TAMI Scenario 9 Storyline

January 2008

Demo Scenario

An unconscious man under treatment in an emergency room is found to have a drug-resistant strain of tubercolsis. In order to prevent an epidemic, the CDC, acting under statutory authority, contacts people the works with, his choir, the members of his scout troop and people he has called.
In the course of this investigation, the CDC gets his phone records from XPhone
Sometime later Bob Same has phone troubles and calls XPhone to schedule an appt
The customer service operator sees that CDC had obtained his records (because the anonymous TB patient once called him) and infers that he must have some contagious disease
So she refuses to schedule a repairman

Click 'run reasoner' and the rules system analyzes the application of the policy rules to the transaction log, providing a description of the policy conclusion.

Ask Why ("?") and the justification browser provides a short explanation (built up from templated descriptions in the rules) along with the premised used to reach the conclusion

A policy is an explicit representation of social and legal norms of behavior

rule-based policy language for accountability and access control
integrated explanations for policy decisions through dependency tracking
more efficient and expressive reasoning through the use of goal direction
grounded in Semantic Web technologies for greater interoperability, reusability, and extensibility

Explanations for policy decisions allow users to understand how the results were obtained
Increase trust in the policy reasoning and enforcement process
Used by policy administrators to confirm the correctness of the policy and to check that the result is as expected
In the case of failed queries, they can be used to figure out what additional information is required for success
Dependency tracking during reasoning process provides integrated justification support

specific set of premises from which any conclusion/policy decision was derived is an effective explanation for the conclusion
these premises are called the set of dependencies and dependency tracking is the process of maintaining dependency sets for derived conclusions
We use Truth Maintenance System (TMS) for tracking dependencies of conclusions
- keeps track of the logical structure of a derivation
- has ability to assume and retract hypothetical premises
Explanations are automatically generated by extracting and presenting relevant information from dependencies

Each AIR policy consists of one or more rules
policy = { rule }
A rule is made up of a pattern that when matched causes an action to be fired
rule = { pattern, action }
An action can either be an assertion, which is a set of facts that are added to the knowledge base or a nested rule
action = { assertion | rule }

     :MyFirstPolicy a air:Policy;
	 air:rule [
	     air:pattern { ... };
	     air:assertion { ... };
	     air:rule [ ... ]
	 ].

Accountability allows violators of applicable privacy policies to be identified and held accountable
Privacy usage restrictions and resource access control policies are specified in AIR
User's actions within the framework are captured and annotated transaction logs are maintained
Policy compliance over transaction logs can be checked using the AIR reasoner

Install Tabulator Extension: http://www.w3.org/2005/ajar/tab
Remote
- Call reasoner on web server with remote log and policy
- Invoking reasoner:
```
http://mr-burns.w3.org/cgi-bin/server_cgi.py?logFile="name of log file"&rulesFile="name of policy file"
```
- View justification: JustificationUI
Local
- execute python reasoner on commandline with local log and policy
- load output generated in firefox extension (load)