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https://doi.org/10.1109/servic...
Article . 2007 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2024
Data sources: DBLP
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Exchanging Policies between Web Service Entities using Rule Languages

Authors: Nima Kaviani; Dragan Gasevic; Marek Hatala; Gerd Wagner 0001; Ty Mey Eap;

Exchanging Policies between Web Service Entities using Rule Languages

Abstract

Web rule languages with the ability to cover various types of rules have emerged to make interactions between Web resources and broker agents possible. The chance of describing resources and users of a domain through the use of vocabularies is another feature of Web rule languages. Combination of these two properties makes Web rule languages an appropriate medium to make a hybrid model of representing both contexts and rules of a policy-aware system, such as a Web service. In this paper, we describe how REWERSE rule markup language (R2ML) can be employed to bridge between different policy languages using its rich set of rules, vocabulary, and built-in constructs. We show how the concepts of the KAoS and Rei policy languages can be transformed to R2ML and then from R2ML to the other policy languages. Following these mappings, we have implemented transformers, which enable us not only to share policies between KAoS and Rei, but also to transform policies onto other rule languages (e.g., F-Logic) for which transformations from/to R2ML are already developed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average