Data/Culture. Building sustainable communities around Arts and Humanities datasets and software

英国处于独特的地位，可以定义世界领先的数据驱动的艺术和人文研究，并对其做出贡献。之前的投资已经创建了大量的数据集、方法、工具和管道。然而，由于目前以项目为重点的融资格局的性质，这些资金很少被发起项目以外的人利用，这意味着投资回报很低。造成这种情况的原因是多方面的，但一个关键因素是缺乏基础设施来支持产出以及在项目结束日期之后在托管、维护或人力专门知识方面吸收产出。其结果是重复出现浪费劳动力的循环。即使进行了最好的尽职调查，新项目往往也会另起炉灶，构建新的数据集、工具和管道，因为它们不知道或无法访问其他地方已经存在的研究基础设施组件。如果这些组件可以变得更具普遍性，如果它们被很好地打包和记录，如果围绕它们积极地建立用户和维护员社区，如果嵌入利用它们的技能，我们就可以创建一个模块化的数字研究基础设施的基本组件，这将有助于加速研究创新。这个试点项目提议用两个先前资助的项目的数据和软件输出来验证这一假设：与机器一起生活(LWM)和SEHAT：全球历史数据库。这一愿景的核心是图灵研究所，该研究所通过在英国召集数据科学和人工智能社区，寻求推动世界一流的研究，并将其应用于现实世界的问题，并为未来培养技能。我们将利用图灵的召集力来交付三项核心任务：*推动数据和软件开发的卓越，将LwM和Seshat项目资产开发成具有这些项目以外的实用价值的可持续架构；*通过利用这些数据和软件组件来加速研究创新；*创建可持续的实践社区，以新的方向维护和发展这些成果。

The UK is in a unique position to define and contribute to world leading data-driven arts and humanities research. Previous investments have created numerous datasets, methods, tools and pipelines. However, due to the nature of the current project-focused funding landscape, these are rarely leveraged by those outside the originating projects, meaning that return on investment is poor. The reasons for this are manifold, but a key factor is the lack of infrastructure to support outputs and their uptake beyond the end date of projects in terms of hosting, maintenance, or human expertise. The effect is a repeated cycle of wasted labour. Even with the best due diligence, new projects often reinvent the wheel, building new datasets, tools and pipelines, because they do not know, or cannot access research infrastructure components that already exist elsewhere. If those components could be made more generalisable, if they were well packaged and documented, if communities of users and maintainers were actively built around them, and if skills to exploit them were embedded, we could create the basic components of a modular digital research infrastructure that would help accelerate research innovation.This pilot project proposes to test this hypothesis on the data and software outputs of two previously funded projects: Living with Machines (LwM), and Seshat: Global History Databank. At the centre of this vision is The Turing Institute, which by convening the data science and AI community in the UK, seeks to advance world-class research and apply it to real-world problems, and to build skills for the future. We will leverage the Turing's convening power in order to deliver three core tasks:* Drive excellence in the development of data and software, developing LwM and Seshat project assets into sustainable architectures that have utility beyond these projects;* Accelerate research innovation, by leveraging these data and software components;* Create sustainable communities of practice that maintain and develop these outputs in new directions.