Data integration across silos

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Biological sciences are building new and improved ways of capturing biological systems. The rate of image acquisition has increased rapidly due to automated image acquisition and phenotyping. This creates a huge bottleneck for annotation and just finding images. Most imaging techniques are expensive both in time and cost but large silos of images with minimal or poorly labeled metadata lie ‘rotting’ on servers never to see the light of day.

The increasing interest in machine learning to look for biomarkers for early prediction of the disease will mean utilizing these unused archives will become increasingly important. Other industries like Gardens, Libraries and Museums (GLAM) are increasingly digitizing their collections, there is an opportunity for Zegami to replace traditional Digital Asset Management systems.