IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v91y2012i2d10.1007_s11192-012-0626-8.html
   My bibliography  Save this article

Visualization of research fronts and knowledge bases by three-dimensional areal densities of bibliographically coupled publications and co-citations

Author

Listed:
  • Edgar Schiebel

    (AIT Austrian Institute of Technology GmbH, Technology Management)

Abstract

In this work the well known scientometric concepts of bibliographically coupled publications and co-cited references were applied to produce interactive maps of research fronts and knowledge bases of research fields. This article proposes a method and some standardization for the detection and visualization of research fronts and knowledge bases with two and three dimensional graphics inspired by geographical maps. Agglomerations of bibliographically coupled publications with a common knowledge base are identified and graphically represented by a density function of publications per area unit. The research fronts become visible if publications with similar vectors of common citations are associated and visualized as an ensemble in a three dimensional graphical representation as a mountain scenery measured with the help of a spatial density. Knowledge bases were calculated in the same way. Maps similar to the geographic representation of oceans and islands are used to visualize the two-dimensional spatial density function of references weighted by individual links. The proposed methodology is demonstrated by publications in the field of battery research.

Suggested Citation

  • Edgar Schiebel, 2012. "Visualization of research fronts and knowledge bases by three-dimensional areal densities of bibliographically coupled publications and co-citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 557-566, May.
  • Handle: RePEc:spr:scient:v:91:y:2012:i:2:d:10.1007_s11192-012-0626-8
    DOI: 10.1007/s11192-012-0626-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-012-0626-8
    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/s11192-012-0626-8?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. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    3. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    4. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    5. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    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. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
    2. Alfonso Ávila-Robinson & Shintaro Sengoku, 2017. "Tracing the knowledge-building dynamics in new stem cell technologies through techno-scientific networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1691-1720, September.
    3. Xuezhao Wang & Yajuan Zhao & Rui Liu & Jing Zhang, 2013. "Knowledge-transfer analysis based on co-citation clustering," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 859-869, December.
    4. Mu-hsuan Huang & Chia-Pin Chang, 2015. "A comparative study on detecting research fronts in the organic light-emitting diode (OLED) field using bibliographic coupling and co-citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2041-2057, March.
    5. Bart Thijs & Edgar Schiebel & Wolfgang Glänzel, 2013. "Do second-order similarities provide added-value in a hybrid approach?," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 667-677, September.
    6. Liu, Yunmei & Yang, Liu & Chen, Min, 2021. "A new citation concept: Triangular citation in the literature," Journal of Informetrics, Elsevier, vol. 15(2).
    7. Linqing Liu & Shiye Mei, 2016. "Visualizing the GVC research: a co-occurrence network based bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 953-977, November.
    8. Berndt Jesenko & Christian Schlögl, 2021. "The effect of web of science subject categories on clustering: the case of data-driven methods in business and economic sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6785-6801, August.
    9. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.

    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. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    2. Toshiyuki Hasumi & Mei-Shiu Chiu, 2022. "Online mathematics education as bio-eco-techno process: bibliometric analysis using co-authorship and bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4631-4654, August.
    3. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    4. Li, Munan & Porter, Alan L. & Suominen, Arho, 2018. "Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 285-296.
    5. David Chavalarias & Quentin Lobbé & Alexandre Delanoë, 2022. "Draw me Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 545-575, January.
    6. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    7. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    8. Rey-Long Liu, 2017. "A new bibliographic coupling measure with descriptive capability," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 915-935, February.
    9. Yulei Xie & Ling Ji & Beibei Zhang & Gordon Huang, 2018. "Evolution of the Scientific Literature on Input–Output Analysis: A Bibliometric Analysis of 1990–2017," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    10. Chris W. Belter, 2013. "A bibliometric analysis of NOAA’s Office of Ocean Exploration and Research," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 629-644, May.
    11. Ding, Ying, 2011. "Community detection: Topological vs. topical," Journal of Informetrics, Elsevier, vol. 5(4), pages 498-514.
    12. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    13. Rui Li & Hong Zhang & Chenguang Liu & Zhenyu Cheryl Qian & Linghao Zhang, 2022. "Bibliometric and Visualized Analysis of User Experience Design Research: From 1999 to 2019," SAGE Open, , vol. 12(1), pages 21582440221, March.
    14. Diego Kozlowski & Jennifer Dusdal & Jun Pang & Andreas Zilian, 2021. "Semantic and relational spaces in science of science: deep learning models for article vectorisation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5881-5910, July.
    15. Kyebambe, Moses Ntanda & Cheng, Ge & Huang, Yunqing & He, Chunhui & Zhang, Zhenyu, 2017. "Forecasting emerging technologies: A supervised learning approach through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 236-244.
    16. Mingchun Cao & Ilan Alon, 2020. "Intellectual Structure of the Belt and Road Initiative Research: A Scientometric Analysis and Suggestions for a Future Research Agenda," Sustainability, MDPI, vol. 12(17), pages 1-40, August.
    17. Kraker, Peter & Schlögl, Christian & Jack, Kris & Lindstaedt, Stefanie, 2015. "Visualization of co-readership patterns from an online reference management system," Journal of Informetrics, Elsevier, vol. 9(1), pages 169-182.
    18. Nauman Majeed & Sulaiman Ainin, 2021. "Visualizing the evolution and landscape of socio-economic impact research," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 637-659, April.
    19. Fan, Yangliu & Lehmann, Sune & Blok, Anders, 2022. "Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach," Journal of Informetrics, Elsevier, vol. 16(3).
    20. Rons, Nadine, 2018. "Bibliometric approximation of a scientific specialty by combining key sources, title words, authors and references," Journal of Informetrics, Elsevier, vol. 12(1), pages 113-132.

    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:91:y:2012:i:2:d:10.1007_s11192-012-0626-8. 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.