Research Data Management

 

Research data management (RDM) combines the organization, structuring, documentation, sharing, publication and secure (long-term) storage of research data. A consistent application of RDM is part of Good Scientific Practice, and makes it possible to disclose the entire research process to be incorporated and further developed by other researchers, which opens the door to Open Science. Within RESOLV, an efficient data flow between the individual sub-projects supports the gain of knowledge and is substantial. For these reasons, we develop a central data hub covering all relevant RDM tools for internal data sharing and archiving as well as data publications of RESOLV results. Therefore, research data management is an integral part of RESOLV.

Typical RESOLV research data includes experimental, e.g., analytical and spectroscopic data, images, videos, or simulation-related data, e.g., program code, analysis scripts, spreadsheets, log files, raw production data and could be assigned to the four bigger disciplines synthesis, spectroscopy, theory, and engineering.

 

RESOLV’s Research Data Management Task Force

 

In 2020, RESOLV installed a RDM Task Force in order to identify and develop tools to manage the RESOLV research data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. The task force consists of dedicated personnel from the relevant disciplines (synthesis, spectroscopy, theory, and engineering). Members of the RDM Task Force are also members of the German National Research Data Infrastructure for Chemistry (NFDI4Chem). The mission of the RESOLV RDM Task Force ist to provide individual RDM support to RESOLV PhD students, Postdocs and other researchers, regular workshops and specific training courses are also offered.

RDM terminology and tools

 

Planning of research projects

Even before the project starts, an RDM concept should be developed that governs the efficient handling of research data during and after a research project and should be written down in a Data Management Plan (DMP). A proven tool for creating, managing and sharing DMPs is the Research Data Management Organizer (RDMO).

 

Documentation and processing of research data

The use of free text documents, such as (laboratory) notebooks is limited because the notes are not machine-readable and searchable. Using electronic laboratory notebooks (ELNs) in combination with structured and defined metadata schema remedies this by making the research data findable, traceable, assignable to projects, and available for other researchers (even after the change of personnel). ELNs support the seamless data flow to repositories for research data sharing, publication and storing. Therefore, we recommend at least for all our experimental groups the use of ELNs (e.g., Chemotion, eLabFTW, sciformation).

For theory groups, GitLab is recommended for coordinating the joint development of program codes and version control.

Metadata contains defined elements, such as the author, the (project) affiliation, and the date of creation, but also essential parameters necessary to understand the data, up to an abstract of the project.

 

Repositories

Repositories (repos) are data- and document servers where scientific research results in publications and datasets can be stored and made accessible. By assigning metadata, it is possible to make these (data) publications findable via search engines. Usually, a persistent identifier is also assigned (DOI) so that the publication is linked sustainably.

Both, the above-mentioned ELNs and GitLab can be exported to the currently developed RESOLV’s repository RESOLVdata (based on Dataverse) for RESOLV-internal data sharing, annotation, export (SI publication, external repositories), and archiving. In RESOLVdata you can assign your research data with specific RESOLV-DOIs to be linked in your manuscript submissions.

Comprehensive information on the RESOLV repository RESOLVdata can be found on our intranet:

RESOLVdata

 

Storage and Archiving

When archiving research data, a distinction is made between the secure and usable storage of research data for a period of 10 years in accordance with the rules of good scientific practice (archiving) and long-term storage for periods of more than 25 years.

In RESOLVdata research data is securely stored for a period of at least 10 years. Unauthorized access to the stored data is prevented by a rights management system.

Archiving and long-term archiving (for more than 25 years) pose particular challenges for your data. Archived data should be in an open, non-proprietary format if possible. If migration to an open format is not technically feasible, then the software used to create or open the data should also be archived. If necessary, the entire software environment can be archived (virtualization and containerization) to ensure the usability of the research data.

 

Individual support

 

The mission of the RESOLV RDM Task Force is to provide individual support to all RESOLV PhD students, Postdocs and other researchers on:

  • Developing Data Management Plans
  • Assigning Metadata
  • Choice of Electronc Lab Notebooks
  • Application of RESOLVdata and open repositories
  • Guidance on storage and archiving
  • Assigning your research data with a RESOLV-DOI
  • Specific questions

Please contact us, we are happy to help!

Support

 

Workshops and Events

Regulations and Policies

 

We base our handling of research data on the overarching policies and regulations of the participating universities and institutes as well as on the DFG's recommendations:

For detailed RESOLV specific guidelines visit the intranet:

RESOLV RDM Guidelines

 

Contact

 

If you want to get in touch with our RDM Team, please write to

resolv[@]rub.de

or browse specific contact persons here:

Contact