Knowledge is power, but the data that creates that knowledge can be even more powerful.
It might even be able to predict the future if you know what you’re looking for.
Santo Fortunato, a professor at the School of Informatics, Computing, and Engineering, and the director of the Center for Complex Networks and Systems Research (CNetS) at SICE, is the lead author of a review paper in the latest edition of Science magazine that showcases the power of the science of science (SciSci).
Fortunato, who worked with a host of researchers on the piece, including four other current or former SICE faculty members, says SciSci can be used to identify the evolution of science through the study of the growing wealth of data that exists. The identification of the fundamental drivers of science and the development of predictive models to capture the evolution of science can help design policies that will create enhanced career paths for scientists and better performance evaluations for organizations that host research. SciSci can also aid the discovery of effective funding opportunities for novel research and spotlight emerging areas of promising research.
Other faculty members from SICE who worked on the paper include Distinguished Professor of Engineering & Information Science Katy Börner, Associate Professor of Informatics Staša Milojevic, and Associate Professor Filippo Radicchi.
Fortunato has been focusing on SciSci for the past decade, and the acquisition of the Web of Science dataset—which was recently acquired by the Indiana University Network Science Institute and features more than 61 million items and more than 1.1 billion articles/reference links dating back to 1900—will enable IU scholars to make significant contributions to SciSci.
“I want people to understand the possibilities that can come from working on this area,” Fortunato said. “There are now many more datasets, some of them even bigger than what has previously been available. We have the tools and the ideas and the methods to conduct our studies, but we couldn’t use them to their fullest potential because we didn’t have a chance to play with the data. Now, this excuse isn’t there anymore.”
The Science article is intended to showcase the promising potential of studying the insights that can be gleaned from domain-specific studies and extrapolating how the patterns that emerge over time can be applied to other fields.
“With large data sets, we’re looking for things like the evolution of fields,” Fortunato said. “We want to see if we can predict when a field will emerge or when an existing field will somehow reach a peak and die out. Predictions are very risky, and if you start to pull money from a field that seems to be dying and become ambitious in putting money into a field that is just starting, that could have serious implications if the new fields don’t work out. There are now very big, important, public data that can be used to study this. We hope that more people will become aware of this kind of study, and we hope more people will start to contribute.”
For more information about the article, visit the Science website.