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aims at a higher added value for all stakeholders
with decreased (development and) operation costs.
The origins and terminology of these trends are
different and, therefore, their fusion is a complex
task to be made in order to achieve viable solutions
for smart spaces and their applications.
Due to the dynamic nature of smart spaces,
it is crucial that the development methodology
supports the attaining of this dynamism at design
time and run time. This dynamism needs to be
supported by:
tion staff, and (end-user) application devel-
opers. These tools shall tolerate the evolu-
tion of smart spaces and software/service
engineering technologies.
•
Providing viable techniques/methods for
collecting end-user experiences, analyzing
the collected information and representing
the analysis results in a convenient form
for all of the stakeholders in order to get
their future improvements incorporated
into the smart space evolution cycle.
•
Agile methods that have proved to embody
an ability to support dynamic work alloca-
tion among development teams and still
provide results of high quality.
CONCLUSION
The ASSDE approach exploits ontology orienta-
tion for realizing interoperability and context-
awareness in smart space application develop-
ment and evolution. The approach follows a set
of principles defined for the development of the
interoperability platform and the applications
executed on top of it. The key drivers of the ap-
proach are: i) interoperability provided on the
information level; ii) shared information repre-
sented in a uniform and application independent
way; iii) a flexible platform that can be used with
any programming language, service platform and
ontology; iv) a platform that can be enhanced with
new ontology and required functionality; and v) a
platform that provides adaptive services and sup-
ports context-aware applications. Besides these
technical drivers, there are also non-technical ones;
the smart space application engineering should
be consistent with the IOP business models and
it should be mapped to the value chain(s) of the
smart space stakeholders. This is to ensure that
the platform provides support for all of the stake-
holders involved in the smart space development.
Moreover, legacy devices and systems should be
able to exchange information through smart spaces
by using domain ontologies. This guarantees that
the legacy can be exploited in the initiation and
evolution of smart spaces. In practice, this feature
•
Ontology and model driven software engi-
neering methodology that helps in manag-
ing design knowledge on different abstrac-
tion levels, the separation of concerns, and
binding times. These three properties, i.e.
abstraction, separation and binding, are the
core elements of dynamic systems.
•
Evolution support that requires new light-
weight solutions for ontology mapping,
ontology retrieval, model transformation
and reasoning, and learning algorithms
for adding intelligence into smart space
applications.
Therefore, the following research items require
an extensive attention within the smart space
communities:
•
Specifying a minimal standard context
ontology that covers all the dimensions of
context and is applicable to all the types of
smart spaces.
•
Encouraging the fusion of ontology ori-
entation and model driven engineering by
developing tool environments for the dif-
ferent stakeholders, i.e. owners, service
providers/consumers, developers, opera-
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