The UK has spent millions building digital archives, maps, and tools for arts and humanities research, but most of them are abandoned once their funding runs out. This pilot project aims to break that cycle by turning two existing digital resources—Living with Machines and the Seshat Global History Databank—into reusable, well-documented, and actively maintained research components that others can actually find and use. The core problem is that each new research project typically builds its own datasets and software from scratch, because previous outputs are poorly packaged, undocumented, or simply vanish when project funding ends. This wastes time, money, and expertise. The project will test whether convening researchers, data scientists, and software engineers around these two assets—using the Turing Institute’s ability to bring people together—can create sustainable communities that maintain and improve the outputs long after the original grants finish. If successful, this approach could transform how arts and humanities research infrastructure works. Instead of each project reinventing the wheel, researchers could build on modular, shared components—accelerating innovation and improving return on investment. The immediate impact is on research efficiency, not everyday life, but the model could eventually apply to any field that generates digital data and tools.
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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.
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