RENDER/Overall Project Description
The World Wide Web offers the possibility to publish, to share and to retrieve huge amounts of information. To every imaginable topic one can find a variety of viewpoints, opinions, and background information. But nowadays the user is frequently missing some important aspects of a particular topic. Sometimes the user may even get the impression that all opinions that can be found on a certain issue share a common point of view. This is due to the increasing number of filtering mechanisms, which are used to preprocess the available data according to personalized preferences or settings. Therefore, it has become difficult to get an all-embracing overview of a topic - much valuable information is inaccessible or can only be retrieved in a rather time consuming process.
Funding of RENDEREdit
The EU funded project RENDER - Reflecting Knowledge Diversity - will engage with the challenges of diversity in knowledge and information. The project is funded under the 7th research framework programme of the EU. The project started in October 2010 and has a duration of three years. It is coordinated by the Karlsruhe Institute of Technology (KIT).
Seven partners from six European countries are involved and Wikimedia Deutschland is one of them. The other partners are Karlsruher Institut für Technologie, (Germany - lead), Institut Jozef Stefan (Slovenia), Ontotext (Bulgaria), STI Innsbruck (University of Innsbruck, Austria), Telefonica (Spain) and Google Ireland Ltd. (Ireland). Apart from Wikimedia Deutschland, further case studies will be realized under the direction of Google Ireland Ltd., and Telefonica I+D. Further information about the participants, the case studies and project deliverables can be found at http://render-project.eu/. At Wikimedia Deutschland the project is managed by Angelika Adam .
RENDER is set out to develop methods, techniques, software and data sets which enable scholars as well as users of internet applications such as Wikipedia, to understand, to describe, to process and to make use the diversity of knowledge and information. To verify the scalability and use of the research, results will be applied in three case studies.