DATA VISUALIZATION AND DEPICTION INTERFACE TO DEVELOP CANCER EPIDEMIC DATASET
DOI:
https://doi.org/10.61841/e20w2v90Keywords:
Cancer, data vislualization,bar plot, depiction, density, areaAbstract
Data visualization is the vivid depiction of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide a versatile way to glimpse and understand trends, outliers, and patterns in data. In the world of Big Data, data visualization tools and technologies are vital part of analyzing the massive amounts of information and make data-driven decisions. As an outcome of the progressive technological trend, massive amounts of data from different subjects and areas are continuously generated and classified on a daily basis. In the past, the main problems were the preservation and publishing of data sets, but today, one of the main challenges is the presentation for more understanding of the data. The suitable visual representation of a given data set is the foundation for a precise and consistent interpretation, analysis and adoption of empirical conclusions related to the semantic meaning of information. In this paper, we present a synopsis of data visualization techniques and their practical application, starting from the acquisition of an unstructured set of publicly available data, their proper preprocessing and organization, and the visual representation for the end user. The nature of the data is related to the emergence, potential and development of various types of cancer diseases officially registered in different geographical regions. We present an interactive system that implements several visualization techniques.
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1. D.A.Keim, “Information Visualization and Visual Data Mining”, IEEE Transactions on visualization and computer graphics, 2002, 8(1):1-8.
2. E. Saranya, A. Sunitha. “Identifying data integrity in Cloud Storage” International Journal of Computer Science, , Mar 2012, 9: 1694-14.
3. B. Stewart and C.P. Wild (eds.), International Agency for Research on Cancer, World Health Organization, (2014) World Cancer Report 2014 [Online], Available from: http://www.iarc.fr/en/publications/books/wcr/wcrorder.php [Accessed: 10th June 2016].
4. G. Wagner, History of cancer registration. In: O.M. Jensen, D.M. Parkin, R. MacLennan, et al, eds. Cancer registration: principles and methods. IARC Scientific Publications no 95. Lyon: International Agency for Research on Cancer, 1991: 3–6.
5. D.M.Parkin, The evolution of the population-based cancer registry, Nat Rev Cancer, 2006; 6: 603–12.
[6] A.M. MacEachren, C.A. Brewer and L.W. Pickle, “Visualizing Georeferenced Data: Representing Reliability of Health Statistics”, Environment and Planning, 1998, 30:1547-61.
6. F. Fan and E.S. Biagioni, “An approach to data visualization and interpretation for sensor networks”, Proceeding of the 37th HICSS, 2004.
7. J.P. McCusker, D.L. McGuinness, J. Lee, C. Thomas, P. Courtney, Z. Tatalovich, N. Contractor, G. Morgan and A. Shaikh, “Towards next generation health data exploration: a data cube-based investigation into population statistics fortobacco”, InSystem Sciences (HICSS), 2013 46th Hawaii International Conference on, 2013, 2725-2732 IEEE.
8. S.O. Torres, H. Eicher-Miller, C. Boushey, D. Ebert and R. Maciejewski, “Applied visual analytics for exploring the national health and nutrition examination survey”, Proceeding of the 45th HICSS, 2012.
[10] L.S. Yung, C. Yang and M. Dakna, “SyncPro: A synchronized visualization tool for differential analysis of proteomics data sets”, InBioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference, 2010, 95-100 IEEE.
9. M. Blevins, F.H. Wehbe, P.F. Rebeiro PF, C.C McGowan and B.E. Shepherd, “Interactive Data Visualization for HIV Cohorts: Leveraging Data Exchange Standards to Share and Reuse Research Tools”, PloS one, 2016, 11:e0151201.
10. C.R. Baquet, J.W. Horm, T. Gibbs and P. Greenwald, “Socioeconomic factors and cancer incidence”, J Natl Cancer Inst, 1991, 83:551-57. [13] O.B. Ahmad, C. Boschi-Pinto, A.D. Lopez, C.J. Murray, R. Lozano and M. Inoue. Age standardization of rates: A new WHO standard. World Health Organization 2001. GPE Discussion Paper Series: No.31. Available from: http://www.who.int/healthinfo/paper31.pdf, accessed [6 Jun 2016]
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