Understanding sensor data with uncertainty using a visual representation

Sensor technologies have been broadly adapted to measure the physical aspects of different environmental phenomena. A major difficulty arising from the adoption of sensor technologies is that sensors generate enormous amounts of data on a daily basis, often surpassing what conventional systems can accommodate. Therefore, there is an escalating need for scientists to effectively manage the increasing volume of data and accurately analyze and understand the phenomena. In this paper, we propose a new visual approach to representing the sensor data with emphasizing the uncertainty of information in the dataset.