Edge Data for Science
Science is increasingly data-driven. From genomics to climate modelling, the ability to generate and analyse vast datasets underpins modern research. This makes data storage and access a silent yet essential part of the scientific ecosystem.
Unlike commercial cloud facilities, science data centres must combine computational power, low-latency access, and specialised cooling for high-performance computing (HPC). Locating them close to research clusters reduces data-transfer times and strengthens collaboration. This raises a key design challenge: how can these energy-intensive, technically complex facilities integrate with the open, collaborative ethos of a science campus?
Energy strategy is paramount. Science data centres often operate at extreme power densities; tens of megawatts per facility: making renewable integration, waste-heat recovery, and grid resilience critical. Forward-thinking campuses are now exploring circular energy systems, using waste heat from computing to warm nearby laboratories or offices, thereby reducing environmental impact and supporting sustainability goals.
Security and redundancy are also defining factors. Research data can be commercially sensitive or ethically constrained, demanding secure perimeters, layered access controls, and robust disaster recovery systems. Yet within these constraints, architecture should aim for transparency and connection rather than isolation, perhaps through shared amenities, transparent façades, or visual links to the wider campus.
As AI and simulation tools proliferate, science data centres will become as central to research as the lab bench. Designing them as part of the scientific landscape, rather than as isolated industrial boxes, is key to creating campuses that are digitally and physically coherent.
To support the exponential growth of data-driven science, our developments now integrate edge data solutions directly within science campuses. Edge data centres process and store data close to its source, enabling real-time analysis, reduced latency, and enhanced security; particularly vital for activities such as DNA sequencing, gene editing, computational modelling, and clinical trials.
Our science edge data strategy includes:
• Strategic Location: Centres sited within or near research clusters to minimise transfer times and support interdisciplinary collaboration.
• High-Speed Networking: Robust, low-latency connectivity across campus.
• Scalable and Secure Infrastructure: Flexible design with advanced security and disaster recovery.
• Sustainable Design: Built to Passivhaus principles and leveraging circular energy systems.
• Support for AI and Simulation: Providing the computational backbone for emerging scientific tools.
By embedding edge data capabilities into our masterplans, we are future-proofing campuses to support the next generation of research, ensuring they remain coherent, resilient, and ready for the demands of data-driven science.
Written by James Buckley-Walker – 3pm Partner
Unlike commercial cloud facilities, science data centres must combine computational power, low-latency access, and specialised cooling for high-performance computing (HPC). Locating them close to research clusters reduces data-transfer times and strengthens collaboration. This raises a key design challenge: how can these energy-intensive, technically complex facilities integrate with the open, collaborative ethos of a science campus?
Energy strategy is paramount. Science data centres often operate at extreme power densities; tens of megawatts per facility: making renewable integration, waste-heat recovery, and grid resilience critical. Forward-thinking campuses are now exploring circular energy systems, using waste heat from computing to warm nearby laboratories or offices, thereby reducing environmental impact and supporting sustainability goals.
Security and redundancy are also defining factors. Research data can be commercially sensitive or ethically constrained, demanding secure perimeters, layered access controls, and robust disaster recovery systems. Yet within these constraints, architecture should aim for transparency and connection rather than isolation, perhaps through shared amenities, transparent façades, or visual links to the wider campus.
As AI and simulation tools proliferate, science data centres will become as central to research as the lab bench. Designing them as part of the scientific landscape, rather than as isolated industrial boxes, is key to creating campuses that are digitally and physically coherent.
To support the exponential growth of data-driven science, our developments now integrate edge data solutions directly within science campuses. Edge data centres process and store data close to its source, enabling real-time analysis, reduced latency, and enhanced security; particularly vital for activities such as DNA sequencing, gene editing, computational modelling, and clinical trials.
Our science edge data strategy includes:
• Strategic Location: Centres sited within or near research clusters to minimise transfer times and support interdisciplinary collaboration.
• High-Speed Networking: Robust, low-latency connectivity across campus.
• Scalable and Secure Infrastructure: Flexible design with advanced security and disaster recovery.
• Sustainable Design: Built to Passivhaus principles and leveraging circular energy systems.
• Support for AI and Simulation: Providing the computational backbone for emerging scientific tools.
By embedding edge data capabilities into our masterplans, we are future-proofing campuses to support the next generation of research, ensuring they remain coherent, resilient, and ready for the demands of data-driven science.
Written by James Buckley-Walker – 3pm Partner