Synthetic Data Generator (White Stork)

Epic Type: Exploratory Epic

The goal is to create a prototype.

Principle Components of Exploration:

Metadata generator based on GHGA model
- Controlled vocabulary for CV fields
- (Random but realistic) Value in non-CV data fields following right data type
- Dataset generator
- Submission JSON model
- Post creation json model
- Data model multiplicities
- Connectivity of the classes
- Realistic file name and size
FASTQ file generator
- Employ dummy_data_generator
- Storage space requirements (platform selection: ABI cluster or de.NBI)
Connection between metadata and file generators for file related parameters
Run time - Not a focus on the performance, but aim for reasonable

User Journeys

This epic covers the following user journeys:

User reguests both metadata and correspoding files

User requests only metadata

User requests only fastq files

Human Resource/Time Estimation:

Number of sprints required: 3

Number of developers required: 1