Uni-Tübingen

What is Research Data Management (RDM)?

Research Data Management is the process of providing the appropriate labeling, storage, and access for data at all stages of a research project

Harvard University

 

Research data management (RDM) incorporates the entire research data lifecycle: from project planning, data generation, data storage and metadata description as well as documentation to data archiving and re-use. This also includes a conscious decision regarding which data from the research process should be preserved in the long term.

 

 

 

Research Data Management (RDM) is based on the data lifecycle.

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Every step in the lifecycle
of your data can be accompanied
by experts at the university.

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RDM in a Nutshell

the most important aspects:

Research data management refers to the process of organising the acquisition, processing, storage and publication of research data.

1. Planning: contact the research support unit; use the DFG checklist; use the university's text modules

2. Generating: create a data management plan (DMP) with RDMO

3. Analysing & Processing: contact an appropriate core facility, seek advice on overarching issues

4. Publishing: contact the university library if you have any questions

5. Archiving: talk to the ZDV about suitable storage solutions

6. Re-using: use FDAT or a repository of your choice

Planning of Data Management

Plan the management of your research data before compiling it. Contact support services at an early stage. Have your research project accompanied by the university's research support unit in order to receive detailed counselling.

Inform yourself about the conditions and requirements for RDM provided by your (potential) third-party funding organisation. If there is no specific information on data management for the funding format, use the DFG checklist and the university's text modules on RDM as a guideline. Also check whether you can apply for funding for RDM as part of the funding programme. Depending on the funding format and organisation, it is possible to apply for material resources and sometimes also personnel resources, e.g. as offered by the DFG.

Generating Research Data

Do you produce new data yourself or do you also use existing datasets? You can search in repositories to reuse research data from other scientists. Discipline-specific institutions such as the NFDI consortia or specialised information services can be contact points and provide support and guidance.

Define the management of your research data in a data management plan (DMP). This is often mandatory with many funding organisations. If your funding organisation does not provide a template, use the DFG checklist as a guideline. The university's RDMO instance can be utilised to generate a DMP. Your DMP can and should be revised and updated during the course of the research project. Ideally, appoint a person responsible for RDM in your project.

Analyzing and Processing Data

In order to make your research data usable in the long term, it must be annotated and provided with metadata. Various tools are available for this purpose. Contact the appropriate core facility for your discipline, which can assist you in this process.  

You should also contact experts for overarching topics such as the university's data protection officer, the copyright office and the technology transfer. This will ensure that issues such as data protection, copyright, licence and patent law are given sufficient consideration regarding your data.

Publishing Research Data and Findings

The results of your research and the corresponding data can be published in various ways. The university recommends following the CARE and FAIR principles and supports open access publications. The University Library can advise you on all questions regarding publishing.

If you register for an ORC-ID, you can link it to your publications. The ID allows your research to be clearly assigned to you and increases your visibility in the academic world. It also makes it easier for you to share data with other researchers. Ideally, you should also use persistent identifiers (e.g. DOI) for your publications.

Archiving of Research Data

To store your data long-term and securely, they should be saved in a repository. Institutional storage solutions are recommended for data that is still being worked on. The ZDV provides advice on data storage and archiving. Members of the Faculty of Medicine can also contact the GB-IT.

It is best to consider in advance how much data is likely to be generated in your project. This information is also relevant for your DMP.

Re-Using of Research Data

Take advantage of the opportunity to store your data locally long-term. With FDAT, the university offers its own cross-disciplinary repository for all researchers. You can find your processed data at any time, pass it on to others if required or access other colleagues' data yourself.

With the help of a retention period, you can also make data accessible at a later point in time, should this be necessary or desired. There are special protective measures for sensitive data, such as personal data. A personal consultation can help to find the best individual solution for you and your project.

Further Information

 

Contact

rdmspam prevention@zv.uni-tuebingen.de 
+49 7071 29-75082