With the rise of "Big Data", the bottleneck in predictive science is not finding relevant data, but how to interpret them. Patents are a key indicator of human technological progress. Studying patent databases can reveal patterns in technological development that can be used in decision-making, for example in resource allocation.

Patents are linked by references, so they also create links between the technology categories to which the patents belong. This network can be understood as a kind of intellectual ecology, which can be used for mathematical analyses similar to numerical ecology. In their recent paper, our colleagues used the non-metric Bray-Curtis dissimilarity to describe the internal dynamics of the patent network.

The article was co-authored with colleagues at the University of Debrecen, published in the Journal of Big Data and is available at this link.