General properties of the evolution of research fields: a scientometric study of human microbiome, evolutionary robotics and astrobiology

Mario Coccia

Scientometrics, 2018, vol. 117, issue 2, No 26, 1265-1283

Abstract: Abstract How do research fields evolve? This study confronts this question here by developing an inductive analysis based on emerging research fields of human microbiome, evolutionary robotics and astrobiology (also called exobiology). Data analysis considers papers associated with subject areas of authors from starting years to 2017 per each research field under study. Findings suggest some empirical properties of the evolution of research fields: the first property states that the evolution of a research field is driven by few disciplines (3–5) that generate more than 80% of documents (concentration of scientific production); the second property states that the evolution of research fields is path-dependent of critical disciplines: they can be parent disciplines that have originated the research field or new disciplines emerged during the evolution of science; the third property states that the evolution of research fields can be also due to a new discipline originated from a process of specialization within applied or basic sciences and/or convergence between disciplines. Finally, the fourth property states that the evolution of specific research fields can be due to both applied and basic sciences. These results here can explain and generalize some characteristics of the evolution of scientific fields in the dynamics of science. Overall, then, this study begins the process of clarifying and generalizing, as far as possible, the general properties of the evolution of research fields to lay a foundation for the development of sophisticated theories of the evolution of science.

Keywords: Research fields; Evolution of science; Dynamics of science; Convergence in science; Applied sciences; Basic sciences; Human microbiome; Evolutionary robotics; Astrobiology; Exobiology (search for similar items in EconPapers)
JEL-codes: A19 C00 I23 L30 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-018-2902-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:117:y:2018:i:2:d:10.1007_s11192-018-2902-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-018-2902-8

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().