IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-032-08489-7_9.html

A Method for Performing Ontology-Based Computational Literature Reviews Exemplified for Design Science Research

In: Shaping the Digital Future Through Innovation and Practice

Author

Listed:
  • Sebastian Huettemann

    (Berlin School of Economics and Law)

  • Roland M. Mueller

    (Berlin School of Economics and Law)

  • Barbara Dinter

    (Chemnitz University of Technology)

Abstract

The traditional process of conducting literature reviews requires a significant amount of manual work and is often constrained by the limitations of small sample sizes. Although novel computational approaches to language analysis offer great opportunities, they are rarely applied to literature reviews. We aim to demonstrate the potential of ontology-based computational literature reviews. Therefore, we conducted a Design Science Research (DSR) project to apply and extend a method for this type of review. Since DSR shows a considerable diversity in theoretical foundations and methodological approaches and can serve as an insightful example, we first developed a machine learning classifier to identify DSR articles. Second, we applied and extended a method for ontological annotation and sentence classification. Finally, we conducted a computational literature review of 6235 DSR articles, focusing on the distribution of theories, methods, and topics. We also developed an interactive dashboard prototype with selected results from our study.

Suggested Citation

  • Sebastian Huettemann & Roland M. Mueller & Barbara Dinter, 2026. "A Method for Performing Ontology-Based Computational Literature Reviews Exemplified for Design Science Research," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Shaping the Digital Future Through Innovation and Practice, pages 119-134, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08489-7_9
    DOI: 10.1007/978-3-032-08489-7_9
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:lnichp:978-3-032-08489-7_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.

    We have no bibliographic references for this item. You can help adding them by using 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.