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Research Data Management

When you are doing research, good data management practices and transparency are essential. This toolbox provides practical information and guidelines for both PhD students and researchers when working with research data.

Open Access and Open Science

Open Access publishing means that you make your publication freely accessible online to everyone without restrictions. The Vrije Universiteit believes that government-funded research should be available free of charge to as many people as possible. To that end, the VU Library offers a guide on how to go about Open Access Publishing.

Open Access publishing is one component of Open Science. The European Commission has defined open science as follows: “Open Science represents a new approach to the scientific process based on cooperative work and new ways of diffusing knowledge by using digital technologies and new collaborative tools. The idea captures a systemic change to the way science and research have been carried out for the last fifty years: shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process”. (Definition taken from Nationaal Programma Open Science.) This includes making openly available research data, methods and documentation where possible. As such, RDM and the practices outlined in this LibGuide are a precondition of Open Science. You can read more about Open Science in the Netherlands on the website of the Nationaal Programma Open Science and join the Open Science Community Amsterdam, the community of VU employees interested in Open Science (joint with the University of Amsterdam).

Publishing your data in a data journal

Instead of archiving research data in a data repository, you may choose to publish an article about your data collection. This is not necessarily common for all disciplines. Some examples of data journals where you can publish your data and dataset, are:

What is a persistent identifier?

A persistent identifier (PID) is a durable reference to a digital dataset document, website or other object. It is a kind of ISBN for digital files. By using a persistent identifier, you make sure that your dataset will be findable well into the future. A DOI or Handle are the commonly used PIDs. The data archiving options at the VU also offer different kinds of PIDs. For more information see: What identifier do I need?

Most data archives or repositories offer a persistent identifier and generate this automatically when research data are archived. Local repositories for sensitive datasets offer similar identifiers or codes. At the VU, the current local repository for sensitive datasets an datasets with personal data generates a DarkStor code.

Licensing the data

A data licence agreement is a legal instrument that lets others know what they can and cannot do with your research data (and any documentation. scripts and metadata that are published with the data). It is important to consider what kind of limitations are relevant. An important component can be a guideline on how people should cite the dataset. Other components could be:

  • Can people make copies or even distribute copies
  • Who should be contacted if you need access to re-use data
  • Etc.

In principle, Dataverse allows you to choose your terms of use. Some data repositories require you to use a certain licence if you want to deposit your data with them. At Dryad, for example, all datasets are published under the terms of Creative Commons Zero to minimise legal barriers and to maximise the impact for research and education. Some funders may also require that you publish the data as open data. Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and share alike (Open Knowledge International definition).

Additional websites and tools: