Design & development of a digital platform for research data

Abstract

In modern society, data collection and storage has become a significant factor for many businesses and the healthcare system. It is being used in endless amounts of researches as well as for diagnostics and preventative care. This project serves a study that strives to find ways to cure motion sickness. That study needs a platform to store its data and for advertising purposes in order to receive more participants. This project aims to find the best way to store and present that data both for research purposes and to appeal to the general public. The study has recorded over 110 subjects so for the scope of this project a smaller cohort of 45 female athletes was used, where 19 of those women had suffered a concussion. The purpose of this cohort is to examine whether physiological measurements can indicate if an individual has suffered a concussion or not. As this data contains sensitive information, a safe way of storage is necessary to avoid the data being personally identifiable. Additionally, this data is complex and not easily understood by the general public, so a simplistic presentation of the data is desired. This project concludes that a structured database management system with strict access control is an ideal way of storing this data. When it comes to visualising the data, the results show that the needs are very different for research purposes and advertising purposes. For research purposes, all data should be available, but it needs proper execution to avoid misinterpretation or loss of important parameters. However, to appeal to the general public, the data needs to be displayed aesthetically and simply, otherwise the general public’s interest is easily lost. In addition, the general public should not have access to all of the data and should not be able to reconstruct the entire database from the results shown. These conclusions have been reached through the design and development of the digital platform, and through user testing with ten participants. The main contribution of this thesis consists of three lessons learned which others can use when designing a digital platform for sensitive research data containing biosignals. These three lessons are to store this kind of data in a structured database management system, with strict access control to ensure privacy and lastly to visualize the data correctly.