Data driven life science skills development - equipping society for the future

Executive summary

We aim to develop and deliver workshops that help health and bioscience researchers - in academia, industry and society as a whole - to be both competent and confident in working with their data.

Why health and bioscience researchers need data science training

Biological and medical research has changed radically in the last 30 years due to new technologies that measure thousands of different molecular components in cells at the same time. For example, it is now routine to measure entire human genomes, all the proteins making up living cells, or DNA from all the microbes in a sample of soil. All this generates huge amounts of data that come in different formats and often at different times and places. So, today all biological researchers need to be good at managing and analyzing data - it is no longer the remit of the specialist. This is not just a UK challenge: international studies show the same trend. The demand for data science training far outstrips supply.

Life science industries are equally dependent on bioscience and health data, across pharmaceutical manufacturers, diagnostic providers, vaccine developers, and agricultural and environmental service providers. New moves towards precision medicine (drugs tailored to the patient) and precision agriculture (tailoring crop management) depend on access to, and accurate interpretation of, high quality data. Many careers in industry, government and society need good data management and analysis skills.

Importantly, the public needs confidence in data and data intensive research - for trust in the scientific process and for harnessing the benefits of data for science and society. Data sharing (Open Access Data) between researchers is important for scientific progress, for all-important reproducibility, and to derive best value for investment in publicly funded research.

In such a data-intensive environment for bioscience and health, it's important that everyone - whatever their career stage or role - can manage, analyse, store and share their data. This is what we hope to achieve through this project.

What we plan to do

We have focused training on areas where we know there is a particular need among health and bioscience researchers.
- Analyzing data - A good grounding in statistics is needed to analyze large and complex data sets, using modern methods such as machine learning.
- Managing data - Driving an understanding of how to move data securely around virtual 'storage' spaces in ways that information can be retrieved.
- Sharing data - Understanding and adhering to the FAIR principles (Findable-Accessible-Interoperable-Reproducible) ensures open access to data.
- Designing portable analysis - Writing complex analysis workflows in a manner that is easily transferred between different computing systems, so other researchers can use them too.

We will deliver these training workshops (online) using a well-established community platform called The Carpentries. This is an inclusive open-access platform that trains people in data and coding skills and encourages learners to become first helpers, and then trainers, as their own expertise develops. Open-access teaching materials mean that small improvements can be suggested every time a workshop is delivered, leading to a constant improvement in quality. It also means that anyone with an internet connection can use the materials for self-study, so work put into developing materials has wider impact. Edinburgh has the largest Carpentries affiliate in the UK, which is keen to extend the reach of its training.

Our programme will help level-up data skills across the UK and develop a growing cohort of confident practitioners across all career stages and industries. This will help meet the growing demand for data-savvy health and bioscience researchers in academia and industry.

Our aim is to enable researchers at all career stages to harness the power of data-driven research and innovation for health and bioscience, by providing training in the management and analysis of biological data. We will address this by scaling our successful training programs, adding new curricula, and training new instructors. We will use open-source platforms developed by The Carpentries, a community-based project that is a global leader in teaching data and coding skills. The Carpentries paradigm of open access training leads participants on a skills development path, first as a learner, then helping an experienced instructor, finally leading instruction themselves. Open platforms such as The Carpentries add value by enabling open peer review, re-use, and long-term archiving.

Our objectives are to:
1. Develop peer-reviewed training modules for biological data science that address identified skill gaps in health and bioscience researchers (Statistics; Open science, FAIR principles & data management; Data science computing with workflows) using The Carpentries platform.
2. Deliver 98 days of remote training of our new workshops, plus established introductory material, to a diverse community of researchers in academia and industry across all career stages.
3. Offer a clinic after every workshop for learners to ask advice regarding their own projects.
4. Train 30 new instructors to deliver these workshops, building a scalable training community.

Our remotely delivered training programme will be piloted locally and made available nationally, publicized via our strong links to organizations involved in data science UK-wide. Our team will bring together subject-matter expertise in 'omics, statistics, and computation, with strengths in research data management and the UK's largest Carpentries chapter, to build an extensive cohort of confident practitioners and a scalable and sustainable network of health and bioscience data science training for the UK.