Porovnat metody

	Triple Helix Analysis	Mapování vědy
Obor	Science Technology Studies	Bibliometrie
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	2000	2000s
Tvůrce	Henry Etzkowitz & Loet Leydesdorff	Katy Börner, Chaomei Chen, and others
Typ	Innovation-systems framework and bibliometric indicator	Method
Původní zdroj	Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from National Systems and 'Mode 2' to a Triple Helix of university–industry–government relations. Research Policy, 29(2), 109-123.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Další názvy	Triple Helix indicator, University-industry-government analysis, Triple Helix synergy analysis	knowledge mapping, domain mapping, research landscape visualization
Příbuzné	4	5
Shrnutí	Triple Helix analysis is a framework and bibliometric method for studying knowledge-based innovation as the evolving interplay of three institutional spheres—university, industry, and government. Rather than treating these as separate actors that occasionally cooperate, it models innovation as the overlapping, mutually shaping relations among them, and offers an information-theoretic indicator that quantifies how much the three spheres jointly reduce uncertainty in a knowledge economy.	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.