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Biotechnology in context: A database‐filtering approach to identifying core and productive non‐core journals supporting multidisciplinary R & D

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  • Katherine W. McCain

Abstract

Eighty‐nine journals were identified as potentially important journals supporting biotechnology R&D through the analysis of journal citation networks (1991 Journal Citation Reports). Twelve research areas emerged: one set of linked intercitation clusters representing the central areas of concern—biotechnology, microbiology, molecular genetics, food science and technology, and plant science. Organic chemistry and natural products research comprised a linked pair, while the remainder, horticulture, pharmaceutical science, chemical engineering, biosensors, and water research remained single clusters. Mapping and clustering of cocitation data (1988–1992 SCISEARCH) displayed a similar structure, with the clusters arranged along a basic (natural science)—applied research (engineering) continuum. A subject indexing profile analysis (Biotechnology Abstracts, 1990–1992) showed that journals in pharmaceutical science, organic chemistry, and natural products rarely if ever published biotechnology‐relevant research. In a productivity analysis, the two top categories (70% coverage—12 titles; 30%–69% coverage—14 titles) included 10 journals not classed as biotechnology by Journal Citation Reports. One of these, Plant Cell Reports (88% coverage), has not been listed as a biotechnology journal in any previous core lists. This database filtering approach, combining citation, indexing, and productivity analyses, is an effective tool for identifying important non‐core journals supporting multidisciplinary R&D. © 1995 John Wiley & Sons, Inc.

Suggested Citation

  • Katherine W. McCain, 1995. "Biotechnology in context: A database‐filtering approach to identifying core and productive non‐core journals supporting multidisciplinary R & D," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 46(4), pages 306-317, May.
    • Handle: RePEc:bla:jamest:v:46:y:1995:i:4:p:306-317
    DOI: 10.1002/(SICI)1097-4571(199505)46:43.0.CO;2-C
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    Cited by:

    1. Senator Jeong & Hong-Gee Kim, 2010. "Intellectual structure of biomedical informatics reflected in scholarly events," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(2), pages 541-551, November.
    2. Rafael Aleixandre & Juan Carlos Valderrama & José María Desantes & Antonio J. Torregrosa, 2004. "Identification of information sources and citation patterns in the field of reciprocating internal combustion engines," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 321-336, March.
    3. Gilbert Shama & Klaus Hellgardt & Charles Oppenheim, 2000. "Citation Ootprint Analysis Part I: UK and US Chemical Engineering Academics," Scientometrics, Springer;Akadémiai Kiadó, vol. 49(2), pages 289-305, October.
    4. Yoshiyuki Takeda & Shiho Mae & Yuya Kajikawa & Katsumori Matsushima, 2009. "Nanobiotechnology as an emerging research domain from nanotechnology: A bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 23-38, July.
    5. Leo Egghe & Ronald Rousseau, 2002. "A proposal to define a core of a scientific subject: A definition using concentration and fuzzy sets," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(1), pages 51-62, April.
    6. Thabang Lazarus Bambo & Anastassios Pouris, 2020. "Bibliometric analysis of bioeconomy research in South Africa," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 29-51, October.

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