The Manchester Institute of Innovation Research in conjunction with the Innovation Co-Lab, the VP Institute and Search Technology is sponsoring the 2018 Manchester Forum on Data Analytics, Tech Mining and Innovation Policy. The Forum brings together active users of data science, tech mining, modelling, and visualization methods who are applying these methods to science and innovation policy, technology transfer, technology intelligence, and technology and innovation management. This year's event builds on the success of earlier Manchester Forums on Data Analytics and Innovation in 2013 and 2015. As part of the Forum, a half-day session of hands-on VantagePoint training and updates on new VantagePoint features will be offered. This will take place on Tuesday 4 September from 2pm – 5.30pm. For complete information on the training session, click here.
Indicators of technological emergence promise valuable intelligence. We present an implemented algorithm to calculate emergence scores (EScores) for topical terms from abstract record sets. We offer a family of emergence indicators. Primary emergence indicators identify "frontier" terms based on their EScores. We then tally organizations, countries, or authors especially active in publishing (or patenting) on high EScore topics in a target R&D domain. We can score research fields on relative degree of emergence. This paper illustrates EScoring for Nano-Enabled Drug Delivery, Non-Linear Programming, Dye Sensitized Solar Cells, and Big Data. The paper is part of a special TFSC issue on tech emergence.
Porter, A.L., Garner, J., Carley, S.F., and Newman, N.C. (2018), Emergence scoring to identify frontier R&D topics and key players, Technological Forecasting and Social Change, https://doi.org/10.1016/j.techfore.2018.04.016
Luciano Kay, Alan Porter, Jan Youtie, Nils Newman, and Ismael Rafols' paper titled "Visual analysis of patent data through global maps and overlays" appears in the recently released book Current Challenges in Patent Information Retrieval Springer (2017).