An empirical case and ongoing efforts on Transversal Computer Strategies & Services for Scientific and Training efforts for the LASF4RI

This white paper outlines a strategic proposal to enhance open-access and free-tier scientific computing and educational resources, leveraging advanced data handling, analysis, and cloud computing technologies. Building on previous work, this proposal updates the 2020 initiatives and presents the state-of-the-art in ongoing projects, such as the deployment of cloud-based HPC resources in Latin American universities. We propose a cohesive strategy to deploy multi-user platforms for scientific data analysis, particularly in resource-limited settings, utilising open data from high-energy physics experiments and other high-dimensional datasets. By strategically using commercial clouds and repositories, we aim to significantly boost computing power access for our researchers and students, preparing them for competitive careers in the industry while democratising access to cutting-edge research tools and methodologies. This approach integrates Software as a Service (SaaS) and Infrastructure as a Service (IaaS) solutions to further enhance accessibility and scalability. Additionally, we actively engage in small-scale computing projects and infrastructure-related training programs to build local capacity and foster scientific collaboration across Latin America. Through these efforts, we seek to create a robust, scalable, and accessible framework that supports scientific endeavours and capacity-building projects in the region. Lastly, we advocate for a more focused, task-oriented approach to scientific collaboration that leverages our students' and academics' adaptability and resourcefulness. Rather than replicating large-scale infrastructures typical of more resource-rich countries, we focus on maximising return on investment and fostering regional human capital development. Results, examples and new developments are and will be hosted in GitHub organizations: https://github.com/laa-hecap https://github.com/GOES-training https://github.com/atlas-outreach-data-tools