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DataSHIELD Road map

DataSHIELD Road map

16 Jul, 2020

This road map is the outcome of the collaboration between Stuart Wheater, Demetris Avraam, Paul Burton, Alex Westerberg, Leire Abbarategui, Olly Butters, Becca Wilson and Patricia Ryser-Welch. It shows planned development and timeline of DataSHIELD architecture and functionalities.

We have included satellite activities to demonstrates our commitments to the sustainability of the project as well as our commitments to develop further DataSHIELD as a community of developers, analysts and data scientists.  

Jan2020FebMarAprMayJunJulAugSepOctNovDecJan2021FebMarAprMayJunJulAugSepOctNovDecJan2022FebMarAprMayJunJulAugSepOctNovDecDS conference 2021
Releases
Testing and maintaining quality
Doc. / training res.
Govervance
Infrastructure
User Interaction
Omics
Machine learning
Non-param. statistics
Visualisation
Data governance
Data

Prepare v5.0

v6.0 - DSI compatibility

v6.1

Update training material

Prepare v5.1

v6.2

v6.3

v6.4

v7 - Explainable and interpretatable IA -virtually-joined and server-level analysis

Develop testing framework

Continuous integration and monitoring with new updates and software technologies

Write training material

New Bar

Testing v6.0

Testing v.6.1

Testing v6.2

Testing v6.3

Testing v6.4

Testing v7.0

v6.1 documentation

v6.0 training material update

v6.2 documentation

v6.4 documentation

v6.3 Documentation

Improving DataSHIELD Analyst document and teaching material

Documentating and developing training material for v7.0

Initiate steering committee - Paul Burton and Andrei Morgan

First steering committee focus on governance and future of the project

Developers collaboration

Steering committee governance

Developers collaboration

Steering committee governance and future functionality

Developers planning development of v.7

Steering committee source of funding and long term planning

Developers monitoring of version 7 development

Engaging with users for release functionality

Engaging with users for release of functionality

Engaging with users for release functionality

Engaging with users for additional functionality

Engaging with users for release functionality

Training and workshop needs

Training and workshop review

Training a workshop review

Statistical methodologies and ML review

Statistical methodologies and ML review

Statistical methodologies and ML review

Develop DS Resources (Back end)

Server reporting, monitoring, benchmarks

Develop and implement containerisation

Integration on the DataSHIELD server of well-established R libraries

Development tools to integrate DS results with institutions systems (Front end)

Defining user interaction needs - with UI department Newcastle University

Develop GUI

Reduce learning curve for DataSHIELD analysts and wider scientific audience (passing results)

Develop dsOmics with IS Global

Medical Faculty Newcastle University - deploying DataSHIELD Fatty liver dataset to other scientists

Working toward release with IS Global

Further development of Fatty liver datasets

DataSHIELD using Bioconductor - IS Global and DataSHIELD core team

Integration and development machine learning imaging techniques

AI: hyper-parametrisation of ML algorithms for virtually-joined analysis and server-level tools

AI: integration of ML techniques to prevent individual-level disclosure

Proof of concepts

Development

Development of non-disclosive graphs using R libraries

Proof of concepts

Review of proof of concepts

Development

Synthetic data generation and validation with DataSHIELD server