19 Aug 3D Scientific Dataset Wanted for International Data Visualization Contest
19 August 2020
Compute Canada is seeking a 3D scientific dataset to use for an international data visualization contest Compute Canada is co-hosting with IEEE. The annual SciVis Contest is dedicated to create novel approaches or state of the art visualizations. Preliminary details of the 2021 SciVis Contest can be viewed here.
Call for datasets
If you have a dataset or if you have recently worked with a researcher who you think might have a suitable dataset for this contest, please contact us. The deadline for submissions is Monday, August 31. Ideal datasets will fit the following criteria:
- The dataset must be unrestricted, public release without any IP issues.
- The dataset should be sufficiently challenging and potentially lead to a beautiful visualization, but easy to understand for non-domain specialists.
- The dataset cannot be too large. Contest participants should not require HPC resources to analyze/visualize it. A time-dependent simulation where each timestep is under ~4-8 GB will be considered.
- Ideally it is from a domain different from the last few IEEE SciVis contests.
Benefits to contributing a dataset
There are a number of benefits for domain scientists who contribute a dataset to this competition:
- An opportunity to showcase your work in Canada and internationally:
- the 2021 challenge (featuring your dataset!) will be launched at the IEEE Vis Conference 2020 in October 2020 (online – date TBC),
- the dataset will be described on the SciVis Contest website and the websites of Compute Canada and its regional partners (WestGrid, Compute Ontario, Calcul Québec, ACENET),
- there will be a separate session at IEEE Vis 2021 (October next year) dedicated to the results of the contest, and the winner will be invited to submit a paper on their visualization technique to IEEE Computer Graphics and Applications (see the 2019 paper here).
- You will have someone create a stunning visualization of your research.
- This is a chance to crowdsource innovative visualization ideas and to apply new visualization techniques to your data.
If your contribution is selected for the SciVis Contest, we’ll request some background material in addition to the dataset (i.e. how to work with the data and a problem description), which will help us define the visualization-related tasks, and also help in judging submissions.