IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i1d10.1007_s11192-019-03268-9.html
   My bibliography  Save this article

Institution information specification and correlation based on institutional PIDs and IND tool

Author

Listed:
  • Yongwen Huang

    (Agricultural Information Institution of CAAS)

  • Jiao Li

    (Agricultural Information Institution of CAAS)

  • Tan Sun

    (Agricultural Information Institution of CAAS
    Ministry of Agriculture)

  • Guojian Xian

    (Agricultural Information Institution of CAAS
    Ministry of Agriculture)

Abstract

Institution information specification and correlation is a necessity for research evaluation and resource sharing, current attempts are mainly focused on institution name disambiguation (IND) based on institution name, address, author, et al., and lack of a unified and universal indicator. To enhance the correlation of institution information, institutional persistent identifier (PID) is introduced in this study, together with a redesigned tool based on existing techniques of IND. And an institution metadata specification model is built for data preprocess by inheriting some authoritative metadata standards. Further, a visual platform is implemented to demonstrate the correlated institution information and supports institution query. The performance of the proposed approach is evaluated on large datasets of three countries, and the test results demonstrate that the precision and recall are high.

Suggested Citation

  • Yongwen Huang & Jiao Li & Tan Sun & Guojian Xian, 2020. "Institution information specification and correlation based on institutional PIDs and IND tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 381-396, January.
    • Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03268-9
    DOI: 10.1007/s11192-019-03268-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03268-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-019-03268-9?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. Natsuo Onodera & Mariko Iwasawa & Nobuyuki Midorikawa & Fuyuki Yoshikane & Kou Amano & Yutaka Ootani & Tadashi Kodama & Yasuhiko Kiyama & Hiroyuki Tsunoda & Shizuka Yamazaki, 2011. "A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(4), pages 677-690, April.
    2. Carmen Galvez & Félix Moya-Anegón, 2006. "The unification of institutional addresses applying parametrized finite-state graphs (P-FSG)," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 323-345, November.
    3. Yong Jiang & Hai‐Tao Zheng & Xinmin Wang & Binggan Lu & Kaihua Wu, 2011. "Affiliation disambiguation for constructing semantic digital libraries," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(6), pages 1029-1041, June.
    4. Natsuo Onodera & Mariko Iwasawa & Nobuyuki Midorikawa & Fuyuki Yoshikane & Kou Amano & Yutaka Ootani & Tadashi Kodama & Yasuhiko Kiyama & Hiroyuki Tsunoda & Shizuka Yamazaki, 2011. "A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(4), pages 677-690, April.
    5. Pascal Cuxac & Jean-Charles Lamirel & Valerie Bonvallot, 2013. "Efficient supervised and semi-supervised approaches for affiliations disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 47-58, October.
    6. James C. French & Allison L. Powell & Eric Schulman, 2000. "Using clustering strategies for creating authority files," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(8), pages 774-786.
    7. Shuiqing Huang & Bo Yang & Sulan Yan & Ronald Rousseau, 2014. "Institution name disambiguation for research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 823-838, June.
    8. Yong Jiang & Hai-Tao Zheng & Xinmin Wang & Binggan Lu & Kaihua Wu, 2011. "Affiliation disambiguation for constructing semantic digital libraries," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(6), pages 1029-1041, June.
    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. Shuiqing Huang & Bo Yang & Sulan Yan & Ronald Rousseau, 2014. "Institution name disambiguation for research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 823-838, June.
    2. Andrea Ancona & Roy Cerqueti & Gianluca Vagnani, 2023. "A novel methodology to disambiguate organization names: an application to EU Framework Programmes data," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4447-4474, August.
    3. Maxim Kotsemir & Sergey Shashnov, 2017. "Measuring, analysis and visualization of research capacity of university at the level of departments and staff members," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1659-1689, September.
    4. Pascal Cuxac & Jean-Charles Lamirel & Valerie Bonvallot, 2013. "Efficient supervised and semi-supervised approaches for affiliations disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 47-58, October.
    5. Carmen Galvez & Félix Moya-Anegón, 2007. "Standardizing formats of corporate source data," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 3-26, January.
    6. Jan Schulz, 2016. "Using Monte Carlo simulations to assess the impact of author name disambiguation quality on different bibliometric analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1283-1298, June.
    7. Rehs, Andreas, 2021. "A supervised machine learning approach to author disambiguation in the Web of Science," Journal of Informetrics, Elsevier, vol. 15(3).
    8. Jinseok Kim & Jenna Kim, 2020. "Effect of forename string on author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 839-855, July.
    9. 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.
    10. Jiang Wu & Xiu-Hao Ding, 2013. "Author name disambiguation in scientific collaboration and mobility cases," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 683-697, September.
    11. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
    12. Fernanda Morillo & Belén Álvarez-Bornstein, 2018. "How to automatically identify major research sponsors selecting keywords from the WoS Funding Agency field," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1755-1770, December.
    13. Thomas Gurney & Edwin Horlings & Peter van den Besselaar, 2012. "Author disambiguation using multi-aspect similarity indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 435-449, May.
    14. Jian Wang & Kaspars Berzins & Diana Hicks & Julia Melkers & Fang Xiao & Diogo Pinheiro, 2012. "A boosted-trees method for name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 391-411, November.
    15. Fernanda Morillo & Rodrigo Costas & María Bordons, 2015. "How is credit given to networking centres in their publications? A case study of the Spanish CIBER research structures," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 923-938, June.
    16. repec:gig:joupla:v:3:y:2011:i:2:p:141-172 is not listed on IDEAS
    17. Deyun Yin & Kazuyuki Motohashi & Jianwei Dang, 2020. "Large-scale name disambiguation of Chinese patent inventors (1985–2016)," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 765-790, February.
    18. Ciriaco Andrea D’Angelo & Nees Jan Eck, 2020. "Collecting large-scale publication data at the level of individual researchers: a practical proposal for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 883-907, May.
    19. Omar Hernando Avila-Poveda, 2014. "Technical report: the trend of author compound names and its implications for authorship identity identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 833-846, October.
    20. Zehra Taşkın & Umut Al, 2014. "Standardization problem of author affiliations in citation indexes," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 347-368, January.
    21. 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.

    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:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03268-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.