Designing the Future of Scientific Computing: FAIR, Efficient, and Sustainable

Achieving sustainability in our current digital age requires rethinking how we design, develop, and use information technologies for research and innovation. This keynote explores two key dimensions of sustainable scientific computing: the adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles for research data and software, and the pursuit of energy efficiency across computational infrastructures and workflows. FAIR principles form the foundation of transparent, reproducible, and collaborative research. They enable knowledge sharing across disciplines, reduce duplication of effort, and ensure that digital resources remain usable over time. By extending these principles from research data to software, the scientific community can promote responsible innovation, strengthen interoperability, and build trust in computational results, which are key elements for advancing sustainability in science and technology. Complementing FAIRness, energy efficiency has emerged as a critical but often overlooked dimension of sustainable computing. Despite rapid advances in computing capacity, the energy and carbon footprints of large-scale computation continue to grow. Addressing these challenges requires greater awareness, reliable monitoring, and new practices that integrate energy considerations into system design and daily research workflows. Drawing on examples from the Earth Observation domain, this talk will highlight current gaps, promising approaches, and the role of community-driven initiatives in fostering both energy-aware and FAIR-aligned digital ecosystems. Together, these efforts can reshape scientific computing into a foundation that is more sustainable, responsible, and resilient for future discovery.