Since my entire professional life is English spoken, my writing here could also somewhat reflect this fact. As a member of the Kavli Institute of Nanoscience here in Delft, I took the opportunity to contribute to the quarterly newsletter with a piece of semi-colloquial writing of my choosing. The entire newsletter can be found here, my column starts here!
Success is 1 percent inspiration, and 99 percent perspiration – almost a Thomas Edison quote, were it not that this American Idol avant la lettre was referring to (his own) geniality rather than success. But it is success most of us are aiming for in science. And everyone – students to professors alike – has experienced first-hand that the better part of being successful is just plain hard work. So far nothing new.
But how to assess success? A recent report  shows the future is not that unpredictable after all. Using the h-index as a measure of success, a large database of predominantly neuroscientists and employing machine-learning techniques, the authors came up with an equation that predicts the future to a reasonable extent. The Hirsch or h-index is – as most readers of this purple periodical undoubtedly know – a scientist’s h number of papers with at least h citations each. As Hirsch reasoned in 2005, the main advantage over other single-number measures is that h combines both the productivity (# of papers) as well as the impact of this productivity (# of citations) into a single number. In 2007 this California-based-physicist-gone-sociologist empirically demonstrated the potential predictive power his index could have. The new-and-improved formula also takes into account other factors such as the total number of papers, the number of distinct journals, the number of active years in research and the number of publications in top-journals.