2023 Visualize This! Contest: two datasets

Hosted by the Digital Research Alliance of Canada and its regional partners, and now in its 6th year, Visualize This! is a Canada-wide competition that aims to celebrate the innovative ways visualization can help researchers explore datasets and answer important scientific questions. Visualize This! is your chance to challenge your creativity, experiment with cutting-edge visualization tools, and contribute to the growth of data visualization in Canada!

In this year’s Contest you can work on one of the two datasets below. Both datasets contain geospatial data, one from a numerical simulation, and the other compiled from several empirical sources. To participate in the challenge, please register your interest – this will add you to the “Visualize This 2023” Google group where we will post all updates and announcements.

Dataset 1: Halloween storm over Eastern Canada

The research group of Alejandro Di Luca (Université du Québec à Montréal) provided the first dataset. The data come from a numerical simulation of a storm over Eastern Canada during Halloween 2019.

The animation below covers six days from October 31st to November 5th, 2019. The 3D volume features the distribution of clouds (white), rain (green to cyan), and ice crystals (yellow) in the atmosphere, whereas the 2D surface at the bottom shows the snow accumulation on the ground. The 3D variables are also displayed in the two projections, along the x- and y-axes, to highlight the relative vertical distribution of the three variables.

Figure 1: Distribution of clouds (white), rain (green to cyan), and ice crystals (yellow) over 6 days starting with the storm on October 31, 2019.

You can find more about this dataset here. The main challenge is to show the overlapping distributions of several 3D variables, ideally (but no necessarily!) in the same visualization.

Dataset 2: normalized difference vegetation index (NDVI)

The second dataset was provided by the research team of Michael Noonan (University of British Columbia at Okanagan). They compiled approximately one year of openly-available remotely sensed NDVI (normalized difference vegetation index) data at the global scale. NDVI is a measure of greenness, widely used to measure the ecosystem productivity. To limit the size of the dataset, here we provide data only for BC.

Figure 2: NDVI as a function of time for BC.

You can find more about this dataset here. This dataset is simpler than the first one, as it contains effectively only 2D data (that you can choose to view in 3D).

Contest webinar

Contest terms

Please only use open-source tools and libraries in the Contest, so that anyone can reproduce your solution without having to pay for commercial / proprietary tools. Two commonly used 3D visualization tools are ParaView and VisIt , but you are free to use any open-source package or library or any programming language – there are many tools readily available for visualizing these data. What you can do with these tools is really limited only by your imagination.

Your submission in the Contest (both images/movies and the workflow) will be published under a Creative Commons Attribution 4.0 International License.