Semantic Web-Based Information Systems: State-of-the-Art ...

Kaykova, Khr yenko, Kovtun, Naumenko, Terz yan, & Zharko
Figure 1. Layers of the GUN architecture
Resource + Adapter +
Agent + Platform =
GUN Resource
Resource
platform
Resource
agents l ayer
Resource
adapters layer
each resource and are able to monitor semantically reached data coming from the
adapter about states of the resource, decide if more deep diagnostics of the state is
needed, discover other agents in the environment that represent decision makers, and
exchange information (agent-to-agent communication with semantically enriched
content language) in order to get diagnoses and decide if a maintenance is needed.
It is assumed that decision-making Web services will be implemented, based on
various machine-learning algorithms, and will be able to learn, based on samples
of data taken from various service consumers and labeled by experts. Use of agent
technologies within the GUN framework allows mobility of service components
between various platforms, decentralized service discovery, FIPA communication
protocols utilization, and MAS-like integration/composition of services (Ermolayev,
Keberle, Plaksin, Kononenko, & Terziyan, 2004).
Main.Stages.Toward.Smart.Resources
Resources
layer
Resources of a
new generator
(Semant c Adapter Ins de)
We have divided the implementation of the GUN concept for the maintenance domain
into the following three stages: adaptation, proactivity, and networking. Each stage
assumes design of a more enhanced version of the maintenance environment.
The adaptation stage defines Semantic Web-based framework for unification of
maintenance data and interoperability in the maintenance system by adding explicit
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