MeisterLabs Joins CODE Project for Semantic Web Research

CODE, a recently started research project funded by the European Union’s Seventh Framework Programme (FP7), will investigate how facts can be extracted from 40 million research papers, visualized, and interlinked with existing knowledge bases on the Web. Over the next two years, mind mapping innovator MeisterLabs will join forces with researchers from the Know-Center (Austria) and the University of Passau (Germany) and the distinguished UK-based web startup Mendeley to re-shape access to scientific knowledge.

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“In Sir Isaac Newton’s words: We’re standing on the shoulders of giants,” says Prof. Dr. Michael Granitzer, scientific coordinator of CODE. “Research of the future requires knowledge of the research of the past. But do we really know what we know? Every day, humanity discovers new findings on the inner working of the world we are living in. We identify new drugs or discover new, more efficient mobile communication technology. However, keeping pace with reading the exponentially growing amount of science literature becomes nearly impossible.”

CODE (“Commercially Empowered Linked Open Data Ecosystems in Research”) will enable users to gain new insights through the provided facts and to share their discoveries with colleagues. These discoveries can be of high value when comparing different drug studies, visualising research trends, or organising contradicting facts on the performance of different algorithms.

At the technical core of the project, new Natural Language Processing technologies will be developed by the Know-Center, which crowdsourced fact extraction on scientific literature via Mendeley’s platform. The extracted facts will be integrated into the Linked Data cloud by the University of Passau and organised in mind maps in the award-winning MindMeister platform.

Crowdsourcing will enable CODE to build a unique knowledge base fuelled by facts and findings contained in scientific literature. The developed technology will bootstrap a marketplace around research data, generating a large, high-quality, machine-readable scientific fact database, empowering researchers to “stand on the shoulders of giants” once more.

More information about the CODE project can be found at

About the Project Partners

MeisterLabs (Munich, Germany, – MeisterLabs develops and provides web-based productivity tools focusing on simplicity, usability and easy collaboration. Its flagship product, MindMeister, is the market-leading web-based mind mapping and brainstorming solution.  Over 500 million ideas have been generated by individuals and businesses using its unique, award-winning interface.  As a cloud-based solution, MindMeister functions in any web browser and comes complete with native mobile applications for iPhone, iPad and Android.

Mendeley (London, UK, – Mendeley is one of the world’s largest research collaboration platforms, used by over 1.6 million researchers worldwide. Mendeley provides real-time statistics, trends by research area, and recommendations for related research based on its crowd-sourced database of over 225 million research documents. Launched in January 2009, the company has offices in London and New York, and its investors include former founders and executives of Skype, and Warner Music Group.

Know-Center (Graz, Austria, – Austria’s competence center for knowledge management and knowledge technologies is an innovation point at the interface between science and industry. Since its establishment in 2001, the Know-Center has been developing highly innovative IT solutions for knowledge management. The Know-Center is being funded by Austria’s Competence Center Program COMET.

University of Passau (Germany, – Founded in 1978, the University of Passau combines the most up-to-date infrastructure with state-of-the-art technology, offering its over 10,000 students an ideal place to study. The two chairs involved in CODE, the chair of distributed information systems and the chair of media informatics, investigate distributed databases, multimedia systems, and automatic media analysis technologies, to improve media access and management.