EVALUATING INTERACTIVE VISUALIZATION TECHNIQUES ON SMALL TOUCH SCREEN DEVICES

Published 31 Dec 2019 •  vol 12  •  no 2  • 


Authors:

 

Muzammil Khan, Department of Computer & Software Technology, University of Swat, Pakistan
Sarwar Shah Khan, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
Kifayat Ullah, Department of Computer & Software Technology, University of Swat, Pakistan
Ghufran Ullah, Department of Computer Science, City University of Science & IT, Pakistan

Abstract:

 

The purpose of the study is to introduce interactive mechanisms for information visualization techniques, which will assist the nomadic users in exploring information on small touch screen mobile devices like smartphones and tablets, on the move. The study is carried out by choosing the Posttest-Only Randomized Experimental research design and evaluated by using a questionnaire-based control experiment. The participants were asked to execute several tasks based on experiments on a functional prototype and fill the feature-based questionnaire. The study introduced six interactive visualization techniques to visualize information in a way that conveys the insight of the data effectively. The results indicate that Drill down approach in column chart (DDA+CC) and Legend navigation approach in column chart (LNA+CC) shows the reliable results and facilitate information manipulation on small screens of mobile devices, Drill down approach in bar chart (DDA+BC) and Legend navigation approach in bar chart (LNA+BC) shows weak results for Smartphones, the interactive visualization techniques DDA+LNA+CC and DDA+LNA+BC are highly appreciated for mobile devices, that are for both Smartphones and Tablets.

Keywords:

 

Data mining result’s interactivity, Drill down interactive visualization technique, Legend navigation interaction, Mobile device visualization interactivity

References:

 

[1] Alan Bryman. "The debate about quantitative and qualitative research: a question of method or epistemology?" British Journal of Sociology, 1984, pages 75–92.
[2] Carmela Comito and Domenico Talia. "Energy consumption of data mining algorithms on mobile phones: Evaluation and prediction". Pervasive and Mobile Computing, 2017, Vol. 42, pages 248–264.
[3] D Dacunha-Castelle. "Vedas: A mobile and distributed data stream mining system for real-time vehicle monitoring". 2004.
[4] Ashutosh K Dubey and Shishir K Shandilya. "Exploiting need of data mining services in mobile computing environments". In Computational Intelligence and Communication Networks (CICN), 2010 International Conference on, 2010, pages 409–414. IEEE.
[5] Gregory J Feist and Erika L Rosenberg. "Psychology: perspectives & connections", 2012 pages 12–08.
[6] Rosemary R Gliem and Joseph A Gliem. "Calculating, interpreting, and reporting Cronbach's alpha reliability coefficient for Likert-type scales". Midwest Research-to-Practice Conference in Adult, Continuing, and Community Education. 2003.
[7] Jiawei Han, Jian Pei, and Micheline Kamber. Data mining: concepts and techniques. 2011, Elsevier.
[8] Nitin Jindal and Bing Liu. "Opinion spam and analysis". In Proceedings of the 2008 International Conference on WebSearch and Data Mining, 2008, pages 219–230, ACM.
[9] Hillol Kargupta, Byung-Hoon Park, Sweta Pittie, Lei Liu, Deepali Kushraj, and Kakali Sarkar "Mobimine: Monitoring the stock market from a PDA". ACM SIGKDD Explorations Newsletter, 2002, 3(2) pages 37–46.
[10] Muzammil Khan. "Interactive Data Mining Results Visualization on Mobile Devices". ISBN 978-3-659-46354-9, 2013, LAP USA.
[11] Muzammil Khan, Fida Hussain, and Imran Khan. "Single level drill down interactive visualization technique for descriptive data mining results". International Journal of Grid and Distributed Computing, 2014, 7(4) Pages 33–40.
[12] Muzammil Khan and Sarwar Shah Khan. "Data and information visualization methods, and interactive mechanisms: A survey". International Journal of Computer Applications, 2011, 34(1) Pages 1–14.
[13] Muzammil Khan, Sarwar Shah Khan, and M Daud. "Comparative exploration of data mining results by legend navigation interactive technique". International Journal of Database Theory and Application. 2016, 9(9) Pages 49–58.
[14] Muzammil Khan, Ali Shah, and Israr Ahmad. "Framework for interactive data mining results visualization on mobile devices". International Journal of Database Theory and Application, 2014, 7(4) Pages 23–36.
[15] Ricardo Langner, Tom Horak, and Raimund Dachselt. "Vistiles: Coordinating and combining co-located mobile devices for visual data exploration". IEEE transactions on visualization and computer graphics, 2018, 24(1) Pages 626–636.
[16] Riccardo Mazza and Alessandra Berre. "Focus group methodology for evaluating information visualization techniques and tools". In Information Visualization, 2007. IV’07.11th International Conference, 2007, pages 74–80, IEEE.
[17] Sweta Pittie, Hillol Kargupta, and ByungHoon Park. "Dependency detection in mobimine: a systems perspective. Information Sciences, 2013, 155(3), Pages 227–243.
[18] Calvin Fisher Schmid and Calvin Fisher Schmid. "Statistical graphics; design principles and practices". Technical report, 1983.
[19] Hansi Senaratne, Manuel Mueller, Michael Behrisch, Felipe Lalanne, Javier BustosJim´enez, J¨orn Schneidewind, Daniel Keim, and Tobias Schreck. "Urban mobility analysis with mobile network data: A visual analytics approach". IEEE Transactions on Intelligent Transportation Systems, 2018, 19(5), Pages 1537–1546.
[20] Roberto Sousa, Valentina Nisi, and Ian Oakley. "Glaze: A visualization framework for mobile devices". In IFIP Conference on Human-Computer Interaction, 2009, pages 870–873. Springer.
[21] Frederic Stahl, Mohamed Medhat Gaber, Max Bramer, and S Yu Philip. "Pocket data mining: towards collaborative data mining in mobile computing environments". In 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010, volume 2, pages 323–330. IEEE.
[22] Frederic Stahl, Mohamed Medhat Gaber, Max Bramer, and S Yu Philip. "Distributed hoeffding trees for pocket data mining". In High-Performance Computing and Simulation (HPCS), 2011 International Conference on, 2011, pages 686–692. IEEE.
[23] Frederic Stahl, Mohamed Medhat Gaber, Han Liu, Max Bramer, and S Yu Philip. "Distributed classification for pocket data mining". In International Symposium on Methodologies for Intelligent Systems, 2011, pages 336–345, Springer.
[24] Domenico Talia, Paolo Trunfio, et al "Mobile data mining on small devices through web services". Mobile Intelligence, 2010, Pages 69- 64.
[25] Lex Van Velsen, Thea Van Der Geest, Rob Klaassen, and Michael Steehouder. "User-centered evaluation of adaptive and adaptable systems: a literature review". The knowledge engineering review, 2008, 23(03) Pages 261–281.
[26] Igor Vasconcelos, Rafael Oliveira Vasconcelos, Bruno Olivieri, Marcos Roriz, Markus Endler, and Methanias Cola¸co Junior. "Smartphone-based outlier detection: a complex event processing approach for driving behavior detection". Journal of Internet Services and Applications, 2017, 8(1) Pages 13.
[27] Frank Wang, Nu Helian, Y Guo, and Hai Jin. "A distributed and mobile data mining system". In Parallel and Distributed Computing, Applications and Technologies. PDCAT’2003. Proceedings of the Fourth International Conference on, 2003, pages 916–918. IEEE.

Citations:

 

APA:
Khan, M., Khan, S. S., Ullah, K., & Ullah, G. (2019). Evaluating Interactive Visualization Techniques on Small Touch Screen Devices. International Journal of Grid and Distributed Computing (IJGDC), ISSN: 2005-4262 (Print); 2207-6379 (Online), NADIA, 12(2), 31-48. doi: 10.33832/ijgdc.2019.12.2.03.

MLA:
Khan, Muzammil, et al. “Evaluating Interactive Visualization Techniques on Small Touch Screen Devices.” International Journal of Grid and Distributed Computing (IJGDC), ISSN: 2005-4262 (Print); 2207-6379 (Online), NADIA, vol. 12, no. 2, 2019, pp. 31-48. IJGDC, http://article.nadiapub.com/IJGDC/vol12_no2/3.html.

IEEE:
[1] M. Khan, S. S. Khan, K. Ullah, and G. Ullah, "Evaluating Interactive Visualization Techniques on Small Touch Screen Devices." International Journal of Grid and Distributed Computing (IJGDC), ISSN: 2005-4262 (Print); 2207-6379 (Online), NADIA, vol. 12, no. 2, pp. 31-48, Dec 2019.