Anticipating future pathways of Science, Technologies, and Innovations is a complex task in any R&D field and is even more challenging for the complex landscape of promising R&D directions in multiple fields. As a solution, this study analyzes research papers in Scientometrics and Technology mining. It presents an approach and text mining tools for building maps of science of a special kind which is called the Map of Science Squared. Nodes of maps corresponding to R&D fields and locations (e.g., as centers of excellence) are created, weighted, and coupled whenever possible based on processing full texts or abstracts of research papers. The questions to answer with this are as follows: (1) Do Scientometrics and Technology mining cover the full range of topics both in terms of breadth and depth? (2) Do research papers appear “at the right time,” i.e., just or soon after emergence of a topic? (3) Do researchers link R&D fields in non-traditional ways through their studies? (4) What fields are locally bound? (5) What conclusions on future pathways of Science, Technologies, and Innovations can be drawn on the basis of the analysis of the Scientometrics and Technology mining agenda?
Author(s): Irina V. Efimenko , Vladimir F. Khoroshevsky, Ed. C. M. Noyons
Organization(s): Higher School of Economics, Dorodnitsyn Computing Center, Leiden University
Source: Anticipating Future Innovation Pathways Through Large Data Analysis