Fig. 1: There are at least three different categories of users of archived images, each with different needs with respect to metadata.

(1) Biologists and life scientists who are interested in repeating experiments, (re-)analyzing or comparing bioimage data and understanding results. For this, they need detailed information on the experimental context, such as the composition of biological samples, molecular entities, experimental interventions (for example, control vs. treatment) and how these relate to the image data. (2) Imaging scientists (microscopists and technology developers) who are interested in developing new imaging technologies. For this, they need detailed information on the image-acquisition process, such as physical properties of the image-acquisition set-up, and may benefit from some high-level information on the biological problem at hand. (3) Computer-vision researchers who develop algorithms (not limited to biological applications). Depending on the objective, they may need any of the information listed above. For example, to train a machine-learning algorithm, they would need ‘ground truth’ information such as adequately labeled images with categories (for example, control vs. treatments/phenotypes) or object outlines (segmentations).