Within the past five years,
the Semantic Web research community has brought to maturity a
comprehensive set of foundational technology components, and this both
at the conceptual level and in the form of prototypes and software.
This includes, among other assets, ontology engineering methodologies,
standardized ontology languages, ontology engineering tools, and
infrastructure like APIs, repositories, and scalable reasoners, plus a
plethora of work for making the Deep Web and
computational functionality in the form of Web Services accessible at a
semantic level. However, in order for these research achievements to
materialize into large scale corporate applications, they must be
complemented by prototypes, methods, and best practices which support
enterprises in the adoption of Semantic Web technology. This includes:
Convincing showcases and
proofs-of-concept that demonstrate the technical feasibility in
relevant business scenarios.
Methods to assess the
costs and business value of semantic technology; in particular, such
help estimate the costs involved in the development and usage of
and to quantify the operational and strategic benefits of
Metrics to evaluate and
compare existing ontologies, ontology engineering methodologies, and
tools in terms of technical quality and organizational fit. This
includes metrics to determine the usability of a particular ontology in
a specific business scenario.
Means to monitor the quality
of ontology development and deployment processes.
The availability of best practices, convincing showcases, and
quantitative and qualitative metrics that help manage the various
stages of building ontologies and ontology-based systems will be
important catalysts for disseminating Semantic Web research into