Main Content

FAIR Data Management

smART is a collaborative, interdisciplinary initiative spanning Goethe University Frankfurt, Philipps University Marburg and their partner institutions. The consortium aims to accelerate the characterization of mRNA structure, dynamics and interactions, and to make its results publicly available to advance research on mRNA targeting and RNA therapeutics. Members have agreed to share protocols, reagents, samples and data within the consortium and to release results through the consortium website and public repositories.

FAIR Data Management

The success of smART depends on knowledge sharing — plasmids and constructs, expression and purification protocols, RNA sample conditions, NMR and biophysical data, sequencing data, microscopy images and screening results. Our data stewardship plan follows the FAIR principles — Findable, Accessible, Interoperable and Reusable — and combines central infrastructure with project-level responsibilities. Z01 coordinates the overall data policy, while Z02 provides bioinformatics support and screens data-intensive requests.

Data stewardship levels

Each project (A01–A07, B01–B06, C01–C06, Z01–Z02) receives a unique identifier that is attached to all data uploads and requests. The plan has three levels, each offering data persistence and a different degree of FAIRness.

Level 1: Nextcloud

All groups have access to a consortium Nextcloud instance for internal data sharing. It is hosted on central servers with a Ceph storage backend, providing redundancy and scalable storage. Data can be processed on the HPC system, and long-term archiving is handled on tape.

Level 2: Central sequencing workflow

Groups submit sequencing requests through a standard form. Z02 screens the requests for technical suitability and comparability, and the steering committee approves them. Sequencing is then organized centrally to reduce costs, ensure quality and comparability, and guarantee central storage and findability of the resulting data.

Level 3: Public repositories

Data underlying publications are deposited in appropriate community repositories and linked to the publication via DOI. Where domain-specific archives exist, these are used; general data and metadata are deposited in a DOI-issuing repository. The consortium aims for the highest practical level of FAIRness for each data type.

A more detailed data management plan is maintained by Z02 and reviewed by the steering committee. It will be updated as the consortium’s data types and workflows mature.