Back to the main README
- Introduction - this file
- Background_Concepts
- Understanding Analysis plans in a federated setting
- Containerising scripts
- Key Payloads
- Command Line - e.g. with
curl - Python
- R
A separate repository provides Worked examples
The main purpose of the Federated Data Sharing Common API is to support analysis of multiple data sets while allowing a data owner (custodian, controller) to control how data is exposed to the analysis. A set of APIs allow users to query metadata, select data and perform computation on data held remotely. This is intended to support a cycle where you can:
- get field-level type and content metadata for remote data
- define a selection (pick fields) or filter (pick rows) you want to analyse
- execute some computation on the selection
In Level 1 federated data sharing, you may have access to select row level data whereas in Level 2 you will only be able to specify your selection and computation task and have both executed remotely. This means that your analysis plan needs to adapt to the protocol.
Understand the Background concepts to enable you to use the API effectively.