Call for Paper - December 2020 Edition
IJCA solicits original research papers for the December 2020 Edition. Last date of manuscript submission is November 20, 2020. Read More

Big Data Analytics for Data Visualization: Review of Techniques

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Geetika Chawla, Savita Bamal, Rekha Khatana
10.5120/ijca2018917977

Geetika Chawla, Savita Bamal and Rekha Khatana. Big Data Analytics for Data Visualization: Review of Techniques. International Journal of Computer Applications 182(21):37-40, October 2018. BibTeX

@article{10.5120/ijca2018917977,
	author = {Geetika Chawla and Savita Bamal and Rekha Khatana},
	title = {Big Data Analytics for Data Visualization: Review of Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2018},
	volume = {182},
	number = {21},
	month = {Oct},
	year = {2018},
	issn = {0975-8887},
	pages = {37-40},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume182/number21/30059-2018917977},
	doi = {10.5120/ijca2018917977},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This is information era, where information is increasing exponentially. Extracting information in a way that the human mind can comprehend is a big challenge. Visualization plays a key role in data discovery process and in better decision making. A question still arises how to visualize interesting structures and patterns that are in hyper-dimensional data spaces. We can sketch a convincing visual story from raw data with the use of right tool. This paper focuses on Big Data visualization, its challenges, various tools. Researchers have explored a new way to visualize and analyze complex and dynamic datasets using virtual reality. We have also investigated how virtual reality has radically changed the world of Big Data Visualization.

References

  1. SAS, Data Visualization: What it is and why it matters, www.sas.com/ensg/insights/big-data/data- visualization.html.
  2. Agrawal R, Kadadi A, Dai X, and Andres F, 2015 “Challenges and opportunities with big data visualization,” 7th International Conference on Management of computational and collective intelligence in Digital EcoSystems, 2015 Oct 25 (pp. 169-173). ACM.
  3. Pamela Vagata and Kevin Wilfong, 2014. Scaling the facebook data warehouse to 300PB.https://code.facebook.com/posts/229861827208629/ scaling-the-facebook-data-warehouse-to-300-pb/, April 2014.
  4. Childs H, Geveci B, Schroeder W, Meredith J, Moreland K, Sewell C, Kuhlen T, and Bethel EW, 2013.“Research challenges for visualization software,” Computer, 2013 May 1(5), 34-42.
  5. T. A. Keahey, Using visualization to understand big data, Technical Report, IBM Corporation, 2013, 1-16.
  6. Syed Mohd Ali, Noopur Gupta, Gopal Krishna Nayak, Rakesh Kumar Lenka, “Big Data Visualization: Tools and Challenges.” 2nd International Conference on Contemporary Computing and Informatics (ic3i).
  7. Tavel, P. 2007. “Modeling and simulation design,” AK Peters Ltd. Natick, MA,2007.
  8. John N. W., Leng J. 2001. "Scientific Applications of Visualization, Virtual Reality and High Performance Visualization Computers", and "Scientific Examples of Virtual Reality and Visualization Applications", Two associated UKHEC reports, 2001.
  9. C. Cruz-Neira, 1993. “Virtual Reality Overview”. SIGGRAPH’ 93, 1.1-1.18 (1993).
  10. C.L. P. Chen, C.-Y. Zhang, 2014. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data, Information Sciences, 275 (10), August 2014, 314-347.
  11. E.Y. Gorodov and V.V. Gubarev, 2013. “Analytical Review of Data Visualization Methods in Application to Big Data,” Journal of Electrical and Computer Engineering, 2013, Jan 1;2013:22.
  12. Andrew Tran, 2015. Introduction to plotly, Sep,2015. http://andrewbtran.github.io/JRN- 418/class3/plotly.html#/
  13. https://www.sas.com/en_in/software/business- intelligence/visual-analytics.html.
  14. B. Laha, D.A. Bowman and J.J. Socha, 2014. “Effects of VR System Fidelity on Analyzing Isosurface Visualization of Volume Datasets,” IEEE Transactions on Visualization and Computer Graphics, 20(4) 513- 522, 2014.
  15. C. Demiralp, C. D. Jackson, D. B. Karelitz, S. Zhang, and D. H. Laidlaw, 2006. "CAVE and Fishtank Virtual- Reality Displays: A Qualitative and Quantitative Comparison," IEEE Transactions on Visualization and Computer Graphics, vol. 12, pp. 323-330, 2006.
  16. T.V. Williams, 1982. A man-machine interface for interpreting electron-density maps. Ph.D. dissertation, University of North Carolina, Chapel Hill, 1982
  17. J. Chen, H. Cai, A. P. Auchus, and D. H. Laidlaw, 2012 "Effects of Stereo and Screen Size on the Legibility of Three-Dimensional Streamtube Visualization," IEEE Transactions on Visualization and Computer Graphics, vol. 18, pp. 2130-2139, 2012.
  18. C. Donalek, S. Djorgovski, A. Cioc, A. Wang, J. Zhang, E. Lawler, S. Yeh, A. Mahabal, M. Graham, A. Drake, S. Davidoff, J. S. Norris, G. Longo, 2014. "Immersive and collaborative data visualization using virtual reality platforms", Proceedings of the IEEE International Conference on Big Data ser. IEEE BigData 2014, pp. 609-614, 2014.
  19. https://www.wired.com/2014/5/darpa-is-using-oculus- rift-to-prep-for-cyberwar/
  20. Ekaterina Olshannikova1, Aleksandr Ometov1, Yevgeni Koucheryavy1 and Thomas Olsson2, 2015 ” Visualizing Big Data with augmented and virtual reality: challenges and research agenda”, Journal of Big Data (2015) 2:22
  21. https://www.sas.com/en_us/insights/big-data/data- visualization.html

Keywords

Big Data, Big Data Visualization, Virtual reality