IConIC data visualization
This data visualization for the IConIC project is a collaboration between myself, a communication designer and data scientists and engineers at the University of Portsmouth, to work with a consortium of companies in the marine industry around the Solent in South East England. The change to society affected here was economic and environmental: to add value to marine engineering services in order to retain market competitiveness, to comply with international standards to reduce fuel consumption and emission through innovation, and also to provide a better user experience through design. In particular, my role was to produce the design research for a user interface on board the ship to assist non-experts in monitoring engineering data. The design visualises sensor data taken from various engine components by utilising body schema like movement and rotation. Theoretically, this design approach draws on phenomenology, embodied cognition and metaphor.
For this project I worked with data scientists in order to make the data more widely engaging and accessible. The context is data taken from the marine and dairy industry, which is ultimately used to detect and predict faulty engine parts. The design aspect here is to provide a user-friendly interface, but involves much more than that.
To make sense of the data and make it accessible to a wider audience, the designer had to work closely with the data analyst to decide upon relevant parameters in the raw data, which then also determines the hierarchy of information on screen – i.e. questions of which information the user needs immediately, and which can be hidden in a different layer, can only be answered if the whole of the data collection and processing system is understood. In practice, the collaboration between the designer and the data scientists was crucial in determining an approach to visualize the data set and to develop the story that the data tells.
The challenge for the data visualization was to move beyond simple traffic light systems – as the data was processed through intelligent machine analysis, the key approach to the data science here is that a ‘healthiness’ score is generated, which contains more complexity than a threshold-based system, which could be dealt with through ‘on’ or ‘off’ states.
The design approach seeks to enhance understanding of the data, by letting users / the audience experience it in an embodied and also tactile way. Sample data, which represents healthy and faulty engine performance, has been visualized in a prototype user interface and translated into a vibrating display. These different ‘data materializations’ set out to problematize the human experience within the scientific process of data processing and representation.
This represents a healthy state of the engine, all parts operating optimally.
This represents a deterioration of the engine over time, where one part is starting to affect another - this will need investigating.
This data was also presented as a data materialization
The IConIC data visualization and materializations was presented as part of the exhibition ‘Between Craft and Code: Making Sense of Data Materialization'
