Describing in-depth support projects
The project produced GIS-based maps and diagrams to visualize archaeological sites and material culture, highlighting the regional shift from hunting-gathering to farming. It integrates environmental and archaeological data to show patterns of human–environment interaction across multiple case study areas and their chronological development.
The goal of this project was to introduce synthetic demographic data to a public audience through an extension of the existing “Sweden-in-Numbers” installation.
This project developed a specialized 3D visualization tool to explore how halogen crystal structures transform under extreme pressure, particularly focusing on incommensurately modulated structures that emerge during molecular dissociation. By enabling interactive visualization of complex atomic configurations and transitions, the tool helps researchers interpret structural phase changes that are otherwise difficult to analyze using conventional crystallographic methods.
This project explores ways of visualizing data concerning the literacy metrics of elementary school children in Sweden, collected using a sophisticated tool developed for this very purpose.
Plastic pollution has emerged as a significant environmental concern, drawing increasing attention from the public and government agencies. In recent years, the presence of microplastics in aquatic and terrestrial ecosystems worldwide has become a critical focus of concern.
The project aims to develop and scale up new methods and solutions for 3D-visualization of invisible data (air, sound, and social consequences)
Diabetes is a long-lasting health condition with serious complications. We studied a new group of rats with a specific genetic mutation linked to diabetes. Regardless of their gender and blood sugar levels, these rats were overweight and had larger livers, hearts, and kidneys compared to normal rats. A study of the size of Bowmans space (difference between outer perimeter and Tuft of their glomeruli) can reveal tendencies toward having or developing cancer. In that respect advanced machine learning approaches are used to automatically segment and evaluate 3D volumetric information of many of the structures found within the tomography scans collected.
Initially an InfraVis pilot project, the VR lab at LTH has worked with Sridhar Halali, a researcher at the LU Dept. of Biology. As part of his work to understand how butterflies have evolved in response to environmental changes, Dr Halali has collected a dataset of microCT scans of butterflies. The specific trait of interest is in this case the shape of the head. It can, however, be a greatly time-consuming task to isolate body segments in a large 3-dimensional dataset using the 2D interface of the standard software (3D Slicer). This is where the VR Lab comes in, analyzing the problem, building on existing plugins for visualization and interaction in VR, and parallel processing to implement a solution to facilitate the task.
Monitoring of Wooden houses: Time series of sensors data measuring
humidity, temperatures, vibrations and weather conditions.
This project aim to demonstrate the availability of a long-term record of biodiversity data which could be used to understand the biodiversity implications of the current climate and extinction crisis. The visualisation can lead to a discussion about the regulations for sound environments, and to the initiation of new research questions about health effects.
