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	Analiza scientometryczna w podziale na okresy czasowe	Science Mapping
Dziedzina	Naukometria	Bibliometria
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1980s–1990s	2000s
Twórca	Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward	Katy Börner, Chaomei Chen, and others
Typ	Quantitative longitudinal analysis	Method
Źródło pierwotne	Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Inne nazwy	temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis	knowledge mapping, domain mapping, research landscape visualization
Pokrewne	6	5
Podsumowanie	Time-sliced scientometric analysis divides a bibliographic corpus into discrete temporal windows — commonly five- or ten-year periods — and applies standard scientometric indicators (publication counts, citation rates, h-index, collaboration networks, keyword co-occurrence) within each slice. By comparing results across slices, researchers can reconstruct how a scientific field has grown, shifted focus, formed new collaborations, or declined in influence over time. The approach combines the rigor of quantitative scientometrics with an explicit longitudinal dimension.	Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning.