IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v58y2003i3d10.1023_bscie.0000006883.28709.d2.html
   My bibliography  Save this article

OLAP and bibliographic databases

Author

Listed:
  • Emil Hudomalj

    (Faculty of Medicine University of Ljubljana)

  • Gaj Vidmar

    (Faculty of Medicine University of Ljubljana)

Abstract

The application of online analytical processing (OLAP) technology to bibliographic databases is addressed. We show that OLAP tools can be used by librarians for periodic and ad hoc reporting, quality assurance, and data integrity checking, as well as by research policy makers for monitoring the development of science and evaluating or comparing disciplines, fields or research groups. It is argued that traditional relational database management systems, used mainly for day-to-day data storage and transactional processing, are not appropriate for performing such tasks on a regular basis. For the purpose, a fully functional OLAP solution has been implemented on Biomedicina Slovenica, a Slovenian national bibliographic database. We demonstrate the system's usefulness by extracting data for studying a selection of scientometric issues: changes in the number of published papers, citations and pure citations over time, their dependence on the number of co-operating authors and on the number of organisations the authors are affiliated to, and time-patterns of citations. Hardware, software and feasibility considerations are discussed and the phases of the process of developing bibliographic OLAP applications are outlined.

Suggested Citation

  • Emil Hudomalj & Gaj Vidmar, 2003. "OLAP and bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 609-622, November.
  • Handle: RePEc:spr:scient:v:58:y:2003:i:3:d:10.1023_b:scie.0000006883.28709.d2
    DOI: 10.1023/B:SCIE.0000006883.28709.d2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1023/B:SCIE.0000006883.28709.d2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1023/B:SCIE.0000006883.28709.d2?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. Quentin L. Burrell, 2002. "Modelling citation age data: Simple graphical methods from reliability theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 273-285, August.
    2. Leo Egghe & Ronald Rousseau, 2000. "Aging, obsolescence, impact, growth, and utilization: Definitions and relations," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(11), pages 1004-1017.
    3. Michael D. Gordon & Robert K. Lindsay, 1996. "Toward discovery support systems: A replication, re‐examination, and extension of Swanson's work on literature‐based discovery of a connection between Raynaud's and fish oil," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(2), pages 116-128, February.
    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. Alfio Ferrara & Silvia Salini, 2012. "Ten challenges in modeling bibliographic data for bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 765-785, December.
    2. Sabine Loudcher & Wararat Jakawat & Edmundo Pavel Soriano Morales & Cécile Favre, 2015. "Combining OLAP and information networks for bibliographic data analysis: a survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 471-487, May.
    3. 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.

    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. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    2. Wolfgang Glänzel, 2004. "Towards a model for diachronous and synchronous citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 511-522, August.
    3. Hamid Bouabid & Vincent Larivière, 2013. "The lengthening of papers’ life expectancy: a diachronous analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 695-717, December.
    4. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    5. Sarabia, José María, 2008. "A general definition of the Leimkuhler curve," Journal of Informetrics, Elsevier, vol. 2(2), pages 156-163.
    6. Giovanni Abramo & Ciriaco Andrea D’Angelo & Tindaro Cicero, 2012. "What is the appropriate length of the publication period over which to assess research performance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 1005-1017, December.
    7. Weimao Ke, 2013. "A fitness model for scholarly impact analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 981-998, March.
    8. Shesen Guo & Ganzhou Zhang, 2017. "Analyzing concept complexity, knowledge ageing and diffusion pattern of Mooc," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 413-430, July.
    9. Wildgaard, Lorna, 2016. "A critical cluster analysis of 44 indicators of author-level performance," Journal of Informetrics, Elsevier, vol. 10(4), pages 1055-1078.
    10. Alan L. Porter & Alisa Kongthon & Jye-Chyi (JC) Lu, 2002. "Research profiling: Improving the literature review," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 351-370, March.
    11. Xianwen Wang & Zhichao Fang & Xiaoling Sun, 2016. "Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 917-926, November.
    12. Gamal Crichton & Simon Baker & Yufan Guo & Anna Korhonen, 2020. "Neural networks for open and closed Literature-based Discovery," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-16, May.
    13. Henneken, Edwin A. & Kurtz, Michael J. & Accomazzi, Alberto & Grant, Carolyn S. & Thompson, Donna & Bohlen, Elizabeth & Murray, Stephen S., 2009. "Use of astronomical literature—A report on usage patterns," Journal of Informetrics, Elsevier, vol. 3(1), pages 1-8.
    14. Andrej Kastrin & Dimitar Hristovski, 2021. "Scientometric analysis and knowledge mapping of literature-based discovery (1986–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1415-1451, February.
    15. Balakrishnan, N. & Sarabia, José María & Kolev, Nikolai, 2010. "A simple relation between the Leimkuhler curve and the mean residual life," Journal of Informetrics, Elsevier, vol. 4(4), pages 602-607.
    16. Vicente P. Guerrero-Bote & Félix Moya-Anegón, 2014. "Relationship between downloads and citations at journal and paper levels, and the influence of language," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1043-1065, November.
    17. Jeong, Yoo Kyung & Xie, Qing & Yan, Erjia & Song, Min, 2020. "Examining drug and side effect relation using author–entity pair bipartite networks," Journal of Informetrics, Elsevier, vol. 14(1).
    18. Jang, Hyun Jin & Woo, Han-Gyun & Lee, Changyong, 2017. "Hawkes process-based technology impact analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 511-529.
    19. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    20. Lorena Espina-Romero & Doile Ríos Parra & José Gregorio Noroño-Sánchez & Gloria Rojas-Cangahuala & Luz Emerita Cervera Cajo & Pedro Alfonso Velásquez-Tapullima, 2024. "Navigating Digital Transformation: Current Trends in Digital Competencies for Open Innovation in Organizations," Sustainability, MDPI, vol. 16(5), pages 1-19, March.

    More about this item

    Statistics

    Access and download statistics

    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:58:y:2003:i:3:d:10.1023_b:scie.0000006883.28709.d2. 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.