Semantic Web Languages for Policy Representation and Reasoning: A Comparison of KAoS, Rei, and Ponder

Authors: Gianluca Tonti^1,2, Jeffrey M. Bradshaw¹, Renia Jeffers ¹, Rebecca Montanari², Niranjan Suri¹, and Andrzej Uszok¹

¹Institute for Human and Machine Cognition (IHMC)
University of West Florida
40 S. Alcaniz Street
Pensacola, FL 32501
USA
EMail: { jbradshaw, rjeffers, nsuri, gtonti, auszok}@ihmc.us
WWW: http://www.ihmc.us/

² Dipartimento di Elettronica, Informatica e Sistemistica (DEIS)
University of Bologna
viale Risorgimento, 2
40136 Bologna
ITALY
EMail: {rmontanari, gtonti}@deis.unibo.it
WWW: http://www.deis.unibo.it/

Abstract

Policies are being increasingly used for automated system management and controlling the behavior of complex systems, allowing administrators to modify system behavior without changing source code or requiring the consent or cooperation of the components being governed. Past approaches to policy representation have been restrictive in many ways. By way of contrast, semantically-rich policy representations can reduce human error, simplify policy analysis, reduce policy conflicts, and facilitate interoperability. In this paper, we compare three approaches to policy representation, reasoning, and enforcement. We highlight similarities and differences between Ponder, KAoS, and Rei, and sketch out some general criteria and properties for more adequate approaches to policy semantics in the future.

Research Paper at 2nd International Semantic Web Conference ( ISWC2003), October 20-23, 2003, Sanibel Island, Florida, USA