Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

High Dimensional Data Visualization: Advances and Challenges

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Fisseha Gidey G., Charles Awono Onana

Fisseha Gidey G. and Charles Awono Onana. High Dimensional Data Visualization: Advances and Challenges. International Journal of Computer Applications 162(10):23-27, March 2017. BibTeX

	author = {Fisseha Gidey G. and Charles Awono Onana},
	title = {High Dimensional Data Visualization: Advances and Challenges},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {162},
	number = {10},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {23-27},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017913362},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Recent technological advances and availability of computing resources resulted in a massive growth of data size, dimensions and complexity. Data visualization is a good approach when dealing with large scale high dimensional datasets as it will provide the opportunity to understand what’s in the data and where to focus. However, the ever increasing dimensions of datasets, the physical limitations of the display screen (2D/3D), and the relatively small capacity of our mind to process complex data at a time pose a challenge in the process of visualization. This paper describe the advancements made so far in visualizing high dimensional data and the challenges that should be addressed in future researches.


  1. Agnes Vathy-Fogarassy and Janos Abonyi. 2013. Graph Based Clustering and Data Visualization Algorithms, Springer.
  2. Anna Maria K. and Janos Abonyi. Visualization of Fuzzy Clustering Results by Modified Sammon Mapping. University of Veszprem
  3. ArpitJangid and Soren Goyal. 2015. Techniques for visualizations of high dimensional data, convex optimization.
  4. Brown, L. D., Hua, H., and Gao, C. 2003. A widget framework for augmented interaction in SCAPE
  5. C. Donalek, S G., Djorgovski, et al. 2014. Immersive and collaborative data visualization using virtual reality platforms. IEEE International conference
  6. Daniel A. Kein. 2001. Visual Exploration of Large Datasets. Communication of the ACM
  7. Daniel A. Keim. 2002. Information Visualization and Visual Data Mining. Transaction on visualization and computer graphics, IEEE, vol 7
  8. 2013. Data Processing and Visualization Tools. European Public Sector Information Platform, Topic Report No: 2013/07
  9. Edward R. Tufte (1997): Visual Explanations: Images, Quantities, Evidence, and Narrative. Graphics Press.
  10. Ingwer Borg and Patrick Groenen. 1997. Modern Multidimensional Scaling: Theory and Applications. Springer
  11. Johan A.K Suykens. 2008. Data Visualization and Dimensionality Reduction Using Kernel Maps with a Reference point. IEEE Transaction on Neural Networks
  12. Justin Choy. 2012. Visualization Techniques from Basics to Big Data with SAS Visual Analytics. SAS Global Forum
  13. K. Chen. 2014. Optimizing Star-Coordinate Visualization Method for Effective Interactive Cluster Exploration on Big Data. Intelligent Data Analysis
  14. Laurens Van der Maaten, Eric Postme, Jaap Van den Herik. 2009. Dimensionality reduction: A comparative Review. Tilburg University.
  15. Lidongwang, Guanghuiwang, and Cheryl Ann Alexander. 2015. Big Data Visualization: Methods, Challenges, and Technology Progress
  16. NemanjaDjuric. 2014. Big Data Algorithms for Visualization and Supervised Learning
  17. NicolaeApostolescu and Daniela Baran. 2016. Sammon Mapping for preliminary Analysis in Hyperspectral Imagery. The 36th IEEE “Caius Iacob” conference on Fluid mechanics
  18. Olga Kurasove, VirginijusMarcinkevicius, and Victor Medvedev. 2014. Strategies for Big Data Clustering. IEEE 26th International Conference on Tools with Artificial Intelligence
  19. PoojaChenna. 2016. Comparative Study of Dimension Reduction Approaches with Respect to Visualization in 3-Dimensional Space. Kennesaw State University, Springer.
  20. SeungHeeBae and Judy Qiu. 2012. High Performance Multidimensional scaling for Large High Dimensional Data Visualization. IEEE Transaction of parallel and Distributed System.
  21. Stephane Few. 2007. Data Visualization Past, Present, and Future. Perceptual edge
  22. S.Lui, D. Maljovich, B. Wang, P.-T. Bremer and V.Pascucci. Visualizing High dimensional data: Advances in the past decade
  23. Data means Big Business. Douglas Laney. Gartnerinc.
  24. Big Data for development:-From Information to Knowledge Societies,2013


Big Data, Data Visualization, Dimension Reduction, PCA, Sammon’s Mapping, and MDS