IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v6y2012i4p505-512.html
   My bibliography  Save this article

Stata commands for importing bibliometric data and processing author address information

Author

Listed:
  • Bornmann, Lutz
  • Ozimek, Adam

Abstract

Given the recent trend in bibliometrics and information science to use increasingly complex statistical methods, it is necessary to have powerful toolboxes to work with data from Web of Science (Thomson Reuters). We developed such a toolbox with four specific commands for the statistical software package Stata. These commands refer to (1) the import of downloads from Web of Science to Stata, (2) the preprocessing of address information from authors of publications in the downloaded set, (3) the geocoding of address information, and (4) the calculation of the minimum and maximum distance between several co-authors of a single paper. An advantage of developing commands for an established and comprehensive statistical software package (like Stata) is that a large number of further commands are available for the analysis of bibliometric data. We will describe some of these useful commands as well.

Suggested Citation

  • Bornmann, Lutz & Ozimek, Adam, 2012. "Stata commands for importing bibliometric data and processing author address information," Journal of Informetrics, Elsevier, vol. 6(4), pages 505-512.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:4:p:505-512
    DOI: 10.1016/j.joi.2012.04.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157712000302
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2012.04.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bornmann, Lutz & Mutz, Rüdiger & Hug, Sven E. & Daniel, Hans-Dieter, 2011. "A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants," Journal of Informetrics, Elsevier, vol. 5(3), pages 346-359.
    2. Loet Leydesdorff & Olle Persson, 2010. "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1622-1634, August.
    3. Bornmann, Lutz & Leydesdorff, Loet & Walch-Solimena, Christiane & Ettl, Christoph, 2011. "Mapping excellence in the geography of science: An approach based on Scopus data," Journal of Informetrics, Elsevier, vol. 5(4), pages 537-546.
    4. Lutz Bornmann & Loet Leydesdorff, 2011. "Which cities produce more excellent papers than can be expected? A new mapping approach, using Google Maps, based on statistical significance testing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1954-1962, October.
    5. Federico Belotti & Domenico Depalo, 2010. "Translation from narrative text to standard codes variables with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 458-481, September.
    6. Ben Jann, 2005. "Tabulation of multiple responses," Stata Journal, StataCorp LP, vol. 5(1), pages 93-122, March.
    7. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    8. Adam Ozimek & Daniel Miles, 2011. "Stata utilities for geocoding and generating travel time and travel distance information," Stata Journal, StataCorp LP, vol. 11(1), pages 106-119, March.
    9. Bornmann, Lutz & Waltman, Ludo, 2011. "The detection of “hot regions” in the geography of science—A visualization approach by using density maps," Journal of Informetrics, Elsevier, vol. 5(4), pages 547-553.
    10. Waltman, Ludo & Tijssen, Robert J.W. & Eck, Nees Jan van, 2011. "Globalisation of science in kilometres," Journal of Informetrics, Elsevier, vol. 5(4), pages 574-582.
    11. J. Scott Long & Jeremy Freese, 2006. "Regression Models for Categorical Dependent Variables using Stata, 2nd Edition," Stata Press books, StataCorp LP, edition 2, number long2, March.
    12. Hennemann, Stefan & Rybski, Diego & Liefner, Ingo, 2012. "The myth of global science collaboration—Collaboration patterns in epistemic communities," Journal of Informetrics, Elsevier, vol. 6(2), pages 217-225.
    13. Gagolewski, Marek, 2011. "Bibliometric impact assessment with R and the CITAN package," Journal of Informetrics, Elsevier, vol. 5(4), pages 678-692.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fernanda Morillo & Ignacio Santabárbara & Javier Aparicio, 2013. "The automatic normalisation challenge: detailed addresses identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 953-966, June.
    2. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.

    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. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    2. Csomós, György, 2018. "Reprint of “A spatial scientometric analysis of the publication output of cities worldwide”," Journal of Informetrics, Elsevier, vol. 12(2), pages 547-566.
    3. Loet Leydesdorff & Lutz Bornmann, 2012. "Mapping (USPTO) patent data using overlays to Google Maps," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1442-1458, July.
    4. Guangyao Zhang & Yuqi Wang & Weixi Xie & Han Du & Chunlin Jiang & Xianwen Wang, 2021. "The open access usage advantage: a temporal and spatial analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6187-6199, July.
    5. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    6. Per Ahlgren & Olle Persson & Robert Tijssen, 2013. "Geographical distance in bibliometric relations within epistemic communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 771-784, May.
    7. Maisonobe, Marion & Eckert, Denis & Grossetti, Michel & Jégou, Laurent & Milard, Béatrice, 2016. "The world network of scientific collaborations between cities: domestic or international dynamics?," Journal of Informetrics, Elsevier, vol. 10(4), pages 1025-1036.
    8. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "A methodology to compute the territorial productivity of scientists: The case of Italy," Journal of Informetrics, Elsevier, vol. 9(4), pages 675-685.
    9. 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.
    10. Bornmann, Lutz & Stefaner, Moritz & de Moya Anegón, Felix & Mutz, Rüdiger, 2014. "What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused in," Journal of Informetrics, Elsevier, vol. 8(3), pages 581-593.
    11. Diekhof, Josefine & Cantner, Uwe, 2017. "Incumbents' responses to innovative entrants: A multi-country dynamic analysis," ZEW Discussion Papers 17-052, ZEW - Leibniz Centre for European Economic Research.
    12. Bornmann, Lutz & Waltman, Ludo, 2011. "The detection of “hot regions” in the geography of science—A visualization approach by using density maps," Journal of Informetrics, Elsevier, vol. 5(4), pages 547-553.
    13. Markus Eberhardt & Christian Helmers & Zhihong Yu, 2011. "Is the Dragon Learning to Fly? An Analysis of the Chinese Patent Explosion," Discussion Papers 11/16, University of Nottingham, GEP.
    14. Bornmann, Lutz & Leydesdorff, Loet & Van den Besselaar, Peter, 2010. "A meta-evaluation of scientific research proposals: Different ways of comparing rejected to awarded applications," Journal of Informetrics, Elsevier, vol. 4(3), pages 211-220.
    15. Gomez-Jauregui, Valentin & Gomez-Jauregui, Cecilia & Manchado, Cristina & Otero, Cesar, 2014. "Information management and improvement of citation indices," International Journal of Information Management, Elsevier, vol. 34(2), pages 257-271.
    16. Bornmann, Lutz, 2014. "Validity of altmetrics data for measuring societal impact: A study using data from Altmetric and F1000Prime," Journal of Informetrics, Elsevier, vol. 8(4), pages 935-950.
    17. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    18. Milica Jovanovic & Veljko Jeremic & Gordana Savic & Milica Bulajic & Milan Martic, 2012. "How does the normalization of data affect the ARWU ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 319-327, November.
    19. Loet Leydesdorff, 2013. "An evaluation of impacts in “Nanoscience & nanotechnology”: steps towards standards for citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 35-55, January.

    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:eee:infome:v:6:y:2012:i:4:p:505-512. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.