Data visualization for distribution of people with disabilities

Zirawani Baharum

Abstract

Data visualizations make data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and styles in groups of data. With the development of the data visualization, more and more data which contains the information of disabled population has been collected. However, researchers have pointed out some problems with visualizing data especially using traditional methods. Therefore, this study aimed to develop a web-based system for data visualization of disabled people distribution in Kuala Selangor, Selangor, Malaysia. Prototyping methodology was chosen in order to develop the web-based system. The results show two main interfaces of the web system which are the admin module and user module. Users may see a specific area, type of disabled people categories and the number of disabled people in the located area from the Google Map. This web system is hope to help public in identifying disabled people location using data visualization technique. In addition, in future it could help the authorize institutions/bodies in doing better planning for disabled people education, facilities and other needs based on its location distribution. ? Published under licence by IOP Publishing Ltd.

References

Department of Statistics Malaysia. (2010). Taburan Penduduk Dan Ciri-Ciri Asas Demografi, Retrieved from www.scopus.com

Hoffman, S. (2017). Big Data and the Americans with Disabilities Act: Amending the Law to Cover Discrimination Based on Data-Driven Predictions of Future Illnesses, Retrieved from www.scopus.com

Lee, B., Choe, E. K., Isenberg, P., Marriott, K., & Stasko, J. (2020). Reaching broader audiences with data visualization. IEEE Computer Graphics and Applications, 40(2), 82-90. doi:10.1109/MCG.2020.2968244

McDermott, S., & Turk, M. A. (2015). What are the implications of the big data paradigm shift for disability and health? Disability and Health Journal, 8(3), 303-304. doi:10.1016/j.dhjo.2015.04.003

Nambisan, P., Kapoor, A., Patrick, T. B., & Cisler, R. A. (2015). 48th Hawaii International Conference on System Sciences Social Media, Big Data and Public Health Informatics: Ruminating Behavior of Depression Revealed through Twitter, , 2906-2913. Retrieved from www.scopus.com

Pan, Z., Ji, W., Chen, Y., Dai, L., & Zhang, J. (2018). Anomaly data management and big data analytics: An application on disability datasets. International Journal of Crowd Science, 2(2), 164-176. doi:10.1108/IJCS-09-2018-0020

Tongkaw, S. (2017). GIS Application Management for Disabled People International Research and Innovation Summit (IRIS2017), 226 Retrieved from www.scopus.com