Efficient Graph Processing
D. Spinellis (Athens University of Economics and Business, TU Delft - Software Engineering)
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Abstract
Science typically advances in small incremental steps, but in some rare instances it leaps forward. One discovery or invention can change how we see the world around us. Would it not be neat to be able to accurately pinpoint those moments of time in an objective way and thereby investigate science and technology’s progress? In 2016, Russel Funk of the University of Minnesota’s Carlson School of Management and Jason Owen-Smith from the University of Michigan published a measure for exactly this purpose.1 Their so-called consolidation-disruption (CD) index quantifies the extent to which published findings affect the subsequent use of the knowledge on which those findings relied. Worryingly, a widely cited subsequent study applied this measure on patents and scientific publications, finding a slowdown in disruptive progress.2 Thickening the plot, a later preprint attributed the finding to dataset artefacts.3 These studies prompt the need for an efficient way to calculate the CD index on large amounts of openly available data. [...]