For all of you Java developers out there, Clark&Parsia has released an initial integration between Stardog and Spring. The Stardog website states, “Spring is a platform to build and run enterprise applications in Java. Stardog’s Spring support makes life easier for enterprise developers who need to work with Semantic Web technology—including RDF, SPARQL, and OWL—by way of Stardog. The Spring for Stardog source code is available on Github. A more feature-full version of will be available in Stardog Enterprise Edition.” Read more

Announcing Semantic Tech & Business Conference - San Francisco 2012

Semantic Tech & Business Conference is returning to San Francisco in June! Join us from June 3-7 for complete coverage of Big Data, Linked Data, Extreme Information Management, and Semantic Web. From breakthrough approaches to solving business problems to the big data implications of fast–evolving technologies, SemTechBiz provides you with an unparalleled interactive experience and delivers tangible business value. We're offering a special early rate when you register by February 17. Sign up now!

Diffbot, a semantic start-up in Palo Alto, CA, is looking for Machine Learning Interns and Web Development Interns. According to the post, “At Diffbot, we apply computer vision techniques to web documents to extract out semantic metadata. These services are used within hundreds of products at companies such as Cisco, Evernote, StumbleUpon, and AOL. We also offer free access to our technology to developers via an open API. Internally, we are using our technology to develop the next generation semantic results engine for the web. Check out http://diffbot.com for more information about our technology and APIs.” Read more

Photo Courtesy: FlickR/elward-photography

There seems to be growing sentiment that 2011 is the year the Semantic Web really, truly happens (see here and here) – but not blindness to the challenges that exist around making it happen, not just on the web at large but within the enterprise community.

One gap to close: Growing the talent that will ease adoption by those enterprises and help them succeed in their desires to get more out of their data. The economic doldrums have fostered the desire to do just that, says Richard Stanton, a thought-leader and consultant for a number of businesses on the practical application of Semantic Web technologies and former CEO of the semantic web job/volunteer matchmaking site Bintro (which has ceased operations).

“The mission in tough economic times is to polish up assets,” he says, and what asset is more powerful or valuable than the data held by businesses ranging from e-commerce plays to highly specific industries such as health care to hosters of large content repositories of every stripe. “Anytime you have to take stock of your own inventory and use it more wisely is a time that you look for new solutions.”

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Empire is an implementation of the Java Persistence API (JPA) for RDF and the Semantic Web. Instead of another implementation of relational databases, Empire implements JPA for RDF and SPARQL, thus allowing developers who are familiar with JPA, but not with semantic web techologies like RDF, to make an easy transition into this brave, new world. JPA is a specification for managing Java objects, most commonly with an RDBMS; it’s industry standard for Java ORMs.

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I decided to conduct an informal survey in an attempt to gauge the current level of adoption and growth potential for Semantic Technology as an industry vertical. The results indicate to me that while progress is being made we still need to do a better job of delivering the message – this messaging problem is the number one reason why adoption of Semantic Technologies and Semantic Methodologies is proceeding slower than we had anticipated. 

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Your guide to building working solutions for the Semantic Web.

We wrote Semantic Web Programming to offer a useful guide to get the Semantic Web to do stuff – such as data integration and rich data analysis. We are active developers in this space and directly see its potential.  We outline the key concepts, tools, and methods you need to program the Semantic Web to achieve these goals.  Our book is filled with practical, easy-to-follow, examples using working code to illustrate how to take advantage of the many data sources and services available today, especially non-semantic ones like instant messaging, relational databases, and web services such as those offered by Facebook. 

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Executive Summary

A JCAF agent represents a network agent with capabilities specialized for defending the cyber-assets of an organization.  Agents may receive and execute instructions, either in isolation or in collaboration with other agents, Web applications, or people. We need to ensure that an agent can correctly execute payloads (scripts or programs) that they receive or retrieve. The potential incompatibility of agents and payloads motivates the need for a mechanism to describe and reason about agents, payloads, and other related assets.

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Executive Summary

Today, one of the biggest challenges in web technologies is information retrieval in digital resource repositories such as digital libraries and the Internet. To cope with this information growth, existing search methods will need to be enhanced to continue an acceptable level of relevancy and efficiency in the results returned. In this paper two search methods are compared: fulltext search and search enriched with a query reformulation based on semantic technologies. Both of these are implemented in a search module – SQE Semantic Query Expansion.

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Executive Summary

In this article, we describe an approach to automating the generation of Java™ agent configuration files which leverages the Web Ontology Language (OWL), the SPARQL query language, and Extensible Stylesheet Language Transformations (XSLT). 

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— ANDREW CRAPO, AMY ARAGONES

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.

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