Data Management
Research Data Management in TRR 387
About
From proteomics and genomics to imaging, compound screening and structural biology, TRR 387 works with a wide range of data types. Research data management helps transform these data into lasting scientific value by making them easier to find, understand, share and reuse.
Our work follows the FAIR principles: making data findable, accessible, interoperable and reusable. It also aligns with relevant funder, infrastructure and institutional requirements.
How we support the TRR 387
As Data Stewards, we support researchers throughout the research data lifecycle: from planning and documentation to sharing, archiving, publication and reuse.
RDM policy and guidance: Shared guidance for handling research data in TRR 387.
Training and consultation: Workshops and consultations to help you apply good research data management.
Data management plans: Support for planning and updating project-specific data management plans.
Metadata and documentation: Standards, naming conventions and metadata templates that make data easier to understand and reuse.
Data sharing and archiving: Help with structured exchange and long-term storage using tools such as the TUM DataTagger.
Sensitive data and responsible access: Support for data sharing in line with legal, ethical and institutional requirements, including secure handling of sensitive human-derived data.
Data publication: Advice on repositories and preparing datasets for publication.
Research software: FAIR practices for code, scripts, workflows and analytical tools.
Networking and community exchange: We work closely with local RDM teams at the TRR partner sites and connect with national RDM communities to bring emerging standards, tools and best practices into workflows.
The Data Steward Team
The TRR 387 Data Steward team is your first point of contact for practical support with research data management.
Contact
Questions about research data management in TRR 387?
Email us and briefly let us know what you need help with.