FAQ
Do you have any questions? We have answers relating to the following topics:
General FAQs
How can I reach you?
You can contact us via our contact form.
What is research data?
Research data refers to ‘[...] data that is generated as part of a research project, e.g. by means of quellenforschung, experiments, measurements, polls or surveys.’ (DFG 2009; own translation)
What is research data management?
Research data management means the handling of (primary) research data. This involves measures that ensure the sustainable availability of the data for use. In this context, it is important that the storage, documentation, description and archiving of the data be planned at the earliest possible stage, preferably at the start of the research project. Ideally, the plans should be documented in the form of a data management plan.
What advantages does research data management have?
- Some sources of funding (e.g. ERC Horizon Europe) are only available for projects for which a data management plan can be presented.
- Requirements relating to research data that may apply for funding schemes are covered by professional RDM.
- Redundant work (e.g. repeated familiarisation with the data) is avoided by means of suitable documentation and preparation of the data.
- If data is requested as part of a review process, it is already prepared for such purposes by data management.
- Professional, standardised RDM processes reduce future efforts if you or a third party subsequently use the data.
- The risk of data loss is minimised through RDM measures such as data documentation, data backups and suitable long-term archiving. This way, data can be reused even decades later.
Can you help me understand and fulfil the requirements regarding data management set by my funding institution(s)?
Yes, we can. We are happy to help you identify and fulfil the exact requirements. Please find further information on our page on data management plans (DMPs).
I do not want to put in a great amount of additional effort in order to fulfil these requirements. Can you facilitate this work for me?
We cannot promise that it will be easy but we will do our best to make it as easy as possible for you. To do this, we will give you access to tools and information that will help you better manage, store and share your research data.
Can I get personal consultation regarding the requirements for my DMP?
We’re happy to advise you personally. Just contact us via email or our contact form. We will then arrange an appointment in order to assist you in handling your research data based on your needs.
What do the FAIR principles stand for?
The FAIR principles (Findable, Accessible, Interoperable, Reusable) serve to ensure sustainable research data management (RDM) by preparing and storing data and the corresponding metadata in a way that allows them to be subsequently used by others.
FAQs on data (management)
I am worried that data will be lost in the case of a change of personnel. How can I make sure that does not happen?
Staff turnover is not unusual in laboratories. As every individual is responsible for their own data, it can be difficult to keep everything together. We will gladly help you establish a sustainable system for storing your entire laboratory data. Why not have a look at our electronic laboratory notebooks?
I save my data in Excel spreadsheets. Is this sufficient?
Data analysis: while you are actively analysing your data, Excel might be the most convenient place to do so. However, Excel file formats change regularly, which might mean that you will no longer have access to your data years later.
Spreadsheet programmes vs databases: if you maintain various fields for your data sets and would like to search for complex combinations of those fields, spreadsheets might not be the best solution. You can use a simple database that includes a more sophisticated search function. We can help you decide whether this is necessary for your purposes. We can also help you set up a simple database.
As file formats change over time, as is the case with Excel, not everyone might be able to read the relevant files in all cases. Therefore, the use of comma-separated formats (.csv) is best suited for exchanging and archiving data.
Do I have to use metadata?
Metadata is information that describes your data. Over the years, you have probably been collecting metadata in a laboratory notebook. Who conducted the experiment? When was the experiment conducted? What are the findings from the experiment? Which samples were used? What were the conditions of the experiment? And so on.
Metadata is important for everyone – including yourself – who would like to examine and use your data files in the future. Imagine a file with 40 columns and 7,000 rows of numbers that only contains cryptic abbreviations for headers. Or a folder with numerous images that are only designated as ‘IMG_2764’, for example. Such data is not helpful to anyone.
The use of consistent, standardised terminology clearly specifies what you mean and facilitates the search for information of a specific kind among numerous data sets or automated processing of large volumes of data sets.
I would like to integrate the strengthening of data management skills into my syllabus. Can you assist me in doing that?
We believe that it is never too early to start applying proper data management. We will gladly give advice on how you can include advanced data management methods in your syllabus and, if you want us to, we will also visit you in class. Feel free to contact us.
FAQs on data management plans
What is a data management plan?
A data management plan is a document that describes which type of data you will collect over the course of your research, how you will describe and manage the data, who is responsible, how you would like to share data and where you will store your data for the long term. You have probably already considered these issues in the past but possibly never officially documented them.
Do you have any tools to help me compile a data management plan?
We will give you access to RDMO. This tool can be used to create data management plans and also provides support for the structured planning, implementation and management of your research project.
How can I get access to RDMO?
Please contact Sonja Hendriks, who will be happy to help you with accessing and using RDMO.
Will you review my data management plan for me?
We’re happy to look over your data management plan with you. Just contact Sonja Hendriks. Please allow an appropriate amount of time for us to review your plan.
Are there sample data management plans?
In addition to DMP templates, e.g. for the different research sponsors, there are also published DMPs, which you can find via Zenodo, for example. Please find an overview here.
FAQs on sharing data
I keep hearing I have to share my data. Is that true?
That depends, in part, on the third party funding your research or the director and on your data. Carefully check the policies of your funding institution.
We are happy to help you find out to what extent the policies of your funding institution apply to your research project. If they do not contain any specifications, you should consider sharing data that supports published articles or that could potentially be reused by others, including software code.
Can you propose a simple way for me to share my data?
Use a repository to publish your data.
I do not know whether I can publish my data as it contains patient data or other sensitive data or because I have made an agreement with my external funding provider (licence agreement). Is that a problem?
Funding institutions understand that certain sensitive data cannot be shared. You should give reasons why you cannot share some or all of your data in your data management plan.
FAQs on legal aspects
Do I own the copyright on my data?
Copyright only protects the form of a work, not its content. Therefore, the copyright only applies to the manner in which the data is presented. If it is presented in writing or graphically, the texts and images can be protected by copyright. The findings and data themselves, on the other hand, are not protected. The same is true for ideas, methods and doctrines as these are free and thus not protected by any copyrights – unless they are patented technological inventions or protected utility models.
Moreover, a minimum level of individuality and novelty must be achieved in order to attain the threshold of originality. This is a prerequisite for a copyright to apply. Therefore, research data is usually not subject to any copyright as it does not attain the required threshold of originality. Case histories, questionnaires/responses and descriptions of experiments are therefore not covered by copyright.
Nonetheless, it is recommended to initially treat research data as if it were in need of protection in accordance with the German Copyright Law (UrhG) as the intellectual effort required for it to apply may be given in some cases. However, this can only be determined by assessing each individual case.
Please find further information on the topic of copyright in the field of research data here.
Am I allowed to publish my data?
The publication of data may be prohibited under specific circumstances. The most important prerequisite for publishing data is that you have comprehensive ownership rights to the data. Furthermore, there is data that must be treated confidentially, e.g. personal data. For such data to be published, the data subjects must give their consent and the data may have to be anonymised.
Who else has a right to make decisions regarding the sharing or publication of data?
In research, you do not always work on your own. In such cases, you must be aware that co-researchers, your employer, the project initiator, your research sponsor or contractual partners in the private sector may have rights to your data. The contractual situation defines who has to be involved in decisions on the sharing or publication of data. Findings from research during which you were bound by instructions are usually owned by your employer or sponsor.
Which data protection regulations must be taken into consideration?
Personal data is subject to strict requirements regarding its collection, use and forwarding. Sensitive and personal research data can be shared in an ethically correct and legal manner. To do so, the applicable laws (EU GDPR, the old and new German Federal Data Protection Act (BDSG alt/BDSG neu) and the relevant state data protection act) must be complied with.
To process personal data, it is indispensable to obtain prior consent from the data subjects. RatSWD, the German Data Forum, provides recommendations on the topic of informed consent and templates for consent forms.
For archiving, provision and publication, a limitation of purposes must be defined from the start. Information that can be linked to an identified or identifiable individual must be anonymised in order to protect the individual’s identity. There are different ways to anonymise personal data.
Instructions on anonymisation are available from the Research Data Centre for Education (FDZ Bildung) and the DIPF.
Furthermore, there is a tool that helps you anonymise your research data: the Amnesia tool is provided by the OpenAIRE project for this purpose.
The principles of necessity and data minimisation generally apply. This means that as little personal data as possible is to be collected, used or processed.
Please find further information on data protection here.
Do I have control over the further use of my data by third parties?
Many aspects of use, such as the form and manner of use, can only be regulated by means of relevant contracts. The use of standardised licences such as Creative Commons or Open Data Commons is suitable for this purpose.
Which licences are there and which should I use?
As most research data is not in itself protected by any law, it is recommended to use licences. A licence establishes a contract regarding the use of the research data.
Please find a helpful overview on the topic (in German) on the forschungslizenzen.de website.
The Research Data Repository (RADAR) has compiled a table containing the existing CC licences and published it under a CC-BY 4.0 licence.
Use of the CC-BY licence is particularly advisable if you would like to apply the FAIR principles.
What must be taken into consideration with regard to employment contracts?
Employment contracts should include clauses stating that the contracting parties grant their future employer at least basic rights of use of the data generated as part of their research activities. The rights and types of use must be explicitly specified in this context.