Today, we released a major update of the DL-Learner plugin for Protege 4, the popular ontology editor. The plugin allows you to get suggestions for axioms you may want to add to your OWL ontology by analysing the instance data using the DL-Learner framework. A screencast is available to show you how it works. The plugin is installable via the standard Protégé plugin mechanism (Protege 4 stable release required). This version allows to fine tune the language features you want to use and displays the length of expressions, which have been searched. It also fixes bugs related to inconsistency handling. More information can be found on the plugin wiki page. Enjoy!

OKCon, now in its fifth year, is the interdisciplinary conference that brings together individuals from across the open knowledge spectrum for a day of presentations and workshops.

Open knowledge promises significant social and economic benefits in a wide range of areas from governance to science, from culture to technology. Opening up access to content and data can radically increase access and reuse; improving transparency, fostering innovation and increasing societal welfare.

In addition to high-profile initiatives such as Wikipedia, OpenStreetMap and the Human Genome Project, there is enormous growth among open knowledge projects and communities at all levels. Moreover, in the last year, many governments across the world began to open up their data.

And it doesn’t stop there. In academia, open access to both publications and data has been gathering momentum, and similar calls to open up learning materials have been heard in education. Furthermore, this gathering flood of open data and content is the creator and driver of massive technological change. How can we make this data available, how can we interlink it, how can we use it to collaborate and share our work?

• where: London, UK
• when: Saturday 24th April, 2010
• www: http://www.okfn.org/okcon/
• cfp: http://www.okfn.org/okcon/cfp/ (deadline: Jan 31st 2010)
• hashtag: #okcon2010

Some AKSW members are involved in next year’s Semantic Web in Use Track of the Extended Semantic Web Conference 2010. Yes, its called “Extended”, instead of formerly “European”, in order to reflect the broadening of the topics of interest. Next year’s In-Use track is particularly devoted to:

• Description of concrete problems in specific application domains, for which Semantic Web technologies can provide a solution.
• Description of an implemented application of Semantic Web technologies in a specific domain.
• Assessment of the pros and cons of using Semantic Web technologies to solve a particular business problem or other practical problems in a specific domain.
• Comparison with alternative or competing approaches using conventional or competing technologies.
• Assessment of the costs and benefits of the application of Semantic Web Technologies, e.g. time spent on implementation and deployment, efforts involved, user acceptance, returns on investment.
• Evidence of deployment of the application, and assessment/evaluation of usage/uptake.
• Domains of interest include, but are not limited to: semantics in the enterprise, improving access to governmental data, semantics-based solutions for health care and life sciences, digital libraries, games with a purpose, semantic geo-data management.

More information can be found at: http://www.eswc2010.org/calls/semantic-web-in-use

Today, we released DL-Learner Build 2009-05-06. DL-Learner is a tool for learning OWL class expressions from examples and background knowledge. It extends Inductive Logic Programming (ILP) to Description Logics and the Semantic Web. Some notable features in this release are:

• a new learning algorithm (CELOE) designed specifically for extending OWL ontologies
• a Protege plugin using CELOE
• a manual for getting started using DL-Learner
• performance improvements through stochastic methods
• more learning examples, unit tests, code quality improvements

DL-Learner can be used to:

• solve general supervised Machine Learning problems using ontologies as background knowledge (given as OWL files, SPARQL endpoints, etc.), e.g. it was used to predict whether chemicals can cause cancer
• help knowledge engineers by learning definitions and subclass axioms (see the Protege plugin and another one for OntoWiki is in progress)
• generating user recommendations when browsing knowledge bases

I’d like to thank all contributors, in particular active developers and everyone who sent us valuable feedback.

Today, we released a major update of the DL-Learner plugin for Protege 4, the upcoming release of the popular ontology editor. The plugin allows you to get suggestions for axioms you may want to add to your OWL ontology by analysing the instance data using the DL-Learner framework. Again, we prepared a small screencast to give you an idea of how it works. The plugin is installable via the standard Protégé plugin mechanism (Protege 4 build 110 or higher required). This version comes with a completely new suggestion algorithm and enhanced performance. More information can be found on the plugin wiki page. Thanks to Christian Kötteritzsch for his implementation work and Nick Drummond for supporting us in integrating the plugin.