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Navigating Science

The scientific literature forms a vast network in which tens of millions of articles are linked by scholarly citations. This network grows dynamically and organically, doubling in size every ten to twenty years. It is within this growing network ecosystem that scholars conduct their scholarship. But how can one find one’s way around this vast edifice in which new rooms, corridors, vestibules, and wings are continually added on an everexpanding foundation? We propose that the revolution in digital scholarship provides the raw material in the form of citation graphs and digital text. Sufficiently intelligent algorithms, acting upon this raw material, will provide new and ever more powerful ways for scholars to navigate the vast academic literature.

Featured Projects
Recommendation Engine
Our recommendation engine, known as Eigenfactor Recommends™ provides suggested readings to accompany a focal paper. The recommendation engine uses the hierarchical structure of scholarly fields along with methods for ranking the importance of individual articles to deliver tailored recommendations.
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