Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Картографирование науки с помощью VOSviewer× | Систематический обзор литературы× | |
|---|---|---|
| Область | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2010 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор метода≠ | Nees Jan van Eck & Ludo Waltman (Leiden University) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Bibliometric mapping technique | Evidence synthesis methodology |
| Основополагающий источник≠ | van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Другие названия | VOSviewer science mapping, bibliometric science mapping with VOSviewer, VOS-based science mapping, VOSviewer network mapping | SLR, systematic review, evidence synthesis review, structured literature review |
| Связанные≠ | 6 | 5 |
| Сводка≠ | VOSviewer-assisted science mapping uses the VOSviewer software — developed at Leiden University — to construct and visualize bibliometric networks from publication metadata. It applies the VOS (Visualization of Similarities) mapping technique to reveal intellectual structures in a research field: co-authorship networks, citation landscapes, keyword clusters, and thematic frontiers, all rendered as interactive, color-coded network maps that expose how concepts, authors, and journals are relationally positioned within a discipline. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
| ScholarGateНабор данных ↗ |
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