FAQ

A data management plan (DMP) is a formal document that describes the handling of research data during the active phase and after the finalization of a research project.

The DMP should be written before the project starts and can be changed during the course of the project according to the requirements (i.e., it is a living document).

The DMP includes regulations regarding, e.g.:

• Responsibilities for data management
• Costs and financing of data management
• Purpose, type, amount and organization of gathered data
• Metadata and metadata standards
• Target group and conditions for the re-use of data
• Storage, backup, archiving and publication of data

You can find several guidelines and templates for the development of research data management plans on our information website.

Research data management is an essential part of grant applications for most funding agencies.

The German Research Foundation (DFG) does not demand a data management plan but the management of the research data in the project has to be described in the grant application (see guidelines on handling research dataExternal link). The concepts for quality assurance as well as long-term data archiving and the publication of research data have to be discussed in this section. The required information is also a typical element of a data management plan. In some research fields, stricter rules regarding research data management apply.

Grant applications and projects in biodiversity research are supposed to create a data management plan (see Guidelines on the Handling of Research Data in Biodiversity ResearchExternal link).

In education research, clear statements regarding research data management are expected during the application phase. In cases where the concept for the data management does not fit the expected re-use of the data, further clarifications or the development of a data management plan can be requested before a decision is made regarding the application (see: Provision and Use of Quantitative Research Data in Education Research: Memorandum of the DFG Review Board for Education SciencesExternal link).

The Federal Ministry of Education and Research (BMBF) demands a clear description of research data management and the accessibility of data during and after a research project. This can be included in the grant application, but in some cases, the creation of complete data management plans in accordance with international standards (e.g. FAIR principles) is expected.

Projects that are funded by the European Commission have to state the strategy for research data management of the project in the grant application. If the project is part of the Open Research Data Pilot (ORD pilot), the creation of a data management plan is required.

The creation of a data management plan is generally recommended for projects which are funded by the EU but is not mandatory (see Horizon 2020 Online ManualExternal link).

Data management plans can have different dissemination levels. Although the public accessibility of the data management plan is favourable and increases the transparency, also confidential handling is possible if there are appropriate reasons.

Material and personnel costs arise from appropriate research data management. These costs should be calculated before the start of the project and should be considered in the grant application.

Typical matters of expense are:

• Access to existing data
• Personnel costs for researchers/student helpers (e.g. formatting/organization/ documentation of data/metadata)
• Personnel costs for data manager(s)
• Storage and backup of data (hardware)
• Digitalization of objects/documents/manuscripts
• Data archiving
• Data publication

Free tools like the OpenAIRE Estimating costs RDM toolExternal link can be used to estimate the costs for research data management in projects.

Many funding agencies offer the possibility to apply for funding of research data management in the context of research projects. However, only project-specific equipment will be funded not basic equipment.

Examples for costs that can be included in grant applications:

1. Costs for processing data for further (re-)use
2. Costs for transferring data into existing infrastructures
3. Personnel costs
4. Project-specific hard- and software
5. Usage fees (e.g. infrastructure, secondary data)

Within the framework of Collaborative Research Centres (SFBs), applications can also be submitted for infrastructure sub-projects.

Many funding organisations require applications to include information on the handling of research data in the project. Funding applications must therefore usually provide information on aspects such as:

• type and size of data
• documentation and data quality
• storage and long-term accessibility of the data
• data exchange
• legal framework conditions in the project
• responsibilities and resources.

It is advisable to make the concept as informative as possible and to already plan the concrete procedure in it. The DFG provides a detailed checklistExternal link of the topics to be described.

Research data that are the basis of a scientific publication has to be stored for at least 10 years (after date of publication), according to the “Guidelines for Safeguarding Good Research Practice” (Code of Conduct, 2019).

For specific datasets longer or unlimited storage periods might be recommendable or required. Reasons for long-term storage (>10 years) of datasets include:

1. The data are the basis of a scientific publication (e.g., research article).
2. The data include unique observations/measurements in space and time that cannot be reproduced.
3. The data can only be reproduced with high efforts (e.g., calculations on supercomputers).

Research data can be stored either at the institution that produced the data or in a repository. In general, the German Research Foundation (DFG) recommends to make data accessible as soon as possible.

Different factors have to be considered regarding the storage of research data. In general, all storage devices have a restricted life time and need to be replaced regularly (a summary of the lifetimes of different storage media can be found hereExternal link). Usually, hardware should be replaced every 5 years.

Mobile devices like USB sticks, hard drives or laptops can be lost or can get stolen. If servers or cloud services are used, the security of the data against access by unauthorized persons must be ensured.

The Rechenzentrum de (computer centre) of the FSU Jena offers a variety of storage options with adequate backup plans for students, employees and working groups. Contact the team of the Rechenzentrum for individual solutions and advice.

In general, a backup according to the “3-2-1 rule” is advisable:

3 copies on 2 different storage devices and 1 storage at an offsite location.

The backup frequency depends on the requirements of the respective project and can either be linked to the generation/change of data or take place at predefined points in time (e.g. once a day).

The storage media and storage location need to be adjusted to the specific requirements of the data (e.g. amount of data, personal data included) and the technical infrastructure. If you use storage provided by the computer centre of the FSU de the data is normally backed up automatically.

Students and employees of the FSU Jena have access to a central, safe and restorable storage (Home External linkFolder). In addition, central storage for the collaborative work within projects or working groups is available (Project FolderExternal link). An FSU account (URZ) is required for the access to the Project Folder. The initial free storage space depends on the size of the institution but an extension is possible (with costs).

All  employees of the FSU Jena have access to storage space in the FSU CloudExternal link for the exchange of data. The free storage is limited to 5GB per user but can be extended (with costs).

If you use your own servers for the storage of your research data, it is possible to include the server into the backup system of the FSU JenaExternal link. In addition, it is possible to house your servers in the facilities of the computer centre of the FSU Jena (Server-HousingExternal link).

There are various options to share data with colleagues and collaborators. Often services of third-party companies are used (e.g. Dropbox, GoogleDocs). Please note that the data may be stored outside the European Union and therefore different legal regulations may apply (e.g. data privacy). Members of the FSU Jena have access to the services of the computer centre of the FSU Jena de. Data can be shared with other persons who possess an URZ account via project foldersExternal link. To share data with collaborators outside of the FSU Jena, data can be shared via the FSU CloudExternal link.

In the “Guidelines for Safeguarding Good Research Practice” (Code of Conduct, 2019) the German Research Foundation (DFG) recommends that data which are the basis of a publication, should be made available in public repositories whenever possible. The publication of the data should be based on the FAIR principles (Findable, Accessible, Interoperable, Reusable) in order to increase the reproducibility and re-use of the data.

Research data of projects which were funded by the Federal Ministry of Education and Research (BMBF) should also be made available for re-use in accordance with the FAIR principles after the end of the project. In some cases, more strict regulations regarding the publication of research data are applied. In a recent funding programme, the BMBF demanded the publication of all research data of the project, independent if they are in accordance with the hypothesis of the study or not.

Projects that were funded by the European Union may be subject to more strict regulations regarding the publication of research data (Open Data). In general, the European Commission demands that research data are made available “as open as possible and as closed as necessary”.

For projects which are funded by the Horizon 2020 programme, publication of research data is the default situation and the data have to be made accessible for others (Open Research Data Pilot). However, this rule only applies to data which are the base of scientific publications. It is still possible to make data not publicly accessible, for example in the context of patents or for further own research work. Under such conditions, projects are free at any time to not make the research data public (opt-out). Projects in other ERC funding programmes can also participate voluntarily in the Open Research Data Pilot (Opt-In).

Data which are not the basis of a scientific publication can be made available if they are supposed to be re-usable for others.

There are different ways to publish research data:

1. Supplement of a publication
2. Data publication
3. Repositories

The publication of research data as a supplement of a scientific publication is an option offered by many journals. The data are directly connected to the research article and the results (without separate DOI). However, the size of files in the supplement is usually restricted and there are usually just limited options to provide rich metadata. In addition, the access to the data may be restricted by the terms of service of the journal if the article is not open access.

Many publishers offer specific data journals for the publication of research data. Here, the dataset and the corresponding background information and metadata are treated as a separate publication which undergoes also a peer review process. An important criterium of many data journals is the compliance of the dataset with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. You can find an overview of some data journals on our information page.

Repositories are intended to store data for long time periods and to make them publicly available. Repositories can be classified according to the scope and the operating agency as institutional/generic (interdisciplinary) or discipline-specific repositories. A search using the repository registry Re3Data.orgExternal link can help you to find a suitable repository for the publication of your data. In general, discipline-specific repositories are preferable to generic/institutional repositories since the searchability is better and the standards in the corresponding scientific community are taken into account.

Further information can be found on our information website.

The Digitale Bibliothek Thüringen (DBT) is an institutional and generic repository which is run by the Thüringer Universitäts- und Landesbibliothek (ThULB). Members of Thuringian universities and research institutes can publish their data without costs. The publication of data in the DBT is recommendent if there is no possibility to publish the data in a discipline-specific repository or if there are reasons which speak against a publication of the data in these repositories. Further information can be found on our website of the DBTExternal link.

In contrast to data publication, long-term archiving is primarily intended to save data but not to make them available for others. The access to the data can be restricted in accordance with the requirements of the dataset.

A simple way to archive data is the transfer into a specific archive folder or better an archive server.

If there are no arguments against the public accessibility of the data, a publication in a suitable repository may be a favourable alternative to non-public archiving.

Some repositories like the Digitale Bibliothek ThüringenExternal link (DBT) or ZenodoExternal link provide ways to publish data with restrictions on the access.

Archiving ensures the long-term availability and usability of data. Therefore, the authenticity, integrity, accessibility and readability of the data have to be preserved. In addition to the bitstream preservation, the accurate rendition and interpretation of data have to be ensured despite the technological developments (e.g. data storage devices, file formats, software, etc.). This can be achieved by the migration of the data, e.g. on new storage devices or in new file formats. The use of open file formats (specifications are openly documented and replicable) makes the later re-use of the data easier. Furthermore, a comprehensive documentation with metadata is necessary for a loss-free and correct reproduction and interpretation of the data.

All mentioned aspects entail costs and a continuous funding for the archiving is necessary.

Many researchers cannot ensure all of these aspects by themselves and rely on the services of data archives.

Yes. Six of the 19 guidelines of the “Guidelines for Safeguarding Good Research Practice” (Code of Conduct, 2019) include regulations with regard to research data management.  One important novelty is that software is also regarded as research data.

Other regulations that can be inferred from the new guidelines are:

1. Research data* should be published in suitable archives/repositories according to the FAIR principles (under appropriate licence).
2. Research data* should be made publicly available in a persistent, citable and well documented manner for an appropriate time.
3. The documentation should be provided according to discipline-specific standards or suitable standards should be developed.
4. Methods for the sharing and publication of research data and the corresponding usage rights should be documented. If there are reasons that speak against the publication of research data, they should be clearly stated.

 (* incl. software, methods, materials)

Yes. The FSU Jena adopted The policy on the handling of research data at the Friedrich Schiller University Jenapdf, 170 kb · de and the Guidelines and recommendations on research data management at the Friedrich Schiller University Jenapdf, 316 kb · de in December 2016.

Further information can be found on our information page.

Research data may be protected by the copyright law. However, the criteria for the personal intellectual creation have to be fulfilled (perceptible form, personal creative work, intellectual content, specific character).

According to this criteria, raw measurement values are not protected by the copyright law but the results of the data analysis are. The status of structured research data (e.g. xml/rdf formats) is unclear and the legal situation has to be clarified for the specific cases. If you have questions regarding the copyright law, please contact the Rechtsamt de (legal office) of the FSU Jena.

Research data which are protected by the copyright law can only be re-used to a small extend without the permission of the author. Therefore, the conditions for the re-use of the published data should always be clarified by the authors. For this, authors can use appropriate licences. Creative Commons licencesExternal link (from version 4.0 on) are highly recommendable for research data. With regard to the FAIR principles, open licences (CC-BY, CC-BY-SA) should be used preferably.

Personal data include all information relating to natural persons. Special caution is required when handling personal data. Especially, data that is related to race, political/religious/philosophical beliefs or sexual orientation underlies strict regulations regarding data protection. This includes, among others, patient data, genetical information of persons but also survey data and interviews.

Data from such projects can only be published if appropriate measures were taken to ensure the protection of the personal information (e.g. restriction of access, anonymisation, pseudonymisation, aggregation).

In general, the Rechtsamt (legal office) of the FSU Jena de should be contacted to clarify the legal regulations for the acquisition, processing, storage and publication of the data and to develop the required documents.

In empirical education science, the demand of the funding agencies to publish research data can often be contradictory to the regulations for the protection of personal data. Therefore, special attention must be paid in this area to the handling of the data collected (especially personal data).

The Verbund Forschungsdaten BildungExternal link (VerbundFDB) provides access to information material, trainings and infrastructures regarding education research.