QUT In4M Rankings
Using the QUT In4M Metric to rank global research institutions
We assessed 200 leading global research institutions for their influence on industry and innovation using a new methodology that relies on knowledge of scholarly work cited in patent literature and the value of the patents as perceived by the applicants.
We correlated the 1980-2015 resolved scholarly work from each institution1, with scholarly work cited in the patent literature that had been extracted and resolved to persistent identifiers in collaboration with NIH NCBI and Crossref. We used this to develop an open metric, the International Innovation and Industry Influence Mapping (In4M) metric. The metric relies on citation intensity2 normalized by each of the ten research discipline groups for an institution. On these pages, we provide the global analyses and offer dossier views for each of the 200 institutions. In a dossier, you can explore the influence an institution’s scholarly work has on which enterprises, the research disciplines that most influence industry and innovation, and the level of influence an institution’s scholarship has on certain technology sectors. The full details of the methodology are in the recently accepted article for publication in Nature Biotechnology “Mapping the global influence of published research on industry and innovation” by Osmat A Jefferson (QUT, Cambia), Adam Jaffe (QUT, Motu Research), Doug Ashton, (Cambia), Ben Warren (Cambia), Deniz Koellhofer (Cambia), Uwe Dulleck, (QUT), Aaron Ballagh (ANU), John Moe, Michael DiCuccio (NIH), Karl Ward, Geoff Bilder (Crossref), Kevin Dolby (Medical Research Council), and Richard Jefferson (QUT, Cambia).
1. With permission from Clarivate Analytics
2. The citation intensity measure reflects the number of 3rd party citing patents weighted by the size of patent family per unit of scholarly output. Citation intensity of an institution can be normalized by research disciplines or fields of Use to enable standardized comparisons or Lens rankings across various institutions. In this first release, we show Lens rankings based on normalization by research disciplines
Summary Stats of the Global Dataset
747,323 Number of citing patent families
1,203,085 Number of citing publication keys
1,181,708 Number of 3rd-party publication keys
5,174,866 Number of 3rd-party publication keys (expanded by family)
1,226,953 Cited Scholarly work