FAIR data management

FAIR (Findable, Accessible, Interoperable, Reusable) data management is the pillar of trustworthy science. Data management according to the FAIR principles must be fully integrated into clinical data collection. An infrastructure with user-friendly front-ends (data collection) and automated back-ends (data management) is essential for broad acceptance in clinical research and care. Data protection and privacy on the one hand and integration, reuse and exchange of data on the other must be reconciled by design.

The use cases range from the manual input of clinical data, the performance of digital tests (e.g. neuropsychology or kinematics), the recording of disease symptoms in daily life with the help of smart devices (e.g. smartphones and health trackers), to so-called Ecological Momentary Assessments and computer-aided data acquisition with AI-based annotation. Homogeneous data management solutions are available for all applications, which ensure and support the “FAIRness” of the data for biomarker development and analysis immediately after it is collected. In addition to pure data acquisition, ABCD-J projects also focus on various data processing scenarios. These include “backend” servers of mobile health systems, as well as integration as storage or computing nodes in cloud systems or in (medical) data centers for controlled connection to existing data and computing infrastructures.

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