At ADLIN, we're reinventing the use of healthcare data by developing the concept of Data Visiting.
Data Visiting makes it possible to share data without losing control of it. It offers the ability to perform analyses on data without it being moved, copied or transformed.
Beyond the importance of preserving data within the institutions that generated them, this concept advocates the importance of maintaining data in their scientific context. Health data taken out of context loses a significant part of its value. Exploiting them directly in their environment, with the experts who generated them, is a founding element of ADLIN's vision.
Thedata is therefore stored where it is generated, operated on-premise (locally), in secure bubbles, integrating the tools needed for its analysis. Data Visiting enables, among other things, analysis and FederatedLearning models to move towards the data, while keeping it under the control of its owners.
This approach is the opposite of the traditional Data Sharing model, which is based on data centralization. Instead of transferring or copying data, it preserves confidentiality, reduces the cost of anonymization and retains the scientific value of the data. Unlike Data Sharing, it guarantees total control over data access and use, while meeting RGPD requirements.
By enabling efficient and ethical Federated Learning, Data Visiting paves the way for multi-institutional collaborations that respect data sovereignty while accelerating innovation in healthcare.
