Research data management plans
The university is committed to supporting its scientific staff with the creation of plans for the management of their scientific outputs. This commitment is outlined in the research data management policy of the MLU (in German only). In the same context, several funder agencies require data management plans to be provided as important complementary information of grant applications. Reviewers pay increasing attention to research data management plans while evaluating a proposal. In some cases, these plans are compulsory. The ULB offers scientific staff at the MLU support with writing the different sections of data management plans.
A data management plan is an instrument which will help grant applicants to provide their grant-application reviewers with information about:
- the types of data being created, including data formats
- how the data will be handled during and after a given project comes to an end
- data ownership
- data storage and data preservation decisions
- the available infrastructure
At the ULB we have drawn up a guide for creating FDM plans with important information.
The ULB and the Open Science Team work closely with other institutions which also support diverse FDM activities at the university. One of these partners is the Historical Data Centre Sachsen-Anhalt. Here you can read their advice document on the creation of data management plans for historians and other researchers in the humanities.
You can also consult an anonymized example of a Data Management Plan that has been written in the context of a natural science research project at the MLU which successfully obtained funding.
ULB’s Open Science Team can be contacted for personalized discussion of RDM questions and DMP. Drafts for DMPs can also be sent via e-mail for comments and remarks. Alternatively, SciFlow users can use templates for data management plans for some funding options (DFG, BMBF, H2020).
Research data management advice
While a number of resources provide excellent general advice on a variety of RDM topics, domain and discipline specific RDM information and advice is often required.
The ULB has therefore prepared the following subject-specific advice pages to provide information about, for example, where and how you can find and store research data, on suitable data formats, and where you can publish these research data:
I Natural Sciences
- our page on medicine (or download the PDF)
- our page on biology (or download the PDF)
- our page on neuroscience (or download the PDF)
II Social Sciences and Humanities
If you require further discipline-specific information which is not available in these pages please get in touch with a member of the Open Science Team.
Resources for finding data
There are a number of metasearch engines which can be used to obtain data sets or get an initial overview of the amount of available data from a particular source or subject.
Other important resources for finding research data are the so-called data journals. These journals publish new types of publication forms called data descriptors and data papers which focus on the data sets describing the methods used to collect the data and technical analyses supporting the quality of the measurements.
The following are examples of established peer reviewed data journals from different disciplines with high re-use potential: