Thinking about interlinking data contexts

Time to remind the project statement. To build a semantic profiling framework to support the connection of researchers. The main use case and application that the framework has to support is illustrated by what could be called: “the conference case”. Scientists and researchers are interested in very specific topics, this is best verified by the conferences they are attending. Another trend is that they all blog and tweet about these events. This creates huge opportunities for profiling. The attendees tweet about what they notice, what they remark as interesting for their own projects. What if we could connect these users using this information? We could call an application that does just that “Scientific Profiling“. This approach comes from the concept that the data produced in social networks can have true value if properly annotated and interlinked. A second requirement is to create a suitable context in which this information can get meaning. This is very important to identify which ontologies should be used. Read more of this post

Integrating 3 semantic web layers: Communities, ontologies and content

Reading a comment in Trends & Controversies in IEEE Intelligent Systems by Steffen Saab led me to an interesting paper by Peter Mika. It supports my conviction that the integration of social network data from different sources is very important. The information produced in social networks has true value since it contains many knowledge. This knowledge is being communicated there between people that are a members from a specific (research) group or community. There are however some issues to be considered. They are outlined very clearly in this article.

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