Data science and visualization

For advanced raw materials exploration and characterization, we combine and analyze big data captured by different sensors and remote sensing platforms. To extract the valuable insights hidden in data that vary greatly in space, time, and material property information, we develop new processing workflows using data science. For that, we deploy amongst others various machine learning techniques in crucial tasks such as data fusion, image resolution enhancement, mapping geometric and compositional features in both 2D images and 3D space, and by conducting time series analysis. The latter proves invaluable in understanding the root causes behind systemic patterns that evolve over time. 

Visualization plays a crucial role in data-driven decision-making as it allows us to quickly identify trends. Amongst others, we work on the visualization of real-time data captured, for example, during hyperspectral drill core scanning. Drill core data can also be combined with so-called 3D hyperspectral point clouds (digital 3D datasets) of outcrops in open pits and underground mines to generate 3D geological models. These accurately represent materials properties and spatial relationships of objects in all three dimensions. 3D models aid to identify potential resource deposits, optimize exploration efforts, and enable precise resource management strategies. In doing so, 3D models serve as valuable tools for collaboration and communication, allowing stakeholders to interact with the data in an immersive and intuitive manner.