Abstract
Large volumetric neuroimaging datasets have grown in size over the past ten years from gigabytes to terabytes, with petascale data becoming available and more common over the next few years. Current approaches to store and analyze these emerging datasets are insufficient in their ability to scale in both cost-effectiveness and performance. Additionally, enabling large-scale processing and annotation is critical as these data grow too large for manual inspection. We provide a new cloud-native managed service for large and multi-modal experiments, with support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API) and web-based user interface. Our project is open source and can be easily and cost-effectively used for a variety of modalities and applications.
Footnotes
Updates to experiments and prose to reflect lessons learned ingesting, managing, and sharing terascale and petascale datasets.
