OSCARS: FAIR Image Analysis Across Sciences
Imaging techniques have become increasingly popular across scientific fields due to their ability to provide rich and comprehensive information. These images, image series, and videos are invaluable resources, offering researchers a wealth of information to explore and analyse. Despite the widespread use of imaging, the practice of extracting quantitative information from image data remains fragmented across scientific communities. Scientists often work in isolated silos, resulting in limited cross-talk and collaboration. This isolation can lead to redundant work and inefficient resource utilisation, as experts in different domains may duplicate efforts unknowingly. The rise of AI and machine learning further complicates this landscape, with access to the necessary tools and computational resources becoming a significant bottleneck for researchers.
The "FAIR Image Analysis Across Sciences" project addresses these challenges by developing reusable image analysis workflows that can be shared across disciplines such as bioimaging, environmental sciences, and astrophysics.
FAIR Image Analysis Across Sciences News
