Web-based interface for data visualization
Abstract: In the age of Big data and exponential digitalization, data visualization is becoming a ubiquitous tool to understand trends, patterns and identify deviations that better help in decision making. The purpose of this thesis is to explore how a scalable data visualization interface can be designed with the open-source web library D3.js. The interface is designed to display a range of patients’ physiological measurements to help healthcare professionals with Covid-19 diagnosis. Several prerequisites were identified through a qualitative study, which proved to alleviate the implementation process, such as choosing a robust model that can support visualizations despite discontinuous and incomplete datasets. Since faulty visualizations may lead to potential harm in the highly sensitive medical setting, a dedicated risk analysis was deemed beneficial and thus formulated. The design of the interface also revealed functionality that could be considered when implementing any visualization interface, such as the rendering of different views and features that can further assist the user in interpreting the visualizations.
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