To address this challenge, the Open Research Data (ORD) project “Surgical Data Science OR-X” was launched in July 2024. The initiative brought together researchers and engineers from the University of Zurich, ZHAW, Zühlke Group and the Digital Medicine Unit of Balgrist University Hospital. Funded by swissuniversities and the State Secretariat for Education, Research and Innovation (SERI), the project focused on developing infrastructure and methods for open and standardized surgical data collection. The project was successfully completed in June 2025.
Unlocking New Horizons in Surgical Data Science
Overcoming Data Barriers in Surgery
Overcoming Data Barriers in Surgery
Generating high-quality intraoperative data remains one of the major challenges in advancing surgical data science. Real-world operating rooms are shaped by strict safety protocols, complex workflows and proprietary systems, which severely limit the ability to capture comprehensive datasets. As a result, the application of data-driven methods in surgery continues to lag behind other disciplines, slowing progress in areas such as 3D reconstruction, behavioural analysis, machine learning and medical imaging.
An Infrastructure for Open Surgical Data
An Infrastructure for Open Surgical Data
From Concept to Implementation
The project aimed to enable the generation and sharing of large-scale multimodal surgical datasets in line with Open Science principles. This included the development of hardware and software solutions for synchronized real-time data capture across different surgical technologies, as well as frameworks for structuring and standardizing the collected information. In parallel, a public cloud platform was created to provide curated datasets according to the FAIR principles: findable, accessible, interoperable and reusable.
To realize this, the project relied on the OR-X research infrastructure, which enabled the integration of technologies such as surgical robotics, augmented reality and artificial intelligence under realistic but non-clinical conditions. Combining a fully equipped surgical environment with flexible technical integration, the OR-X allowed the team to synchronize data streams, connect experimental systems and conduct highly reproducible studies beyond the limitations of conventional operating rooms.
The implementation phase also included iterative validation cycles with external clinical and academic experts. Their feedback ensured that the developed systems were not only technically robust, but also aligned with practical requirements in surgical research and future data-driven applications.
Outcomes and Broader Impact
Outcomes and Broader Impact
The project resulted in two central outcomes: a Data Collection Framework for automated and standardized data acquisition, and a Surgical Data Cloud Platform providing open access to selected datasets for the research community. Together, these developments contribute to establishing new standards for how surgical data can be collected, managed and shared.
Beyond its technical achievements, the project demonstrates how Open Research Data initiatives can create reusable infrastructure and scalable approaches for future surgical research, while supporting the broader development of surgical data science and AI-driven innovation.