This paper presents a comparative benchmarking of scientometric indicators to characterize the patterns of publication and research performance at the country level, in a specific field (nanoscience and nanotechnology) during the period 2003-2013. The aim is to assess how decisive collaboration may be in attaining a sound level of scientific performance, and how important leadership is for publication. To this end, we used a new methodological approach that contributes to the debate about scientific autonomy or dependency of countries in their scientific performance, and which may serve as an aid in decision-making with regard to research management. The results reveal that in terms of output, USA and China are the main producers; and due to the huge increase in their publications, Iran, India and Australia can be considered emerging countries. The results highlight USA, Ireland and Singapore as the countries with the highest levels of normalized citation impact, scientific excellence and good management of leadership, all of which suggest strong scientific development as well as scientific autonomy. Also worth mentioning is the high visibility and scientific consolidation of China and Australia, despite the meager growth of their output. Moreover, the performance results indicate that in most cases the countries whose pattern of publication is more international tend to have greater visibility. Yet a high degree of leadership does not always translate as a high performance level; the contrary is often true. Due to the limitations of the sample and characteristics of the field, we propose that future studies evaluate the generation of new knowledge in this field and refine the approach presented here, so as to better measure scientific performance.
Chinchilla-Rodríguez, Z., Ocaña-Rosa, K., & Vargas-Quesada, B. (2016). How to Combine Research Guarantor and Collaboration Patterns to Measure Scientific Performance of Countries in Scientific Fields: Nanoscience and Nanotechnology as a Case Study. Frontiers in Research Metrics and Analytics, 1. https://doi.org/10.3389/frma.2016.00002