FAQ Data Management
In this FAQ we try to answer a selection of the most important questions on research data management that we compiled over the last 5 years.
Data management planning (DMP)
In your proposal you outline the type of data that you will be collecting and how these will be made available for reuse, if applicable, after the research project ends. You can also account for costs for data management included in the budget. Some funders require you to contact data management support staff before submitting your full proposal.
Upon request, the Centre for Digital Scholarship can send you guidelines for a data management section in a research proposal and advise you on your full data management plan. Please contact us by sending an email to: firstname.lastname@example.org.
The Psychology Institute has its own template that you can find on the pages of the Research Committee.
The Centre for Digital Scholarship organizes workshops on how to write a DMP and advises on individual plans.
You only need to write one Data Management Plan.
Some funders allow you to use your institutional template. If not, you use the funder’s template.
Some funders made their template available in a tool called DMPOnline.
You can write the plan online and the tool will provide you with some specific guidance. You can also authorize members of the CDS Data Management Team to review your plan in DMPOnline.
You can contact the Data Management Team of the Centre for Digital Scholarship: email@example.com.
The Centre for Digital Scholarship provides information on FAIR data.
Additionally, we organize hands-on workshops on FAIR data and are happy to advise you on the steps to take from the start of your research project.
The Data Management Plan not only focuses on datasets that need protection, but also on the availability and reuse of all your data with a focus on the long term. In many cases, you can reuse the information throughout the different forms.
Your options for data storage may vary depending on factors such as size and sensitivity of the data or collaboration with partners outside the university.
Check the Leiden Research Data Services Catalogue to see what options you have or contact the Data Management Team.
There is no dedicated data storage for privacy sensitive data available at the university yet. Consult the privacy officer of your faculty to make sure that you will use the preferred location for your institute.
You are not required to make data containing personal information publicly available for reuse in a new study.
In principle, you will only share data outside of the project team, if your data do not reveal your participants' identity. However, if it is not possible to de-identify your data, you can still register information about the datset and a description of the confidential data in a public data archive, so that others can learn about the existence of the dataset.
In very specific situations it can be possible to share personal data with a broader audience, for instance when you show a video recording in class.
When asking your participants for consent, you must be as explicit as possible about your future intentions.
You can read more about informed consent for data sharing on the pages of our colleagues from Utrecht University.
Yes, the university network storage is backed-up on a daily basis. In Surfdrive the possibilities of recovering files are limited.
Not all disciplines have set standards but it can be worthwhile to look for similar examples in datasets from your field that have been deposited in data repositories, so that you get a good idea of what metadata can be applied.
The Data Curation Centre in the UK also provides a solid overview of metadata standards.
You can contact the Centre for Digital Scholarship for advice.
Sometimes metadata are produced by the instruments that you use and automatically integrated in the dataset. Another way of adding metadata is by adding a readme file in the same folder that contains the datasets. Also, a file name often contains information on the content of the file. When you upload your dataset in a data repository you will be asked to add metadata (such as creator, title, subject term etc.) to improve the findability of your datasets.
Data and Software Publishing
Publishing your data is one way of guaranteeing sustainable availability of your data, that is, if you publish it in a trustworthy repository. It also increases the visibility and findability of your research findings.
No, it does not. The Leiden Repository is dedicated to the archiving of publications only.
You can consult the Leiden Research Data Services Catalogue for an overview of trustworthy data repositories that you can use to publish your data or software, most of them without costs for small amounts of data. These repositories create a ‘persistent identifier’ (such as a DOI) that you use to link to the data in your publication.
Researchers from the Faculties of Social Sciences and the LUCL institute (Faculty of Humanities) can make use of Dataverse to publish their data packages.
If you publish a ‘dump’ of your code in an archive such as Zenodo your deposit will be assigned a DOI, to make sure that it can be properly cited; at the same time, versioning is possible, so you can still continue to work on the software. We recommend publishing software in Zenodo, and you can do so very easily by using your Github login credentials.
No, repositories do not accept privacy sensitive data. As a depositor, you are responsible for checking the data to make sure that all data have been sufficiently anonymized in order to protect your participants.
Funders usually require a license that allows for reuse of the data, but the choice remains yours. In many data repositories, the default license is CC BY or CC0.
We recommend a CC BY license. CC BY requires future users to cite your data, but it does not limit the possibilities for the re-use of your dataset. In this way, you maximize the impact of your dataset and the potential number of citations.
First of all, you should check your funder’s requirements. In most cases you can opt for an embargo period or an ‘upon request’ access mode, if you have good reasons not to make the data (immediately) publicly available. After publication or when your project is finished, you may no longer have the need for an embargo.
LUCRIS offers the possibility to register a dataset, that you have published. When you register the dataset, you choose publication -> other types -> dataset.
When you register a ‘regular’ publication such as an article in LUCRIS, you can also add the URL of any underlying dataset in the in a dedicated field ‘dataset’.
Please note that LUCRIS offers no option for uploading other file types than PDF, so make sure you archive or publish your data elsewhere.