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Science Surveyor
Algorithm-based method to help science journalists rapidly and effectively characterize the rich literature for any topic they might cover, as a way to inform and assist news judgment and reporting.

Centrality view
Centrality / Pagerank
Topic Map
CSR Science Surveyor Visualization 1
CSR Science Surveyor Visualization 2

One of the biggest challenges facing science journalists is the ability to quickly contextualize journal articles they are reporting on deadline. A science reporter must rapidly get a sense of what has come before in the field, understand whether the new paper represents a significant advance or not, and establish whether this finding is an outlier or part of the field’s consensus. Doing all that within a matter of hours or a few days is often impossible. The consequences of these limitations are serious and well documented. Science journalists are often overly dependent on expert sources, which encourages investigative complacency; they become vulnerable to presenting false balance and to covering articles that will be retracted; they sensationalize. As a consequence, the public often receives a mistaken view of science. Many people see science as a series of great new “discoveries” accompanied by a lot of hype; few understand its incremental character, its complexity, its nuance. 

We propose designing a tool that can help science journalists and others to rapidly and effectively characterize the scientific literature for any topic they might cover, as a way to inform and assist news judgment and reporting. Science Surveyor seeks to do this through intuitive, clear interactive graphics that visualize trends in the scientific literature. It aims to show the centrality (or not) of the ideas in the new study, temporal patterns of publishing in the field, and social relationships (the networks of authors and institutions involved in related research).

We see the development of such a tool as having the potential to greatly improve science news coverage, making it more independent, contextualized, and investigative. If successful, the tool will have wider use as well. Scientists and other researchers would use it to improve communication about their fields and practice within their fields. Members of the public would use it to engage with the specialized literature in new ways.

In September 2015 Science Surveyor began its second year of research with an extremely generous Magic Grant from the Helen Gurley Brown Institute for Media Innovation. Science Surveyor was chosen as the Brown Institute’s first Flagship Project. The expanded bi-coastal team aims to develop a methodology and to then test that methodology in interactive visualizations of several case studies from climate science and neuroscience.

Explore this project here.