Visualization of Online Datasets

Peng, Taoxin; Downie, Christopher

Abstract

As computing technology advances, computers are being used to orchestrate and advance wide spectrums of commercial and personal life, an element even more significant as we immerse ourselves into the era of big data, leading to an economy heavily reliant on data mining and precise, meaningful visualizations. However, accuracy of information visualization techniques is heavily dependent on the knowledge and capabilities of the user, leaving novices in many fields at a disadvantage. This is a challenging problem that has been inadequately addressed regardless of the influx in visualization tools. Therefore, this paper proposes a novel approach with a focus on online datasets, allowing for the user to automatically and accurately visualize datasets. Using a browser extension and specially created HTML tables containing custom attributes - stating the data attribute type - the extension is able to detect and present the most suitable visualizations at the click of a mouse. This proposed approach provides a means for novices to quickly and accurately visualize online datasets.

Citation

Peng, T., & Downie, C. (2017, June). Visualization of Online Datasets. Presented at 2017 15th IEEE/ACIS International Conference on Software Engineering Research, Management and Application (SERA)

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2017 15th IEEE/ACIS International Conference on Software Engineering Research, Management and Application (SERA)
• Start Date: Jun 7, 2017
• End Date: Jun 9, 2017
• Acceptance Date: Apr 3, 2017
• Online Publication Date: Jun 7, 2017
• Publication Date: Jun 9, 2017
• Deposit Date: Sep 25, 2017
• Publicly Available Date: Sep 25, 2017
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 239-246
• Book Title: Proceedings of 15th IEEE/ACIS International Conference on Software Engineering Research, Management and Application (SERA)
• ISBN: 978-1-5090-5755-9
• Keywords: Online datasets, Visualization, Browser Extensions, Data transformation, HTML
• Public URL: http://researchrepository.napier.ac.uk/Output/947273
• Contract Date: Sep 25, 2017