that this has been done. But it can also be given a machine executable corollary, namely,

In order for EU-Rent’s rule-system to work in the intended fashion, the system needs to be able to recognize which rules can be immediately executed, and which have first to be routed or "pended" for some human action. For example, the rule requring recovery of an off-site vehicle within 24 hours may be automatically initiated and cause a timer to be set up, but then for up to 24 hours the rule might be in a suspended condition awaiting human input. If a human indicates that the car has been recovered after 5 hours, then the rule will conclude, the car will be considered returned and the penalty calculated. If 24 hours go by without such input, the rule will conclude and the rented car will still have an off-site status. This will cause the above corollary to fire.

This scenario shows one way in which RIF metadata can be used to help machines cope with organizational practices that might involve joint human-machine interaction. The notion of human-machine interactive rule systems is, of course, not new to the RIF, but by making this an explicit part of the standard the accurate interchange of such rules is also enabled.