Why Manage Data?

Research Data Management is beneficial for both researchers and disciplinary progress in general. Even if data management requires additional work at the beginning of a research project, it reduces difficulties and problems in the course of the project.

Life cycle of research data according to WissGrid WissGrid Tasks in the research data life cycle according to WissGrid

Involved Tasks

  • Planning and generation are activities that form the basis for data management.
  • Selection means analysis – which data must be stored? What documentation must be provided to make the research results understandable and verifiable?
  • Ingest: Migration of research data that is to be stored on a long-term basis
  • Storage / infrastructure – in the archive or repository – is the core responsibility of data management.
  • Data maintenance is to secure the permanent availability and follow-up use of research data.
  • Access must be provided to make the data available internally or externally.
Research Data Management at RWTH Aachen – English version

Quality

Research data management improves the quality of your research data, ensures that your data are complete, and secures their full reproducibility.

Security, Protection, and IP

Research data management protects your data against loss; furthermore, sensitive data are professionally protected against misuse, theft, damage, et cetera.

Integrity

Research funding bodies, such as the DFG and Horizon 2020, as well as various publishing houses and scientific journals, increasingly demand that research data is effectively managed:

  • to meet standards of good academic practice,
  • to ensure that research processes are transparent,
  • to safely archive and provide access to research data.