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Informetric studies using databases: Opportunities and challenges

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  • William W. Hood

    (The University of New South Wales)

  • Concepción S. Wilson

    (The University of New South Wales)

Abstract

Since their arrival in the 1960s, electronic databases have been an invaluable tool for informetricians. Databases and their delivery mechanism have provided both the source of raw data, as well as the analytical tools for many informetric studies. In particular, the citation databases produced by the Institute for Scientific Information have been the key source of data for a whole range of citation-based research. However, there are also many problems and challenges associated with the use of online databases. Most of the problems arise because databases are designed primarily for information retrieval purposes, and informetric studies represent only a secondary use of the systems. The sorts of problems encountered by informetricians include: errors or inconsistency in the data itself; problems with the coverage, overlap and changeability of the databases; as well as problems and limitations in the tools provided by the database hosts such as DIALOG. For some informetric studies, the only viable solution to these problems is to download the data and perform offline correction and data analysis.

Suggested Citation

  • William W. Hood & Concepción S. Wilson, 2003. "Informetric studies using databases: Opportunities and challenges," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 587-608, November.
  • Handle: RePEc:spr:scient:v:58:y:2003:i:3:d:10.1023_b:scie.0000006882.47115.c6
    DOI: 10.1023/B:SCIE.0000006882.47115.c6
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    References listed on IDEAS

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    12. W. W. Hood & Concepción S. Wilson, 1999. "The distribution of bibliographic records in databases using different counting methods for duplicate records," Scientometrics, Springer;Akadémiai Kiadó, vol. 46(3), pages 473-486, November.
    13. William W. Hood & Concepción S. Wilson, 2002. "Analysis of the fuzzy set literature using phrases," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(1), pages 103-118, April.
    14. Raúl G. Torricella-Morales & Guido Van Hooydonk & Juan Antonio Araujo-Ruiz, 2000. "Citation Analysis of Cuban Research. Part 1. A Case Study: The Cuban Journal of Agricultural Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 413-426, February.
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    4. Zehra Taşkın & Umut Al, 2014. "Standardization problem of author affiliations in citation indexes," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 347-368, January.
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    6. Mohamed Rafik Noor Mohamed Qureshi, 2022. "A Bibliometric Analysis of Third-Party Logistics Services Providers (3PLSP) Selection for Supply Chain Strategic Advantage," Sustainability, MDPI, vol. 14(19), pages 1-25, September.
    7. José Álvarez-García & Amador Durán-Sánchez & María de la Cruz Del Río-Rama & Diego Fernando García-Vélez, 2018. "Active Ageing: Mapping of Scientific Coverage," IJERPH, MDPI, vol. 15(12), pages 1-21, December.
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    9. Camil Demetrescu & Andrea Ribichini & Marco Schaerf, 2018. "Accuracy of author names in bibliographic data sources: an Italian case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1777-1791, December.
    10. Fernanda Morillo & Javier Aparicio & Borja González-Albo & Luz Moreno, 2013. "Towards the automation of address identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 207-224, January.
    11. Guangyuan Hu & Stephen Carley & Li Tang, 2012. "Visualizing nanotechnology research in Canada: evidence from publication activities, 1990–2009," The Journal of Technology Transfer, Springer, vol. 37(4), pages 550-562, August.
    12. Mallig, Nicolai, 2010. "A relational database for bibliometric analysis," Journal of Informetrics, Elsevier, vol. 4(4), pages 564-580.
    13. Li Tang & Philip Shapira, 2011. "Regional development and interregional collaboration in the growth of nanotechnology research in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 299-315, February.
    14. Mallig, Nicolai, 2010. "A relational database for bibliometric analysis," Discussion Papers "Innovation Systems and Policy Analysis" 22, Fraunhofer Institute for Systems and Innovation Research (ISI).
    15. Sjoerd Hardeman, 2013. "Organization level research in scientometrics: a plea for an explicit pragmatic approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1175-1194, March.
    16. Ying Huang & Donghua Zhu & Qi Lv & Alan L. Porter & Douglas K. R. Robinson & Xuefeng Wang, 2017. "Early insights on the Emerging Sources Citation Index (ESCI): an overlay map-based bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 2041-2057, June.
    17. He, Zi-Lin & Geng, Xue-Song & Campbell-Hunt, Colin, 2009. "Research collaboration and research output: A longitudinal study of 65 biomedical scientists in a New Zealand university," Research Policy, Elsevier, vol. 38(2), pages 306-317, March.
    18. Yu, Hairong & Davis, Mari & Wilson, Concepción S. & Cole, Fletcher T.H., 2008. "Object-relational data modelling for informetric databases," Journal of Informetrics, Elsevier, vol. 2(3), pages 240-251.
    19. Martha Flores‐Sosa & Ezequiel Avilés‐Ochoa & José M. Merigó, 2022. "Exchange rate and volatility: A bibliometric review," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1419-1442, January.

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