title: Density-equalizing mapping and scientometric benchmarking in Industrial Health.
abstract: Bibliometric techniques have been introduced to the field of industrial health in the past two decades. Since then, several studies have assessed progression of science in this area using quantitative measures and qualitative measures such as impact factor or H-indices. Since novel procedures such as density-equalizing mapping have not been used so far, the present study combined classical bibliometric tools with novel scientometric and visualizing techniques. All "INDUSTRIAL HEALTH" entries listed in the ISI database since 1987 were screened and analyzed. Using bibliometric approaches, a continuous increase in qualitative markers such as collaboration numbers or citations were found while quantity markers such as author numbers or publication numbers remained relatively constant. The combination with density equalizing mapping revealed a distinct global pattern of research productivity and citation activity with Japanese institutions at the leading position. Radar chart techniques were used to visualize bi- and multilateral research cooperations and institutional cooperations. In summary, the present study supplies a first scientometric-bibliometric approach that visualizes research activity in "INDUSTRIAL HEALTH" over the past decades.
authors.affiliation: Department of Information Science, Charité-Universitätsmedizin Berlin, Free University Berlin, Berlin, Germany. cristian.scutaru@charite.de
authors.forename: Cristian
authors.initials: C
authors.lastname: Scutaru
authors.forename: David
authors.initials: D
authors.lastname: Quarcoo
authors.forename: Masaya
authors.initials: M
authors.lastname: Takemura
authors.forename: Tobias
authors.initials: T
authors.lastname: Welte
authors.forename: Tanja C
authors.initials: TC
authors.lastname: Fischer
authors.forename: Beatrix
authors.initials: B
authors.lastname: Groneberg-Kloft
mesh_terms: D019985:Benchmarking / Q000379:methods*; D015706:Bibliometrics; D006801:Humans; D016272:Occupational Health / Q000706:statistics & numerical data*; D010506:Periodicals as Topic / Q000706:statistics & numerical data; D012106:Research / Q000706:statistics & numerical data*; D012107:Research Design