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 that help estimate the costs involved in the development and usage of ontologies, and to quantify the operational and strategic benefits of ontology-based systems.

• 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 enterprise applications.