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2019 | OriginalPaper | Chapter

Visualization of Data: Methods, Software, and Applications

Authors : Gintautas Dzemyda, Olga Kurasova, Viktor Medvedev, Giedrė Dzemydaitė

Published in: Advances in Mathematical Methods and High Performance Computing

Publisher: Springer International Publishing

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Abstract

Visualization is a part of data science, and essential to enable sophisticated analysis of data. The visualization ensures the human participation in most decisions when analyzing data. In this paper, we review methods and software for visualization of multidimensional data. The emphasis is put on the web-based DAMIS solution for data analysis, allowing researchers to carry out the primary data analysis and to investigate the projection of multidimensional data on a plane, the similarities between the data items, the influence of individual features, and their relationships by visual analysis techniques, using the high-performance computing resources. DAMIS is applied to the visual efficiency analysis of regional economic development to evaluate how regional resources are reflected in the economic results. The projection methods (principal component analysis, multidimensional scaling) and artificial neural networks (self-organizing map, SAMANN) are the core strategies for the analysis.

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MIDAS: The National Open Access Research Data Archive. https://doi.org/10.18279/MIDAS.RegionalData.xlsx.30026

Bai, J.: On regional innovation efficiency: evidence from panel data of China’s different provinces. Regional Studies 47(5), 773–788 (2013)CrossRef

Belkin, M., Niyogi, P.: Laplacian eigenmaps and spectral techniques for embedding and clustering. In: Advances in Neural Information Processing systems, pp. 585–591 (2002)

Bengoa, M., Martínez-San Román, V., Pérez, P.: Do R&D activities matter for productivity? A regional spatial approach assessing the role of human and social capital. Economic Modelling 60, 448–461 (2017)

Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kötter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B.: KNIME: The Konstanz Information Miner. In: Studies in Classification, Data Analysis, and Knowledge Organization. Springer (2007). https://doi.org/10.1007/978-3-540-78246-9_38 CrossRef

Borg, I., Groenen, P.: Modern Multidimensional Scaling: Theory and Applications. Springer (2005). https://doi.org/10.1007/0-387-28981-X

Borg, I., Groenen, P.J., Mair, P.: Applied Multidimensional Scaling. Springer Science & Business Media (2012)

Cai, Y., Hanley, A.: Innovation rankings: good, bad or revealing? Applied Economics Letters 21(5), 325–328 (2014)CrossRef

Daouia, A., Florens, J.P., Simar, L.: Regularization of nonparametric frontier estimators. Journal of Econometrics 168(2), 285–299 (2012)MathSciNetMATHCrossRef

10.

Daraio, C., Simar, L.: Introducing environmental variables in nonparametric frontier models: a probabilistic approach. Journal of Productivity Analysis 24(1), 93–121 (2005)CrossRef

11.

Demšar, J., Curk, T., Erjavec, A., Gorup, C., Hočevar, T., Milutinovič, M., Možina, M., Polajnar, M., Toplak, M., Starič, A., Štajdohar, M., Umek, L., Žagar, L., Žbontar, J., Žitnik, M., Zupan, B.: Orange: Data mining toolbox in Python. Journal of Machine Learning Research 14, 2349–2353 (2013)MATH

12.

Dubitzky, W. (ed.): Data Mining Techniques in Grid Computing Environments. John Wiley and Sons, Ltd (2009). https://doi.org/10.1002/9780470699904.ch1

13.

Dzemyda, G.: Visualization of a set of parameters characterized by their correlation matrix. Computational Statistics & Data Analysis 36(1), 15–30 (2001)MathSciNetMATHCrossRef

14.

Dzemyda, G., Kurasova, O.: Heuristic approach for minimizing the projection error in the integrated mapping. European Journal of Operational Research 171(3), 859–878 (2006). https://doi.org/10.1016/j.ejor.2004.09.011 MathSciNetMATHCrossRef

15.

Dzemyda, G., Kurasova, O., Medvedev, V.: Dimension reduction and data visualization using neural networks. In: I. Maglogiannis, K. Karpouzis, M. Wallace, J. Soldatos (eds.) Emerging Artificial Intelligence Applications in Computer Engineering, Frontiers in Artificial Intelligence and Applications, vol. 160, pp. 25–49. IOS Press (2007)

16.

Dzemyda, G., Kurasova, O., Žilinskas, J.: Multidimensional Data Visualization: Methods and Applications, Springer Optimization and its Applications, vol. 75. Springer (2013). https://doi.org/10.1007/978-1-4419-0236-8 MATHCrossRef

17.

Dzemydaitė, G., Dzemyda, I., Galinienė, B.: The efficiency of regional innovation systems in new member states of the European Union: a nonparametric DEA approach. Economics and Business 28(1), 83–89 (2016)CrossRef

18.

Dzemydaitė, G., Galinienė, B.: Evaluation of regional efficiency disparities by efficient frontier analysis. Ekonomika 92(4), 21 (2013)CrossRef

19.

Eurostat-European Commission and others: Regions in the European Union. Nomenclature of territorial units for statistics. Tech. rep., NUTS 2010/EU-27. Luxemburgo: Publications Office of the European Union (2011)

20.

Farrell, M.J.: The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General) 120(3), 253–290 (1957)CrossRef

21.

Groenen, P., Borg, I.: Past, present, and future of multidimensional scaling. Visualization and Verbalization of Data pp. 95–117 (2014)

22.

Groenen, P.J., van de Velden, M.: Multidimensional scaling by majorization: A review. Journal of Statistical Software 73(8), 1–26 (2016)CrossRef

23.

Guan, J., Chen, K.: Modeling the relative efficiency of national innovation systems. Research Policy 41(1), 102–115 (2012)MathSciNetCrossRef

24.

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: An update. SIGKDD Explorations Newsletter 11(1), 10–18 (2009). https://doi.org/10.1145/1656274.1656278 CrossRef

25.

Hofmann, M., Klinkenberg, R.: RapidMiner: Data Mining Use Cases and Business Analytics Applications. Chapman & Hall/CRC (2013)

26.

Jolliffe, I.: Principal Component Analysis. Springer, Berlin (1986). https://doi.org/10.1007/b98835

27.

Kohonen, T.: Overture. In: Self-Organizing Neural Networks: Recent Advances and Applications, pp. 1–12. Springer-Verlag, New York, NY, USA (2002)MATH

28.

Kurasova, O., Molytė, A.: Integration of the self-organizing map and neural gas with multidimensional scaling. Information Technology and Control 40(1), 12–20 (2011)CrossRef

29.

Kurasova, O., Molytė, A.: Quality of quantization and visualization of vectors obtained by neural gas and self-organizing map. Informatica 22(1), 115–134 (2011)MathSciNet

30.

Mao, J., Jain, A.K.: Artificial neural networks for feature extraction and multivariate data projection. IEEE Transactions on Neural Networks 6(2), 296–317 (1995). https://doi.org/10.1109/72.363467 CrossRef

31.

Medvedev, V., Dzemyda, G., Kurasova, O., Marcinkevičius, V.: Efficient data projection for visual analysis of large data sets using neural networks. Informatica 22(4), 507–520 (2011)MATH

32.

Medvedev, V., Kurasova, O., Bernatavičienė, J., Treigys, P., Marcinkevičius, V., Dzemyda, G.: A new web-based solution for modelling data mining processes. Simulation Modelling Practice and Theory (2017)

33.

Schaffer, A., Simar, L., Rauland, J.: Decomposing regional efficiency. Journal of Regional Science 51(5), 931–947 (2011)CrossRef

34.

Talia, D., Trunfio, P.: Service-oriented Distributed Knowledge Discovery. Chapman and Hall/CRC (2012). https://doi.org/10.1201/b12990-4

35.

Tenenbaum, J.B., De Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319–2323 (2000)CrossRef

36.

Venskus, J., Treigys, P., Bernataviciene, J., Medvedev, V., Vozňák, M., Kurmis, M., Bulbenkiene, V.: Integration of a self-organizing map and a virtual pheromone for real-time abnormal movement detection in marine traffic. Informatica 28(2), 359–374 (2017)CrossRef

37.

Vila, L.E., Cabrer, B., Pavía, J.M.: On the relationship between knowledge creation and economic performance. Technological and Economic Development of Economy 21(4), 539–556 (2015)CrossRef

38.

Žilinskas, J.: Parallel branch and bound for multidimensional scaling with city-block distances. Journal of Global Optimization 54(2), 261–274 (2012)MathSciNetMATHCrossRef

Title: Visualization of Data: Methods, Software, and Applications
Authors: Gintautas Dzemyda
Olga Kurasova
Viktor Medvedev
Giedrė Dzemydaitė
Publisher: Springer International Publishing
Book: Advances in Mathematical Methods and High Performance Computing
Print ISBN: 978-3-030-02486-4

Electronic ISBN: 978-3-030-02487-1

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-02487-1_18

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