Manage & share

Although 4TU.ResearchData is aimed at the long-term preservation, findability and accessibility of data and software at the end of the research project, effective data management practices start at an early stage.

If you have followed good research data management in the planning phase and throughout the course of a research project then your data will be well-organised, clearly documented and exist in open (non-proprietary) or common file formats.

This will make sharing your data relatively easy when the time comes, although it is never too late to implement good data management.

FAIR principles

The FAIR Principles describe how data can be organized and documented so they are more Findable, Accessible, Interoperable, and Reusable by other users and computer systems. In practice, preparing and sharing your data in line with the FAIR Data Principles enable higher visibility and reuse potential for your research. Depositing data in a data repository such as 4TU.ResearchData is a very good and easy way to make them FAIR.

Findable: your data should include metadata and a persistent identifier, to make it discoverable.
Accessible: data and metadata should be retrievable through a free and open communications protocol. Metadata should always be available, even if data is not.
Interoperable: metadata should use controlled vocabularies, be machine-readable and include references to other metadata. Data should use open formats whenever possible.
Reusable: metadata should conform to standards for greatest reusability. It should be clear to humans and machines alike. Data should also come with a clear and accessible licence to regulate reuse.

Software can also be made FAIR, see the five recommendations for FAIR software.

At 4TU.ResearchData, we encourage and support researchers to apply FAIR Principles to their datasets by providing the following features:

  • Set a DOI (Digital Object Identifier) to each published dataset or software item to make it findable.
  • Support for open and standard file formats making data interoperable.
  • All datasets, except for those that are restricted, are accessible to everyone and there is no need for special protocols to download and obtain the data.
  • Metadata are always openly accessible, even if the data are restricted or under embargo.
  • The metadata of datasets and research software published in 4TU.ResearchData follows the DataCite metadata schema, one of the most used metadata standards to guarantee its interoperability. The metadata model contains required, recommended and optional fields to make your dataset more findable and reusable. All the data and software items have a clear and accessible data usage licence to facilitate its reuse.
  • Controlled vocabularies, community standards, or ontologies are used where possible, making data interoperable and exchangeable with other data and systems.

Data Management Planning

Having a data management plan (DMP) is essential for your research project. A data management plan is a document that describes how the data will be generated or used within a given project, and how they will be shared upon completion of the research project.

A good DMP helps to manage your data more efficiently and improves the integrity and impact of your research. In addition, planning for good data management from the start reduces the risk of data loss, data breach, or other threats that could render the data illegible or unusable.

In addition to the benefits of having a data management plan, sometimes you might also be required by your institution or funder to create one.

Please check the policies and guidelines at your home institution or seek advice from your institution’s Data Steward or RDM Support. Institutions often offer specific tools, templates, and support for creating a data management plan.

Including 4TU.ResearchData in your data management plan
For describing your data management and sharing practices, 4TU.ResearchData facilitates compliance with access, metadata, licensing, and archiving requirements.
Please include 4TU.ResearchData in the appropriate sections of the data management plan to satisfy the data sharing requirements of funders.

Please contact us at [email protected] if you have any questions.

Reserve a DOI before publishing your dataset

You may need to obtain a DOI for your draft dataset before publication. For example when you want to publish your dataset at the same time as your associated paper. Reserving a DOI enables you to integrate the DOI into your paper that is still in the publication process.

Below are the steps to get your reserved DOI:

  1. Go to your Dashboard page and click the Add new dataset button.
  2. Add descriptive metadata.
    The reserved DOI for the dataset can be found in the DOI reservation field.
  3. Click Save draft once you have completed the form.

Please note that the reserved DOI is inactive, and will only resolve once your dataset is published.

When your paper is accepted and published, return to your draft dataset, add a reference to the paper and ensure metadata and files are complete.
Click Submit for review to complete the upload process. As soon as your dataset is published, the DOI will go live and the citation in your paper will be linked to the dataset.

Share your dataset with a private link

You may need to share your dataset (e.g. for peer review purposes) before it is actually published.
To do this, go to your My datasets page and click the private link icon (chain) to the far right of the dataset title. Or find the private link feature on top of the dataset’s Edit dataset page.

You will be directed to the Private link page. Click the button Create new private link which opens a form:

  • Select the duration of the private link, and optionally the purpose of the link and who the link will be shared with.
  • Check the box Hide authors and affiliation if the link is shared for blind (anonymous) peer review.

When the form is completed, click the Activate private link button.
You will be able to send the resulting private link to, for example, the peer reviewers.

Please note that this temporary private link is not a permanent identifier like a DOI and should be substituted with the dataset DOI at the point of final manuscript submission.
The DOI reserved for your dataset will not change at any point after the dataset has been created.