Addressing the broadest and most pressing issues facing the natural world requires a holistic understanding of the complex interactions that govern it. This requires the use of models - mathematical descriptions of the world - to explain observed trends, answer "what if?" questions and predict future trajectories. As these models evolve to match our increasing understanding of the natural world, so must the research software infrastructure that underpins them. Amongst other things, this software infrastructure is responsible for helping us link models together to assess the bigger picture, promoting trust in scientific results by making model results reproducible, letting us easily use models on the latest high-performance computers, providing a consistent computational environment and access to data to help developers collaborate, and providing interactive visualisations and apps of model results to a broader audience. To use an analogy - just as analytical scientists require access to laboratories full of high-tech equipment to perform scientific experiments, computational scientists require access to virtual laboratories full of the latest software infrastructure to perform computational experiments. Software infrastructure and communities have developed to begin to meet these challenges across the globe, and partners in this project have been leading these developments for several decades. However, these software and communities are currently independent and constrained, either by geography or to particular scientific domains. The goal of this project is to unite this infrastructure around an international community of practice, providing much needed international cohesion across environment modelling software infrastructure. United, this software has the potential to be truly transformative, enabling collaborative innovation where, for example: models can be readily deployed to and dynamically linked within the cloud; physics-based, statistical and data science models can work seamlessly together to provide a step change in how realistically our models predict the natural world, and; results can be shared easily to non-developers via interactive apps. We will showcase this transformative potential through a case study, which will predict the transport of microplastics in the environment from their release, through waterways and the terrestrial environment, out to the ocean. Plastic pollution is widespread and global, with plastic debris present in all parts of the environment, from deep ocean trenches to remote mountains. It poses a potentially significant risk to both the environment and ourselves. Despite this, the modelling of microplastic transport in the environment is in its infancy, and whilst models of individual compartments (rivers, oceans) exist, there are no frameworks capable of predicting high-resolution microplastic transport from source to sea. Our case study will solve this, at the same time as demonstrating the benefits yielded by our united software infrastructure. This infrastructure will underpin the case study, providing the tools needed to link together the hydrological, microplastic transport and coastal ocean models of which it comprises, and providing a collaborative virtual environment to power it. The result will be a modelling framework that not only offers a step change in our ability to predict microplastic transport from source to sea, but that is flexible enough to be adapted to different chemical classes, thereby making a significant contribution to our efforts towards a zero pollution society. We are a new partnership who collectively unites world-leading expertise in software infrastructure development, community building, hydrology, chemical fate modelling and oceanography. All partners are committed to securing a long-term, self-sustaining collaboration that will ultimately help advance environmental modelling far beyond the scope of this project.

In Phases 1 (Prepare) and 2 (Deploy) we developed an understanding of the state of the nation of research software, its developers/users, its requirements, and how software is changing the way research is conducted. Building on our experience and expert understanding, Phase 3 (Expand) will focus on the creation of sustainable and self-supporting communities of practice to empower cultural change that enables better practice to be widely adopted to: foster a culture of sharing expertise and enabling; integrate project consultancy, training and awareness raising to effect and support change; move from local and individual actions to national and community level effects. Our goal is that the UK research community be enabled to take full advantage of software and, in doing so, to support the conduct of excellent research. Our objectives are: A) Widespread adoption of research best practice: agreeing and defining best practice with reference to research software, and enabling its widespread adoption to ensure the reliability and reproducibility of modern research. Enabling development of models and blueprints for initiating, nurturing and maturing communities of practice, enhancing our status in the UK and internationally as the go-to institution for insight into research software matters and catalysing new international collaborations. B) Cutting-edge policy and guidance: collaborating with stakeholders to create and disseminate evidence-based guidance, infrastructure, policies and tools. This leads to improved reusability of research software and its associated research outputs. C) A capable research community: based on a sustainable and scalable community-led model that will push the boundaries of knowledge across domains to maintain excellence and drive innovation and career paths, to increase the recognition of research software. Supporting collaboration in the UK research society and helping it become more resilient and sustainable will achieve an increased social and cultural impact. D) An open evidence bank: identifying and generating datasets, conducting analysis to provide insight and evidence of the importance of software, people and practices. This enables costing of resources required to develop, maintain and preserve research software. To achieve these goals, we will be: 1) Raising awareness: empower and develop a cohort of ambassadors for good practice through our Fellowship; outreach to stakeholders at all levels on research software issues; to deliver adoption of best practice. 2) Seeding change: build multiple sustainable Communities of Practice (CoP): for research domains, for techniques, for stakeholder groups, for UK institutions; set up expert panels that commission topic-based programmes of workshops, policy studies and outreach; nurture and scale existing CoPs e.g. through RSE exchanges; develop tools and services to support CoPs; to guarantee the widespread adoption of research best practice. 3) Providing expertise: create regional training hubs to continue growth of provision; commission new courses; refocus open call consultancy; conduct feasibility study for an RSE brokerage; to form a capable research community. 4) Influencing policy: publish new guidance and standards; work with international collaborators to put policy into practice; conduct research that improves understanding of research software; to deliver cutting-edge policy and guidance and build an open evidence bank.