title: Tracking the evolution of waste recycling research using overlay maps of science.
abstract: Tracking the evolution of research in waste recycling science (WRS) can be valuable for environmental agencies, as well as for recycling businesses. Maps of science are visual, easily readable representations of the cognitive structure of a branch of science, a particular area of research or the global spectrum of scientific production. They are generally built upon evidence collected from reliable sources of information, such as patent and scientific publication databases. This study uses the methodology developed by Rafols et al. (2010) to make a "double overlay map" of WRS upon a basemap reflecting the cognitive structure of all journal-published science, for the years 2005 and 2010. The analysis has taken into account the cognitive areas where WRS articles are published and the areas from where it takes its intellectual nourishing, paying special attention to the growing trends of the key areas. Interpretation of results lead to the conclusion that extraction of energy from waste will probably be an important research topic in the future, along with developments in general chemistry and chemical engineering oriented to the recovery of valuable materials from waste. Agricultural and material sciences, together with the combined economics, politics and geography field, are areas with which WRS shows a relevant and ever increasing cognitive relationship.
authors.affiliation: Foresight, Technology and Management (FTM) Group, Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Elcano 21, 48030 Bilbao, Spain. gaizka.garechana@ehu.es
authors.forename: Gaizka
authors.initials: G
authors.lastname: Garechana
authors.forename: Rosa
authors.initials: R
authors.lastname: Rio
authors.forename: Ernesto
authors.initials: E
authors.lastname: Cilleruelo
authors.forename: Javier
authors.initials: J
authors.lastname: Gavilanes
mesh_terms: D057225:Data Mining / Q000379:methods*; D059027:Recycling; D012106:Research; D018505:Waste Management / Q000379:methods