OWL-POLAR: A Framework for Semantic Policy Representation and Reasoning

Abstract

In a distributed system, the actions of one component may lead to severe failures in the system as a whole. To govern such systems, constraints are placed on the behaviour of components to avoid such undesirable actions. Policies or norms are declarations of soft constraints regulating what is prohibited, permitted or obliged within a distributed system. These constraints provide systems-level means to mitigate against failures. A few machine-processable representations for policies have been proposed, but they tend to be either limited in the types of policies that can be expressed or are limited by the complexity of associated reasoning mechanisms. In this paper, we present a language that sufficiently expresses the types of policies essential in practical systems, and which enables both policy-governed decision-making and policy analysis within the bounds of decidability. We then propose an OWL-based representation of policies that meets these criteria and reasoning mechanisms that use a novel combination of ontology consistency checking and query answering. The proposed policy representation and reasoning mechanisms allow development of distributed agent-based systems that operate flexibly and effectively in policy-constrainted environments.

Enabling smart environments through scalable policy reasoning and Internet of Things

“…There is a variety of policy frameworks: some with rich policy representations (Kagal, Finin, & Joshi, ; Sensoy, Norman, Vasconcelos, & Sycara, ; Uszok et al, ), and some targeting pervasive environments (Qwasmi & Liscano, ; Twidle, Dulay, Lupu, & Sloman, ; Zhu, Keoh, Sloman, & Lupu, ). However, they are either not scalable—e.g., to create and refine policy instances to large number of devices (Sensoy et al, )—or expressive enough to use high level concepts to describe devices and situations (Twidle et al, ).…”

“…OWL‐POLAR (Sensoy et al, ) is an ontology‐based policy framework that differs from other ontology related frameworks (e.g., Rei: Kagal et al, ; KAoS: Uszok et al, ) as it uses conjunctive formulas, which are then converted into SPARQL (Prud'hommeaux & Seaborne, ) queries to perform DL‐based reasoning with Pellet (Sirin, Parsia, Grau, Kalyanpur, & Katz, ). It aims to offer an expressive policy language while preserving the decidability of the reasoning process.…”

“…We can detect such conflicts with an algorithm that utilizes query freezing (Sensoy et al, ; Ullman, ). However, the success of detection relies on the action descriptions of policies and the structure of the TBox.…”

Automatic policy enforcement on semantic social data

“…There are various proposals in the literature on Normative Multiagent Systems (NorMAS) for the declarative specification of norms [6,11] and policies [30,31] and of frameworks for their management, enforcement, and monitoring using different languages [12,32]. The choice of using formal declarative languages (like logics or logic programming languages) has many important advantages, because it makes possible:…”

“…Norms/policies can be used to regulate electronic institutions, electronic commerce, and to deal with security issues [25]. Among those studies, the most relevant for this paper are the one that use Semantic Web Technologies for norms formalizations and enforcement [10,12,30,33], but none of them is focussed on regulating the performance of actions on big amount of data.…”