CSEDU 2013, the International Conference on Computer Supported Education was taking place in Aachen, Germany this year. The conference was addressing different e-learning themes such as Information Technologies Supporting Learning, Learning/Teaching Methodologies and Assessment, Ubiquitous Learning, Social Context and Learning Environments as well as Cloud Education Environments.
On behalf of AKSW, Ali Khalili and Darya Tarasowa presented two papers namely “CrowdLearn: Crowd-sourcing the Creation of Highly-structured E-Learning Content” and “Balanced Scoring Method for Multiple-mark Questions” at the conference (with acceptance rate 13% for full papers). The corresponding slides are available on SlideWiki (CrowdLearn, Balanced Scoring). The CrowdLearn paper discussing the underlying philosophy behind SlideWiki received many attention from the audience and was also nominated for the best-paper award in the conference. There were many people who were interested in using SlideWiki for publishing their teaching material and to share their educational content with other people in an OpenCourseWare environment.

Most of the keynotes were addressing MOOCs (Massive Open Online Courses) and the new paradigms emerging on the Web for social learning. SlideWiki as an example of collaboration platform was also mentioned by professor Michael E. Auer in his keynote about the new engineering challenges in e-learning.

On the second day of Sören’s short trip to Korea, we participated in the Open Data Conference of the Information Society Agency (NIA). NIA seems to be implementing a comprehensive Open Data strategy (also involving LinkedData). Looks like South Korea is quite advanced in this regard already. In addition to my talk about Linked Open Government Data, there was also a talk by Haklae Kim about the Korean Open Knowledge foundation chapter. There were also some industry representatives (Samsung, LG) in the audience and interested in applying Linked Data in enterprise environments.

You can find pictures from the event on Facebook.

In the recent years the LOD2 stack established a collection of applications developed in the context of the LOD2 project, presented as an unified environment. These applications are referred to as components although they can also be installed independently. However, having all these components in a single environment eases the access from one application to the other and improves the UI experience.

As LOD2 stack is now available in it’s second version, questions of usability and end users experience came more in the focus of the ungoing development. So the LOD2 consortium set up  a survey asking users of the LOD2 stack (or the online Demonstrator) for feedback, regarding their experiences with the LOD2stack and the separate components. The outcome of this, is to fine tune development and improve the user experience in each phase of the Linked Data life cycle.

The survey is open from April 15 to June 30 and will only demand 15 minutes of your time.

We are happy to announce the preview release of our RDFaCE WYSIWYM content editor special edition for Schema.org. RDFaCE (RDFa Content Editor) extends the TinyMCE rich text editor to facilitate the authoring of semantic documents. This version of RDFaCE is customized for annotating content in RDFa or Microdata formats based on Schema.org vocabularies. It is also published as a WordPress plugin to promote semantic content authoring among a wide variety of end users.

The main features of RDFaCE Schema.org edition are:

• Support of flexible form-based approach to annotate content using Schemas defined by Schema.org
• Providing a Schema creator module which creates a subset of Schema.org schemas based on preferred user domain and requirements.
• Providing a flexible color schemes for Schema.org schemas.
• Support of RDFa as well as Microdata formats.
• Support of automatic content annotation using external NLP APIs (Alchemy, Extractiv, Open Calais, Ontos, Evri, Saplo, Lupedia and DBpedia spotlight.).
• This feature provides an initial set of annotations for users that can be modified and extended later on.
• Combination of the results of multiple NLP APIs based on user preferences. This features improves the quality of automatic annotations.
• One click editing of annotated entities.

For more information on RDFaCE visit:

• RDFaCE project: http://aksw.org/Projects/RDFaCE
• Online demo: http://rdface.aksw.org/
• Download WordPress plugin: http://wordpress.org/extend/plugins/rdface/
• Video tutorials: http://www.youtube.com/playlist?list=PLSBPxopOi20UsJmbqFp2OZlLWBY2LviP6
• Annotation steps in RDFaCE: http://slidewiki.org/slide/25542/latest
• Sourcecode: https://bitbucket.org/ali1k/rdface/

Every day, approximately 3000 new articles are published in biomedical journals. That averages to more than 2 articles every minute! Managing this large amount of data is a challenge in itself. Yet, ensuring that this wealth of knowledge is used for the sake of the patients in a timely manner is an even more demanding task for both computer scientists and biomedical experts.

The BioASQ project, which started on October 1st 2012 and runs for 2 years, aims to push research in information technology towards highly precise biomedical information retrieval systems. The project will achieve this goal through a competition (challenge), in which systems from teams around the world will compete. BioASQ will provide the data, software, hardware and the evaluation infrastructure for the challenge. By these means, the project will ensure that the biomedical experts of the future can rely on software tools to identify, process and present the fragments of the huge space of biomedical resources that address their personal questions.

The tasks included in the BioASQ challenges will help advance the state of the art in two fields. First, the automatic classification of biomedical documents will be improved. Here, systems will be required to tag large numbers of scientific biomedical articles with terms from a predefined biomedical vocabulary. Additionally, the challenge will evaluate how well systems identify text fragments in scientific articles, and related data in public knowledge bases, in order to answer questions set by the European biomedical expert team of BioASQ. Further results of the project will include a set of open-source tools and a social network that will support experts in setting up similar challenges, beyond the end of the project.

The BioASQ team combines researchers with complementary expertise from 6 organisations in 3 countries: the Greek National Center for Scientific Research “Demokritos” (coordinator), participating with its Institutes of ‘Informatics & Telecommunications’ and ‘Biosciences & Applications’, the German IT company Transinsight GmbH, the French University Joseph Fourier, the German research Group for Agile Knowledge Engineering and Semantic Web at the University of Leipzig, the French University Pierre et Marie Curie‐Paris 6 and the Research Center of the Athens University of Economics and Business in Greece. Moreover, biomedical experts from several countries assist in the creation of the evaluation data and a number of key players in the industry and academia from around the world participate in the advisory board of the project.

More information can be found at: http://www.bioasq.org
Project Coordinator: George Paliouras (paliourg@iit.demokritos.gr)