InfraVis’s main activity towards the public is supporting researchers in the form of projects, specifically supporting them with visualization skills, experience, and knowledge. Depending on the scope of those projects, they may be classified as one out of two different classifications.
Mid-level Projects
This classification is given to projects that are evaluated to take no more than a set amount of time (currently set to ~80 hours of involvement from our end). In most cases for these kinds of projects, the path towards the end goal is clear enough for us, that the time needed is mostly spent on getting a working viable prototype according to specifications up and running. Any eventual questions that may spring up in projects such as these are usually in the realms of what the researcher prefers specifically or domain-specific knowledge.
This level of support is given free of charge.
Dynamically Visualizing high-dimensional datasets using parallel coordinates plot
Producing and Rendering a 3D Mesh of Cassida Viridis – Green Tortoise Beetle
Visualizing Buzz Pollination
In-Depth Projects
For projects that are much larger in scope, and it is not feasible to have it done within the set amount of time for a Mid-Level project, we give the In-Depth classification. The common denominator for these projects, other than taking a large amount of hours, is that it is not exactly clear how the desired output for the project will be achieved. It may take more than a few iterations and evaluations from the researcher(s) and possibly their own users. In the more extreme cases, it may involve inventing new methods for visualization entirely.
Due to the grand nature of these projects, this level of support involves contributing in the form of user fees or in-kind contributions.
Visualizing Literacy of Children in School
Utopia web app: Study Microplastics Fate And Transport On A Global Scale
MiljöVis II & MålVis 2022 – 2024
Segmenting Glomeruli and other structures from synchrotron X-ray microtomography datasets
Butterflies in Virtual Reality: developing workflows for efficient morphological segmentation and analysis of X-ray microtomography Datasets
The pulse of the wood
