Morphing rivers - innovating water quality visualisation

Primary supervisor

Sarah Goodwin

Co-supervisors

  • Anna Linten / Engineering

This project seeks to explore and trial new map morphing representations for seeing river water quality data sets more effectively over time and space. 

We are particularly focusing on the Melbourne and the region of Victoria, but expect the visualisation to be applicable to any geographical region.  

Water quality data is usually mapped as points on a river, with the most recent data presented. We want to make this information more salient and easier for decision-making (for example to identify sections of the river that fluctuation in quality over season) by changing the representation so that spatial location is abstracted and we can see the temporal dataset in one view.

We will working with water engineers and hydrologists and organisations like Melbourne Water to design and define visualisation requirements and later to evaluate the developed solution with them.

We seek to develop an effective alternative representation to a standard interactive map that retains the spatial information but provides a rich overview for more informed decision making. 

This project is influenced by our work on map morphing, abstraction and interaction to encourage more informed data interpretation and data exploration. 

Aim/outline

As a thesis student you will explore the literature, help design the new visualisation, iterate on possibilities, implement the new visualisation and evaluate it against more traditional alternatives to judge its effectiveness for reading and comprehending the data. 

This project is suggested to be 2D web browser visual work for an expanded audience. There is potential for continuation within the immersive environment in future research. You will work independently but in collaboration with relevant personnel at Monash and externally to ensure the ideas are effective and research is robust. 

Required knowledge

Honours or Minor thesis project.

You will need to have demonstrated proficiency in programming, JavaScript ideally and ability to work with geospatial vector datasets, and good mathematical skills.

Should have completed a data visualisation unit such as FIT3179 or FIT5147 or be able to show demonstrated understanding of data visualisation design principles. (completing in parallel to S1 thesis may suffice)

Data visualisation design skills and water quality or environmental knowledge a plus.