The Semantic Web vision of the World Wide Web Consortium is to extend the current Web, so that “information is given well-defined meaning, better enabling computers and people to work in cooperation.”¹  This is important, as the mix of content on the web and in applications built using web architectures is shifting from exclusively human-oriented content to computer-mediated content.

Executive Summary

Semantic Web Service (SWS) frameworks especially address service discovery, composition and execution. This article first describes WSMO-Lite, a lightweight ontology of service semantics that builds on a W3C standard for semantic annotations of WSDL. WSMO-Lite distinguishes four kinds of service semantics (functional, nonfunctional, behavioral and information) and it provides a simple and modular ontology for capturing these semantics. Secondly, the article describes MicroWSMO, an approach for semantic description of RESTful services, which have been largely neglected both in context of SOA and in SWS research. MicroWSMO uses WSMO-Lite semantics and thus integrates RESTful services in our Semantic Web Service automation.

Executive Summary

There are a variety of tools and approaches available to model the enterprise and its processes. Almost all of these lack a clear, standards-based semantics and the ability to integrate different types of enterprise models. Semantic technology addresses some but not all enterprise modeling needs. Hence enterprise modeling can derive significant benefit from embracing semantics, and semantic technology might be made significantly more robust and valuable by applying the community’s skills to enterprise modeling problems at-hand.

Executive Summary

Chemistry is an important and high-value vertical in the modern world and the “semantification” of chemistry will be crucial for further rapid innovation not only in the discipline itself, but also in related areas such as drug discovery, medicine and materials design. This article provides a short overview over the current technological state of the art in semantic chemistry and also discusses some obstancles, which have, so far, impeded the widespread uptake of chemistry in the domain.

My first encounter with semantic web technologies grew out of my desire for a persistence mechanism that modeled graphs with more ease and freedom than relational based models.  I was specifically interested in any persistent store that would allow me to create new structures without having to fiddle with the intricacies of a rigid schema.  I found my solution in Jena, a Java framework for building Semantic Web applications. 

In this initial article, I provide an overview of my ‘version’ of SSOA. I summarize a couple of perspectives and then highlight the technical underpinnings.  I close by summarizing and supplying a projected roadmap for this column.  As a point of order, my background is with the U.S. Navy; therefore, my perspective tends toward military/government settings. However, as I will indicate in a subsequent article, at their core all organizations strive to be the best at the same process: decision making.

Executive Summary

The current information management tools and techniques have not kept pace with the dramatic growth of data within the enterprise. Much of this new data is represented in an unstructured or semi-structured format. The volume of the data makes it unmanageable by humans and the structure of the data makes it unavailable for machine processing. This has created a situation where information is now hidden or lost within the enterprise. This lost information has a significant business impact in the form of unmanaged risk and lost opportunities for revenue or savings.

Entity Extraction is the process of automatically extracting document metadata from unstructured text documents.  Extracting key entities such as person names, locations, dates, specialized terms and product terminology from free-form text can empower organizations to not only improve keyword search but also open the door to semantic search, faceted search and document repurposing.  This article defines the field of entity extraction, shows some of the technical challenges involved, and shows how RDF can be used to store document annotations. It then shows how new tools such as Apache UIMA are poised to make entity extraction much more cost effective to an organization.

Part I : Advice from Nova Spivack, CEO of Radar Networks at SemTech 2008. Radar Networks is the creator of Twine, a promising semantic-social-networking collaboration app.

SR: Nova, I’m looking for some advice. The semantic web field is exciting, it’s promising. Suppose I’m a fairly competent programmer looking in from the outside. How do I break in and find work in the semantic web field?