Abstract
Visual representations of data have a long history. Before the invention of the computer and the graphics display they were produced manually, often according to well-established norms and traditions. Techniques were developed for drawings and paintings for the realistic presentation of objects, and 2D and 3D scenes. Subsequently, the development of computer software enabled the analysis and presentation of data according to a wide variety of presentation styles such as graphs, charts and statistical distributions. This was followed by the production of visualization facilities which enabled a wide range of data types to be processed and displayed. Such data could also be explored interactively in order to concentrate on areas of particular interest. One objective of such visual representations has been to capitalize on the bandwidth of the human visual system and maximize the power of human reasoning and cognition in order to be able to extract validated meaning and knowledge from data. The range and volume of data sources has increased over time, particularly those generating real-time data. This has posed additional challenges for the analysis of the data and also its effective representation and display. Rapid analysis is needed in areas where immediate decisions need to be made based on the results of the analysis of the data. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze it, attention is being focussed how best to address these challenges.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sutherland, I.E.: Sketchpad, a man machine graphical communication system. Ph.D. Thesis, MIT (1963). http://hdl.handle.net/1721.1/14979, https://en.wikipedia.org/wiki/Sketchpad, https://www.youtube.com/watch?v=BKM3CmRqK2o, https://www.youtube.com/watch?v=USyoT_Ha_bA, https://www.youtube.com/watch?v=495nCzxM9PI
Dill, J.C., Thomas, J.J.: On the organization of a remote low cost intelligent graphics terminal. In: Proceedings of the 2nd Annual Conference on Computer Graphics and Interactive Techniques (Siggraph 75), pp. 1–8, https://doi.org/10.1145/563732.563733. ACM, New York (1975). https://doi.org/10.1145/1476589.1476686
Sutherland, I.E.: The ultimate display. Information Processing 1965: Proceedings of the IFIP Congress, pp. 506–508. Macmillan, London (1965). http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.3720, https://www.wired.com/2009/09/augmented-reality-the-ultimate-display-by-ivan-sutherland-1965/, http://graphics.cs.wisc.edu/WP/virtualreality11/2011/01/05/the-ultimate-display-by-ivan-sutherland-1965/, https://prezi.com/ugrvf4opamsv/1965-ivan-sutherland-ultimate-display-the-beginnings-of-vr/, http://www.roadtovr.com/fred-brooks-ivan-sutherlands-1965-ultimate-display-speech/
Sutherland, I.E.: A head-mounted three dimensional display. In: Proceedings of the Fall Joint Computer Conference (AFIPS 68, part I), pp. 757–764. ACM, New York (1968). https://doi.org/10.1145/1476589.1476686, https://en.wikipedia.org/wiki/The_Sword_of_Damocles_(virtual_reality)
Kay, A.: Sketchpad, by Dr. Ivan Sutherland with comments by Alan Kay. https://www.youtube.com/watch?v=495nCzxM9PI
Earnshaw, R.A., Wiseman, N.: An Introductory Guide to Scientific Visualization, p. 156. Springer, London (1992). ISBN 0-387-54664-2. http://link.springer.com/book/10.1007/978-3-642-58101-4
Brown, J.R., Earnshaw, R.A., Jern, M., Vince, J.A.: Visualization: Using Computer Graphics to Explore Data and Present Information, p. 287. Wiley, Hoboken (1995). ISBN 0-471-12991-7. http://www.amazon.co.uk/Visualization-Computer-Graphics-Explore-Information/dp/0471129917
https://en.wikipedia.org/wiki/Visualization_(graphics), https://en.wikipedia.org/wiki/Data_visualization
Ward, M.O., Grinstein, G., Keim, D.: Interactive Data Visualization: Foundations, Techniques, and Applications, p. 513. A K Peters/CRC Press, Boca Raton (2010)
Heer, J., Bostock, M., Ogievetsky, V.: A tour through the visualization zoo: A survey of powerful visualization techniques, from the obvious to the obscure. Commun. ACM. 53(6), 59–67 (2010). http://queue.acm.org/detail.cfm?id=1805128, https://idl.cs.washington.edu/files/2012-VisualizationZoo-CACM.pdf, https://pdfs.semanticscholar.org/532e/d73c71101fc64e4c307d7d932d4c90140487.pdf
Bederson, B., Shneiderman, B.: The Craft of Information Visualization: Readings and Reflections. Morgan Kaufmann, San Francisco (2003)
Thomas, J.J., Cook, K.A. (eds.): Illuminating the Path: The R&D Agenda for Visual Analytics, p. 190. National Visualization and Analytics Center (2005). http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf
Rattenbury, T., Hellerstein, J., Heer, J., Kandel, S., Carreras, C.: Principles of Data Wrangling: Practical Techniques for Data Preparation. O’Reilly, Farnham (2017)
https://www.trifacta.com/gated-form/principles-of-data-wrangling/?utm_medium=referral&utm_source=media+alert&utm_campaign=book+launch, http://vis.stanford.edu/wrangler/, http://vis.stanford.edu/papers/wrangler
Chuang, J., Ramage, D., Manning, C.D., Heer, J.: Interpretation and trust: designing model-driven visualizations for text analysis. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM (2012). http://vis.stanford.edu/files/2012-InterpretationTrust-CHI.pdf
Bradel, L., Wycoff, N., House, L., North, C.: Big text visual analytics in sensemaking. Big Data Visual Analytics (2015). https://doi.org/10.1109/BDVA.2015.7314287
Aggarwal, C.C. (ed.): Social Network Data Analytics, p. 507. Springer (2011); Borgatti, S.P., Everett, M.G., Johnson, J.C.: Analyzing Social Networks, p. 304. Sage Publications Ltd., Thousand Oaks (2013)
Zhao, Z., Feng, Z., Zhang, Y., Ning, L., Fan, J., Feng, S.: Collecting, managing and analyzing social networking data effectively. In: 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), (2015). https://doi.org/10.1109/fskd.2015.7382191
Gorg, C., Liu, Z., Kihm, J., Choo, J., Park, H., Stasko, J.: Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw. IEEE Trans. Visual Comput. Graphics 19, 1646–1663 (2013). https://doi.org/10.1109/TVCG.2012.324
Earnshaw, R.A.: Art, Design and Technology: Collaboration and Implementation, p. 87. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-58121-7, http://www.springer.com/gp/book/9783319581200
Davenport, T.H.: How analytics has changed in the last 10 years (and how it’s stayed the same). Harvard Bus. Rev. (2017). https://hbr.org/2017/06/how-analytics-has-changed-in-the-last-10-years-and-how-its-stayed-the-same
Sun, G.D., Liang, R.H., Lin, S.X.: A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges. J. Comput. Sci. Technol. 28(5), 852–867 (2013). https://doi.org/10.1007/s11390-013-1383-8. http://www.shixialiu.com/publications/VASTSurvey/paper.pdf
Scudellari, M.: The human brain project reboots: a search engine for the brain is in sight. IEEE Spectr. (2017). http://spectrum.ieee.org/computing/hardware/the-human-brain-project-reboots-a-search-engine-for-the-brain-is-in-sight, https://en.wikipedia.org/wiki/Human_Brain_Project, https://forbetterscience.com/2017/02/22/human-brain-project-bureaucratic-success-despite-scientific-failure/
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 The Author(s)
About this chapter
Cite this chapter
Earnshaw, R. (2018). Visual Analytics and Big Data. In: Research and Development in Digital Media. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-73080-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-73080-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73079-0
Online ISBN: 978-3-319-73080-6
eBook Packages: Computer ScienceComputer Science (R0)