5. PROPUESTA DE UN MODELO DE ARQUITECTURA EMPRESARIAL
5.1 PROPUESTA DE UN ENFOqUE DE ARqUITECTURA DE SOLUCIóN
The aim of this research project was to determine the usability and learn-ability of an interactive WebVR system for data visualization. Alternatively, the system was also built so that it can run on a Mac or PC’s Google Chrome browser. This project used the Samsung Galaxy S8 as the VR device and the VR Box along with Bluetooth controller as the equipment for viewing and interaction. The whole design process began with creation of sketches on a notebook and then creating the pro- totype for a multi-dimensional data-set. The data-set was collected from an online repository called UCI Machine Learning Repository [18]. The prototype underwent several iterations until the 3D scatter plot was finalized. This project used a WebVR framework called A-frame for creating the virtual reality scene and D3.js for plotting the data points in a 3D environment. A new user interface was also developed for interacting with the application. The VR Box and the Bluetooth controller were the most accessible and cost-effective equipment available in the market at the moment. One of the main reasons for bringing this application into the WebVR environment was due to its high accessibility and maintainability.
8.1 Limitations and Future Discussion
For WebVR applications, performance always plays a vital role in providing the best experience to the user. And a lot of it has to do with maintaining a high frame- rate which was one of the main limitations that this project encountered. Also, this project used cubes instead of other shapes such as a sphere or cylinder because cubes have the least number of sub divisions (polygon count) which also affects the overall performance. This project was tested with the latest android phone i.e. the
company called Looker. They created their own custom APIs and are using the HTC Vive as the virtual reality device [5]. This corroborates that WebVR although in its experimental phase is already becoming one of the popular technologies to emerge in recent times due to its wide array of applications and high compatibility across many domains.
In the near future, this project hopes that it can provide sufficient information in creating a visualization platform that can have different graphs and data-sets in a WebVR setting for smart-phones where data changes can be seen in real time and implemented across various domains. Since the processing power of smart-phones are increasing at a rapid pace, they may potentially become one of the competing medi- ums for visualizing and analyzing multi-dimensional data in future. This could also means providing more interaction with data-points using innovative input technology such as hand gloves or 3D mouse. If smart-phones are utilized in an effective manner for visualization, it could potentially become a viable option in the field of technology and science which is highly portable, accessible and affordable as well as at the same time it could also provide a gateway for interdisciplinary research and applications.
Bibliography
[1] Aframe best practices. URL https://aframe.io/docs/0.5.0/introduction/ best-practices.html.
[2] Steps in the data analysis process. URL http://www.bcps.org/offices/lis/ researchcourse/data process.html.
[3] All ux evaluation methods. URL http://www.allaboutux.org/all-methods. [4] Applications of virtual reality. URL https://www.vrs.org.uk/virtual-
reality-applications/.
[5] Data analytics in virtual reality because why not?, February 2017. URL https://info.looker.com/youtube-product/data-analytics-in-virtual- reality-because-why-not.
[6] R. L. Adams. Five reasons why virtual reality is a game-changer, March 2016. URL http://www.forbes.com/sites/robertadams/2016/03/21/ 5-reasons-why-virtual-reality-is-a-game-changer/#3de0e9e06d78. [7] J. Allen and J. Chudley. Smashing UX Design: Foundations for Designing
Online User Experiences. Smashing magazine book series. Wiley, 2012. ISBN 9780470970621. URL https://books.google.com/books?id=b1Ga 0p1zIUC. [8] C. Donalek, S. G. Djorgovski, S. Davidoff, A. Cioc, A. Wang, G. Longo, J. S.
Norris, J. Zhang, E. Lawler, S. Yeh, A. Mahabal, M. J. Graham, and A. J. Drake. Immersive and collaborative data visualization using virtual reality platforms. CoRR, abs/1410.7670, 2014. URL http://arxiv.org/abs/1410.7670.
[9] S. Galbraith. Google analytics. Journal of the Canadian Health Li- braries Association / Journal de l’Association des bibliothques de la sant du Canada, 34(2):119–122, 2014. doi: 10.5596/c13-022. URL https://journals.library.ualberta.ca/jchla/index.php/jchla/article/ view/22651.
[10] C. Hall and E. Betters. Best vr headsets to buy in 2017, whatever your bud- get, January 2017. URL http://www.pocket-lint.com/news/132945-best-vr- headsets-to-buy-in-2017-whatever-your-budget.
[13] C. Josh. Quick vr prototypes, DECEMBER 2014. URL https:// blog.mozvr.com/quick-vr-prototypes/.
[14] J. Kirakowski and M. Corbett. SUMI: the Software Usability Measurement In- ventory. British Journal of Educational Technology, 24(3):210–212, 1993. ISSN 1467-8535. doi: 10.1111/j.1467-8535.1993.tb00076.x. URL http://dx.doi.org/ 10.1111/j.1467-8535.1993.tb00076.x.
[15] C. Laura. The ux of vr, March 2016. URL http://www.creativebloq.com/ux/ the-user-experience-of-virtual-reality-31619635.
[16] H. Le, A. Joshi, and M. Betke. b3.js: A library for interactive web data visual- izations in virtual reality. 2016.
[17] J. A. Lee and M. Verleysen. Nonlinear Dimensionality Reduction. Springer Publishing Company, Incorporated, 1st edition, 2007. ISBN 0387393501, 9780387393506.
[18] M. Lichman. UCI machine learning repository, 2013. URL http:// archive.ics.uci.edu/ml.
[19] R. Margaret. multidimensional database (mdb), September 2005. URL http: //searchoracle.techtarget.com/definition/multidimensional-database.
[20] R. Margaret. Big data, July 2014. URL http://
searchcloudcomputing.techtarget.com/definition/big-data-Big-Data. [21] D. Mccurdy. Gamepad. URL https://github.com/donmccurdy/aframe-
gamepad-controls.
[22] A. Moran, V. Gadepally, M. Hubbell, and J. Kepner. Improving big data visual analytics with interactive virtual reality. CoRR, abs/1506.08754, 2015. URL http://arxiv.org/abs/1506.08754.
[23] J. Nielsen and T. K. Landauer. A mathematical model of the finding of usability problems. In Proceedings of the INTERACT ’93 and CHI ’93 Conference on Human Factors in Computing Systems, CHI ’93, pages 206–213, New York, NY, USA, 1993. ACM. ISBN 0-89791-575-5. doi: 10.1145/169059.169166. URL http://doi.acm.org/10.1145/169059.169166.
[24] O. Rist and D. Strom. Looker, June 2016. URL http://www.pcmag.com/ article2/0,2817,2495564,00.asp.
[25] J. Rubin. Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests. John Wiley & Sons, Inc., New York, NY, USA, 1st edition, 1994. ISBN 0471594032, 9780471594031.
[26] P. C. S. Moro and P. Rita. A data-driven approach to predict the success of bank telemarketing. Decision Support Systems Elsevier, 62:22–31, jun 2014. URL http://archive.ics.uci.edu/ml/datasets/Bank+Marketing.
[27] P. Simon. Wiley and SAS Business Ser. : The Visual Organization : Data Visualization, Big Data, and the Quest for Better Decisions (1), chapter 1: The Ascent of the Visual Organization. John Wiley & Sons, Incorporated, February 2014. ISBN 9781118858417.
[28] J. Verhage. Goldman sachs has four charts showing the huge potential in virtual and augmented reality, January 2016. URL http://www.bloomberg.com/ news/articles/2016-01-13/goldman-sachs-has-four-charts-showing- the-huge-potential-in-virtual-and-augmented-reality.
[29] L. Wilkinson. The Grammar of Graphics (Statistics and Computing). Springer- Verlag New York, Inc., Secaucus, NJ, USA, 2005. ISBN 0387245448.
[30] A. Williams. Datahero turns data into rich visuals without the need for a data analyst, May 2013. URL https://techcrunch.com/2013/05/01/ datahero-turns-data-into-rich-visuals-without-the-need-for-a- data-analyst/.
[31] C. Wohlin, P. Runeson, M. Hst, M. C. Ohlsson, and B. Regnell. Experimentation in Software Engineering. Springer, 2012. ISBN 978-3-642-29043-5.