UM Data Science Research Seminar
The UM Data Science Research Seminar Series are monthly sessions organised by the Institute of Data Science in collaboration with different departments across UM with the aim to bring together data scientists from Maastricht University to discuss breakthroughs and research topics related to Data Science.
This first session of 2019 is organised in collaboration with United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT) on March 21, 2019 from 12:00 - 1:00pm.
Event is free and open to everyone. Lunch will be provided. Please register by March 19, 2019.
12.00 - 12.30
Talk by Dr. Önder Nomaler
Title: Identifying technological progress trajectories in patent citation networks
Abstract: The talk will commence with a brief introduction to databases of patent meta-data in the particular context of data sciences and big data, and the various ways in which scholars of ‘innovation sciences’ have been making sense of these huge bibliometric databases in order to address various research questions on technological progress. One particular interesting aspect of patents is that, similar to scientific articles, they cite each other. Among scholars of innovation sciences, there is a general agreement that patent citations can be used as an indicator (i.e., proxy) of knowledge flows between inventions and accordingly, their inventors. These citation links between individual patent pairs form enormous (directed and acyclical) citation network graphs when large collections of selected patents (or all patents) are considered as the landscape of technical inventions. We have (at UNU-MERIT) developed algorithms that are reminiscent of Google’s PageRank, which can identify the most important patents and the citation trajectories formed by these important patents. We use these algorithms to analyse technical progress across geographical entities (i.e., countries, regions) and or different technological areas that must have benefitted from mutual synergies (i.e., recombinant innovation).
12.30 - 13.00
Talk by Dr. Lili Wang
Title: Knowledge flows from public science to industrial technologies
Abstract: Scientific research has been acknowledged as an important knowledge resource for developing technologies. Studying science-technology linkages is crucial to help understand the mechanisms of innovation. Using nano technology as a case study, this paper investigates what types of scientific research can help improve the quality of technologies. This study uses backward and forward citation analysis, extracted from the Derwent World Patents Index (DWPI). Non-patent citations (NPCs) from each patent are further connected with records indexed in Web of Science, and the forward citations for the cited articles are collected. On the one hand, our results confirm that there is an important contribution from science to technology. High-quality academic research has significantly contributed to the development of high-quality patents. On the other hand, this study also reveals the heterogeneous pattern of patents citing scientific publications, depending on the organizational type, country, and knowledge origin. Compared to those in the U.S., patents developed by Chinese inventors tend to reply on more recent science but with a narrower scientific scope.
About the speakers
Önder Nomaler is a researcher at UNU-MERIT. His fields of expertise are in: Evolutionary Economics, Computational Economics and Microeconomics.
Lili Wang obtained her PhD degree from Eindhoven University of Technology and currently works at UNU-MERIT. Her research interests cover two main strands: a) S&T economics, innovation systems and policy, emerging technologies,publications and patents, scientometrics, and b) economic growth and structural change in developing countries. She has conducted various research projects since 2008 and her work has been widely published in peer-reviewed journals, such as Research Policy, Proceedings of the National Academy of Sciences of the United States of America (PNAS), Technological Forecasting & Social Change, Regional Studies, Journal of Informetrics, Industrial and Corporate Change, Oxford Development Studies, Scientometrics, China Economic Review, Research Evaluation, Journal of Technology Management in China, and International Journal of Technology Management.