Assessing the bibliometric productivity of forest scientists in Italy

Since 2010, the Italian Ministry of University and Research issued new evaluation protocols to select candidates for University professorships and assess the bibliometric productivity of Universities and Research Institutes based on bibliometric indicators, i.e. scientific paper and citation numbers and the h-index. Under this framework, the objective of this study was to quantify the bibliometric productivity of the Italian forest research community during the 2002-2012 period. We examined the following productivity parameters: (i) the bibliometric productivity under the Forestry subject category at the global level; (ii) compared the aggregated bibliometric productivity of Italian forest scientists with scientists from other countries; (iii) analyzed publication and citation temporal trends of Italian forest scientists and their international collaborations; and (iv) characterized productivity distribution among Italian forest scientists at different career levels. Results indicated the following: (i) the UK is the most efficient country based on the ratio between Gross Domestic Spending (GDS) on Research and Development (R&D) and bibliometric productivity under the Forestry subject category, followed by Italy; (ii) Italian forest scientist productivity exhibited a significant positive time trend, but was characterized by high inequality across authors; (iii) one-half of the Italian forest scientist publications were written in collaboration with foreign scientists; (iv) a strong relationship exists between bibliometric indicators calculated by WOS and SCOPUS, suggesting these two databases have the same potential to evaluate the forestry research community; and (v) self-citations did not significantly affect the rank of Italian forest scientists.

Abstract licence: CC BY

55 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.