Andrzej Uszok, Jeffrey M. Bradshaw, Renia Jeffers
Institute for Human and Machine Cognition (IHMC), 40 S. Alcaniz, Pensacola, FL 32501, USA
{auszok, jbradshaw, rjeffers}@ihmc.us
WWW: http://www.ihmc.us/

Austin Tate, Jeff Dalton
Artificial Intelligence Applications Institute, University of Edinburgh, Edinburgh EH8 9LE, UK
{a.tate, j.dalton}@ed.ac.uk
WWW: http://www.aiai.ed.ac.uk/

Abstract
In this paper we describe our experience in applying KAoS services to ensure policy compliance for Semantic Web Services workflow composition and enactment. We are developing these capabilities within the context of two applications: Coalition Search and Rescue (CoSAR-TS) and Semantic Firewall (SFW). We describe how this work has uncovered requirements for increasing the expressivity of policy beyond what can be done with description logic (e.g., role-value-maps), and how we are extending our representation and reasoning mechanisms in a carefully controlled manner to that end. Since KAoS employs OWL for policy representation, it fits naturally with the use of OWL-S workflow descriptions generated by the AIAI I-X planning system in the CoSAR-TS application. The advanced reasoning mechanisms of KAoS are based on the JTP inference engine and enable the analysis of classes and instances of processes from a policy perspective. As the result of analysis, KAoS concludes whether a particular workflow step is allowed by policy and whether the performance of this step would incur additional policy-generated obligations. Issues in the representation of processes within OWL-S are described. Besides what is done during workflow composition, aspects of policy compliance can be checked at runtime when a workflow is enacted. We illustrate these capabilities through an example where policies control runtime queries and return results from the CMU Semantic Matchmaker. Finally, we outline plans for future work.