The JSTOR Labs team recently partnered with Dr. Jevin West's team at the University of Washington DataLab to test and develop tools to help researchers introduce themselves to key topics and publications from other fields. The results of their work have been incorporated into JSTOR Sustainability—a new site, currently in beta, that contains a broad range of scholarly articles and research reports dealing with environmental stresses and their impact on human society.
Dr. West's lab created the Eigenfactor, which uses citation networks to evaluate the impact of scholarly publications, and recently introduced Eigenfactor Recommends, which helps identify the classic and foundational papers within a field as well as the latest innovations.
JSTOR has created a semantic index which identifies more than 1,500 key terms in Sustainability. By uniting this semantic index with the algorithms that drive Eigenfactor Recommends, the two labs were able to create a series of topic pages that provide overviews of key areas in Sustainability, including a topic description, important journals and authors, and related topics. One of the key features of the topic pages is Influential Articles—an interactive timeline of the articles that have most influenced the topic. The Eigenfactor Recommends functionality also powers the 'background reading' recommendations that appear alongside each article on JSTOR Sustainability.
JSTOR Labs employed a process called 'flash builds' for the collaboration, which allowed the two teams to go from ideation to a tested prototype in only a week's time.
Interested parties may visit http://labs.jstor.org/sustainability/ to see the JSTOR Sustainability topic pages. A video of the collaboration is also available at http://labs.jstor.org/blog/#!the_(rapid)_evolution_of_an_idea.
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