IDEAS home Printed from https://ideas.repec.org/p/sru/ssewps/2014-14.html
   My bibliography  Save this paper

Matching MEDLINE/PubMed Data with Web of Science (WOS): A Routine in R language

Author

Listed:
  • Daniele Rotolo

    (SPRU, University of Sussex, UK)

  • Loet Leydesdorff

    (Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Netherlands)

Abstract

We present a novel routine, namely medlineR, based on R language, that enables the user to match data from MEDLINE/PubMed with records indexed in the ISI Web of Science (WoS) database. The matching allows exploiting the rich and controlled vocabulary of Medical Subject Headings (MeSH) of MEDLINE/PubMed with additional fields of WoS. The integration provides data (e.g. citation data, list of cited reference, list of the addresses of authors’ host organisations, WoS subject categories) to perform a variety of scientometric analyses. This brief communication describes medlineR, the methodology on which it relies, and the steps the user should follow to perform the matching across the two databases. In order to specify the differences from Leydesdorff and Opthof (2013), we conclude the brief communication by testing the routine on the case of the "Burgada Syndrome".

Suggested Citation

  • Daniele Rotolo & Loet Leydesdorff, 2014. "Matching MEDLINE/PubMed Data with Web of Science (WOS): A Routine in R language," SPRU Working Paper Series 2014-14, SPRU - Science Policy Research Unit, University of Sussex Business School.
    • Handle: RePEc:sru:ssewps:2014-14
    as

    Download full text from publisher

    File URL: http://www.sussex.ac.uk/spru/documents/1412-rotolo-leydesdorff-medliner-wos-wp.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Johannes Stegmann & Guenter Grohmann, 2003. "Hypothesis generation guided by co-word clustering," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(1), pages 111-135, January.
    2. Hanning Guo & Scott Weingart & Katy Börner, 2011. "Mixed-indicators model for identifying emerging research areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 421-435, October.
    3. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    4. Ryosuke L. Ohniwa & Aiko Hibino & Kunio Takeyasu, 2010. "Trends in research foci in life science fields over the last 30 years monitored by emerging topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 111-127, October.
    5. Jonas Lundberg & Anette Fransson & Mats Brommels & John Sk?r & Inger Lundkvist, 2006. "Is it better or just the same? Article identification strategies impact bibliometric assessments," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 183-197, January.
    6. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Vetle I. Torvik & Marc Weeber & Don R. Swanson & Neil R. Smalheiser, 2005. "A probabilistic similarity metric for Medline records: A model for author name disambiguation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(2), pages 140-158, January.
    8. Allan P. O. Williams, 2006. "Impact of Strategies," Palgrave Macmillan Books, in: The Rise of Cass Business School, chapter 13, pages 167-181, Palgrave Macmillan.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    2. Loet Leydesdorff & Jordan A. Comins & Aaron A. Sorensen & Lutz Bornmann & Iina Hellsten, 2016. "Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2077-2091, December.
    3. Ryosuke L. Ohniwa & Kunio Takeyasu & Aiko Hibino, 2022. "Researcher dynamics in the generation of emerging topics in life sciences and medicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 871-884, February.
    4. Ryosuke L. Ohniwa & Aiko Hibino, 2019. "Generating process of emerging topics in the life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1549-1561, December.
    5. Gaetan de Rassenfosse & Kyle Higham & Orion Penner, 2022. "Scientific rewards for biomedical specialization are large and persistent," Working Papers 19, Chair of Science, Technology, and Innovation Policy.
    6. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    7. Lundberg, Jonas, 2007. "Lifting the crown—citation z-score," Journal of Informetrics, Elsevier, vol. 1(2), pages 145-154.
    8. Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    9. Rocío Guardiola-Wanden-Berghe & Javier Sanz-Valero & Carmina Wanden-Berghe, 2013. "Medical subject headings versus American Psychological Association Index Terms: indexing eating disorders," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 305-311, January.
    10. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    11. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
    12. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    13. Lv, Yanhua & Ding, Ying & Song, Min & Duan, Zhiguang, 2018. "Topology-driven trend analysis for drug discovery," Journal of Informetrics, Elsevier, vol. 12(3), pages 893-905.
    14. Loet Leydesdorff, 2015. "Can technology life-cycles be indicated by diversity in patent classifications? The crucial role of variety," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1441-1451, December.
    15. Loet Leydesdorff & Ping Zhou & Lutz Bornmann, 2013. "How can journal impact factors be normalized across fields of science? An assessment in terms of percentile ranks and fractional counts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 96-107, January.
    16. Sanderson, Susan Walsh & Simons, Kenneth L., 2014. "Light emitting diodes and the lighting revolution: The emergence of a solid-state lighting industry," Research Policy, Elsevier, vol. 43(10), pages 1730-1746.
    17. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    18. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    19. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sru:ssewps:2014-14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: University of Sussex Business School Communications Team (email available below). General contact details of provider: https://edirc.repec.org/data/spessuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.