DIFUTURE will improve data quality, data availability, and data integration. Data and knowledge need to be available at the point of care as a basis for targeted diagnosis and therapy.
From an application perspective, our approach is use-case driven, i.e. following the needs of physicians and researchers and aiming at benefits for the patients.
With focuses on neurology, oncology, and further disease entities, we will work on early diagnosis, tailored therapies, and therapy decision tools.
Our first use cases are built to form a blueprint for the following ones, and we have already implemented organizational and technical measures, e.g. by convening groups of key persons and by implementing technical solutions. Our efforts will be based on previous and current work in numerous projects (e.g., BBMRI LPC and ADOPT, BioMedBridges, Leading Edge Cluster m4, e:Med).
From an informatics perspective, we will adhere to state-of-the-art software engineering processes, and (a) start with a vision and global goals, (b) proceed to concrete goals, (c) specify analyses and data required for concrete improvements, (d) implement concepts and methods of secure data sharing, and (e) realize and evaluate concrete solutions. We will base our approach on sound architectural models.
We are clearly aware of the data security and privacy challenges of this initiative, with its unparalleled size and scope in Germany. We will provide strong levels of security by innovative combinations of privacy protection measures (“safe data” ,“safe setting”, “safe outputs”) and by distributed approaches (e.g., “Data Analysis Trains”).
Outline of the architecture of a data integration centre