Jupyter Hub deployments¶
General Principles¶
We have foreseen to develop 3 distinct end-user facing apps.
- a generic data-explorer - including an open browse/find UI and a found sample visualiser.
- (demonstrator) Bioprospecting Service
- (demonstrator) Ecological Strategies Service
In order to get these applications actually developed and deployed this analysis will tackle defining them together with their expected ins and outs. The content and goal of this work is therefore:
- To allow briefing the developers of the applications itself on the expected usage scenario’s that typical actors will walk through to achieve what specific outcomes.
- To list and priorities actual features and expectations.
As this this should give the engineering / development team
- a clear view that inspires the design of what they should build, and which reusable components that should be made of.
- a guide to create and finetune the data-provisioning layer: i.e. the mix of (1) organised data-management, the supporting (2) discovery-, subsetting- and caching- services and (3) access-libraries that enable transparent and efficient access to the dataframes that feed these apps.