On the use of Biplot analysis for multivariate bibliometric and scientific indicators

Torres-Salinas, Daniel and Robinson-Garcia, Nicolas and Jiménez-Contreras, Evaristo and Herrera, Francisco and Delgado-López-Cózar, Emilio On the use of Biplot analysis for multivariate bibliometric and scientific indicators., 2012 [Preprint]

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Alternative locations: http://arxiv.org/abs/1302.0608v1

English abstract

Bibliometric mapping and visualization techniques represent one of the main pillars in the field of scientometrics. Traditionally, the main methodologies employed for representing data are Multi-Dimensional Scaling, Principal Component Analysis or Correspondence Analysis. In this paper we aim at presenting a visualization methodology known as Biplot analysis for representing bibliometric and science and technology indicators. A Biplot is a graphical representation of multivariate data, where the elements of a data matrix are represented according to dots and vectors associated with the rows and columns of the matrix. In this paper we explore the possibilities of applying the Biplot analysis in the research policy area. More specifically we will first describe and introduce the reader to this methodology and secondly, we will analyze its strengths and weaknesses through three different study cases: countries, universities and scientific fields. For this, we use a Biplot analysis known as JK-Biplot. Finally we compare the Biplot representation with other multivariate analysis techniques. We conclude that Biplot analysis could be a useful technique in scientometrics when studying multivariate data and an easy-to-read tool for research decision makers.

Item type: Preprint
Keywords: Biplot; JK-Biplot; Bibliometric Indicators; Principal Component Analysis; Multivariate Analysis; Information visualization; Science Maps
Subjects: B. Information use and sociology of information > BB. Bibliometric methods
Depositing user: Nicolas Robinson-Garcia
Date deposited: 18 Apr 2013 08:03
Last modified: 02 Oct 2014 12:25
URI: http://hdl.handle.net/10760/18984

References

Alcántara, M., & Rivas, C. (2007). Las dimensiones de la polarización partidista en América Latina. Política y Gobierno, 14(2), 349-390.

Arias Díaz-Faes, A., Benito-García, N., Martín-Rodero, H., & Vicente-Villardón, J.L. (2011).

Propuesta de aplicabilidad del método multivariante gráfico "BIPLOT" a los estudios bibliométricos en biomedicina. In XIV Jornadas Nacionales de Información y Documentación en Ciencias de la Salud, Cádiz, 13-15 de Abril de 2011. (Unpublished) [Conference Poster]. From: http://hdl.handle.net/10760/15998

Börner, K., Chen, C., & Boyack, K.W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 149-255.

Cárdenas, O., Galindo, P., & Vicente-Villar don, J.L. (2007). Los métodos Biplot: evolución y aplicaciones. Revista Venezolana de Análisis de Coyuntura, 13(1), 279-303.

Chapman, S., Shenk, P., Kazan, K., & Manners, J. (2001). Using Biplots to interpret gene expression pattern in plants. Bioinformatics Applications Note, 18(1), 202-204.

Gabriel, K.R. (1971). The Biplot graphic display of matrices with application to principal component analysis. Biometrika, 58(3), 453-467.

Gabriel, K.R. (2002). Goodness of fit of biplots and correspondence analysis. Biometrika, 89(2), 423-436.

Gabriel, K.R., & Odoroff, C.L. (1990). Biplots in biomedical research. Sta. Med., 9, 469-485.

Galindo, P. (1986). Una alternativa de representación simultánea: HJ Biplot. Qüestiió, 10(1), 13-23.

Galindo, P.V., Vaz, T.D., & Nijkamp, P. (2011).Institutional capacity to dynamically innovate: an application to the Portuguese case. Technological Forecasting and Social Change, 78(1), 3-12.

Groh, G., & Fuchs, C. (2011).Multi-modal social networks for modeling scientific fields. Scientometrics, 89(2), 569-590.

Klavans, R., & Boyack, K.W. (2009). Towards a consensus map of science. Journal of the American Society of Information Science and Technology, 60(3), 455-476.

Moya-Anegón, F., Herrero-Solana, V., & Jiménez-Contreras, J. (2006). A connectionist and multivariate approach to science maps: the SOM, clustering and MDS applied to library and information science research. Journal of Information Science, 32(1), 63-77.

Noyons, E. (2001). Bibliometric mapping of science in a science policy context. Scientometrics, 50(1), 83-98.

Noyons, E., & Calero-Medina, C. (2009). Applying bibliometric mapping in a high level science policy context. Scientometrics, 79(2), 473-490.

Pan, S., Chon, K., & Song, H.Y. (2008).Visualizing tourism trends: a combination of ATLAS. ti and Biplot. Journal of Travel Research, 46(3), 339-348.

Theoharatos, C., Laskaris, N.A., Economu, G., & Fotopoulos, S. (2007). On the perceptual organization of image databases using cognitive discriminative biplots. Eurasip Journal on Advances in Signal Processing, 68165.

Torres-Salinas, D., Delgado-López-Cózar, E., Moreno-Torres, J.G., & Herrera, F. (2011a). Rankings ISI de las universidades españolas por campos científicos: Descripción y resultados. El profesional de la información, 20(1), 111-122.

Torres-Salinas, D., Delgado-López-Cózar, E., Moreno-Torres, J.G., & Herrera, F. (2011b). A methodology for Institution-Field ranking based on a bidimensional analysis: the IFQ2A Index. Scientometrics, 88(3), 771-786.

Van Eck, N.J., Waltman, L., Dekker, R., & van den Berg, J. (2010).A comparison of two techniques for bibliometric mapping: multidimension al scaling and VOS. Journal of the American Society for Information Science and Technology, 61(12), 2405-2416.

Veiga de Cabo, J., & Martín-Rodero, H. (2011). Acceso Abierto: nuevos modelos de edición

científica en entornos web 2.0. Salud Colectiva, 7(Supl. 1), S19-S27.

White, H. (2003). Pathfinder networks and author cocitation analysis: A remapping of

paradigmatic information scientists. Journal of the American Society for Information Science and Technology, 54(5), 423-434.

White, H., & McCain, K. (1998). Visualization of literatures. Annual Review of Information Science of Science and Technology, 32, 99-169.

Wouters, L., Gohlmann, H.W., Bijnens, L., Kass, S.U., Molenberghs, G., & Lewi, P.J. (2003). Graphical exploration of gene expression data: a comparative study of three multivariate methods. Biometrics, 59(4), 1131-1139.

Wouters, P. (1999). The citation culture [Doctoral Thesis]. Amsterdam: Universiteit van Amsterdam. From: http://garfield.library.upenn.edu/wouters/wouters.pdf

Yan, W. K., Hunt, L.A., Sheng, Q.L., & Szlavnics, Z. (2000).Cultivar evaluation and mega-environment investigation based on the GGE Biplot. Crop Science, 40(3), 597-605.


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