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

英国在定义和促进世界领先的数据驱动的艺术和人文研究方面处于独特的地位。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，由于当前以项目为中心的融资格局的性质，这些融资很少被原始项目之外的人利用，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支持产出的基础设施，以及在项目结束日期之后在托管、维护或人员专业知识方面对产出的吸收。其结果是劳动力浪费的反复循环。即使有最好的尽职调查，新项目也常常会重新发明轮子，建立新的数据集、工具和管道，因为他们不知道，或者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通用，如果它们被很好地打包和记录，如果用户和维护者社区围绕它们积极地建立起来，如果利用它们的技能被嵌入，我们就可以创建模块化数字研究基础设施的基本组件，这将有助于加速研究创新。该试点项目建议在两个先前资助的项目的数据和软件输出上测试这一假设：与机器一起生活（LwM）和Seshat：全球历史数据库。这一愿景的核心是图灵研究所（the Turing Institute），它通过召集英国的数据科学和人工智能社区，寻求推进世界级的研究，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完成三个核心任务：*推动数据和软件开发的卓越性，将LwM和Seshat项目资产开发成具有超越这些项目效用的可持续架构；*利用这些数据和软件组件，加速研究创新；*创建可持续的实践社区，在新的方向上保持和发展这些产出。

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.