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A literature study of bottlenecks in 2D and 3D Big Data visualization
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Context. Big data visualization is a vital part of today's technological advancement. It is about visualizing different variables on a graph, map, or other means often in real-time.

Objectives. This study aims to determine what challenges there are for big data visualization, whether significant amounts of data impact the visualization, and finding existing solutions for the problems.

Methods. Databases used in this systematic literature review include Inspec, IEEE Xplore, and BTH Summon. Papers are included in the review if certain criteria are upheld.

Results. 6 solutions are found to reduce large data sets and reduce latency when viewing 2D and 3D graphs.

Conclusions. In conclusion, many solutions exist in various forms to improve visualizing graphs of different dimensions. Future grows of data might change this though and might require new solutions of the growing data.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Human perception, Big data, N-dimensional Data, Visualization.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-15461OAI: oai:DiVA.org:bth-15461DiVA: diva2:1155657
Subject / course
DV1478 Bachelor Thesis in Computer Science
Supervisors
Examiners
Available from: 2017-11-09 Created: 2017-11-08 Last updated: 2017-11-09Bibliographically approved

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fulltext(535 kB)32 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf