Data science and AI are becoming ever more prevalent in the UK with common needs and challenges arising. Solving these challenges requires novel tools, practices and systems which can unlock advances across the wider sector and accelerate innovation.
The 'Tools, practices and systems' (TPS) programme at the Turing represents a cross-cutting set of initiatives which seek to build open source infrastructure that is accessible to all, and to empower a global, decentralised network of people who connect data with domain experts.
The programme will:
- Build trustworthy systems
- Embed transparent reporting practices
- Promote inclusive interoperable design
- Maintain ethical integrity
- Encourage respectful co-creation
TPS is closely aligned with the Research Engineering Group at the Turing.
Header image created by Scriberia for The Turing Way community and used under a CC-BY licence.
Develop open-source tools to accelerate innovation
Open-source toolkits represent a hugely valuable resource for a wide range of sectors and industries. TPS will work closely with developers, stakeholders and end-users to support the creation and maintenance of essential open-source software libraries. Key widely-used products supported by the TPS programme to date include a machine learning framework for the Julia programming language, and a toolbox for time series analysis in data science.
Establish practices for reproducible & reusable workflows
Effective science relies on reproducibility. TPS will continue to promote and embed practices which ensure that data science research is carried out in a reproducible way from inception to completion. The Turing Way guide for reproducible research is used around the world to ensure that published results can be interrogated and extended with ease.
Unlock innovation by optimising high-performance computing and secure data access
Secure infrastructure is essential for research and innovation that deals with high-sensitivity data. The Data Safe Haven initiated under TPS is now deployed around the UK – this secure research environment gives data scientists the scale and power of the cloud to predict personalised outcomes without sacrificing the privacy of people represented in the dataset. TPS also prioritises development of high-performance computing infrastructure which can optimise potential of scientific research.
Democratise access to data science and AI
TPS looks to co-create solutions in a multidisciplinary and mutually respectful environment. We are committed to demonstrating the creativity and transformative vision that can only be delivered by a diverse group of experts in a welcoming and collaborative space. Researchers and practitioners will be trained and mentored to transparently communicate their insights, and programme participation and outputs will be promoted openly to reach a broad community.
Impact Story: Changing the culture of data science
The crisis of reproducibility in science is well known. The combination of ‘publish or perish’ incentives, secrecy around data and the drive for novelty at all costs can result in fragile advances and lots of wasted time and money. Even in data science, when a paper is published there is generally no way for an outsider to verify its results, because the data from which the findings were derived are not available for scrutiny. Such science cannot be built upon very easily: siloed science is slow science.
That’s one of the reasons funders and publishers are beginning to require that publications include access to the underlying data and analysis code. It’s clear that this new era of data science needs a new cultural and practical approach, one which embraces openness and collaboration more than ever before. To this end, a group of Turing researchers have created The Turing Way – an evolving online “handbook” on how to conduct world-leading, reproducible research in data science and artificial intelligence.