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

数据驱动的生命科学技能发展——为未来的社会做好准备

• 批准号: MR/V039075/1
• 负责人: Alison Meynert
• 金额: $ 56.7万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV039075%2F1
• 关键词: Data; driven; life; science; skills

Executive summaryWe 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 trainingBiological 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 doWe 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.

我们的目标是开发和提供研讨会，帮助健康和生物科学研究人员-在学术界，工业和整个社会-为什么健康和生物科学研究人员需要数据科学培训生物和医学研究在过去的30年里发生了根本性的变化，因为新技术可以同时测量细胞中数千种不同的分子成分。时间例如，现在测量整个人类基因组、构成活细胞的所有蛋白质或土壤样本中所有微生物的DNA已成为常规。所有这一切都会产生大量的数据，这些数据以不同的格式出现，而且往往发生在不同的时间和地点。因此，今天所有的生物研究人员都需要善于管理和分析数据-这不再是专家的职责。这不仅仅是英国面临的挑战：国际研究显示了同样的趋势。数据科学培训的需求远远超过供应。生命科学行业同样依赖于生物科学和健康数据，包括制药商、诊断提供商、疫苗开发商以及农业和环境服务提供商。精准医疗（为患者量身定制的药物）和精准农业（定制作物管理）的新举措取决于对高质量数据的获取和准确解读。工业、政府和社会中的许多职业都需要良好的数据管理和分析技能。重要的是，公众需要对数据和数据密集型研究有信心-对科学过程的信任，以及利用数据为科学和社会带来的好处。研究人员之间的数据共享（开放获取数据）对于科学进步、至关重要的可重复性以及获得公共资助研究的最佳投资价值至关重要。在这样一个数据密集型的生物科学和健康环境中，每个人-无论其职业阶段或角色-都可以管理、分析、存储和共享其数据，这一点非常重要。这就是我们希望通过这个项目实现的目标。我们计划做什么我们把培训的重点放在我们知道卫生和生物科学研究人员特别需要的领域。- 分析数据-需要良好的统计基础才能使用机器学习等现代方法分析大型复杂的数据集。- 管理数据-推动理解如何以可检索信息的方式在虚拟“存储”空间中安全地移动数据。- 共享数据-理解并遵守公平原则（可发现-可验证-可互操作-可再现），确保数据的开放获取。- 设计便携式分析-编写复杂的分析工作流程，使其易于在不同的计算系统之间传输，以便其他研究人员也可以使用它们。我们将使用一个名为The Carpentries的成熟社区平台提供这些培训研讨会（在线）。这是一个包容性的开放获取平台，培训人们的数据和编码技能，并鼓励学习者成为第一个帮助者，然后是培训者，因为他们自己的专业知识发展。开放获取的教学材料意味着每次举办讲习班时都可以提出小的改进建议，从而不断提高质量。这也意味着任何有互联网连接的人都可以使用这些材料进行自学，因此开发材料的工作具有更广泛的影响。爱丁堡拥有英国最大的Carpentries分支机构，该机构热衷于扩大其培训范围。我们的课程将帮助提升英国各地的数据技能，并培养越来越多的自信从业者，他们横跨所有职业阶段和行业。这将有助于满足学术界和工业界对精通数据的健康和生物科学研究人员日益增长的需求。