Research data is any information gathered or generated in the research process, and that forms the basis for analyses, results and conclusions. Publishing open research data improves the transparency and reproducibility of research. Open data also enables others to reuse and cite the data in new research.
On this page, we present an introduction to how to publish and cite research data. For information about the support regarding research data available at the university, please refer to this resource at Medarbetarportalen where you can find guides for how to gather, analyse, store, publish and archive research data.
What is research data?
By publishing open data, other researchers can cite and reuse your work. This has the potential to increase the academic impact of data generation in itself, independent of other associated scholarly publications.
In the research policy bill from 2016 (Collaborating for knowledge, 2016/17:50), the Swedish government specified that the transition to open science, including open data, should be completed by 2026. This is in line with the ambition from the European Parliament and other prominent actors on the global stage.
There are several ways to publish your research data openly:
- Any data that is used in a scholarly publication can be published as an appendix or complementary material, either together with the associated publication or on an independent open data repository.
- Research data can be published in open data repository, either independently or coupled with a data paper that describes the published data in terms of e.g. content, method, origin and structure. There are many different data repositories available, some of which are general and other that are subject specific. At re3data.org you can find help to identify the best data repository for your needs.
When you publish a dataset, the author list does not have to be identical to that of the associated research paper. On CRediT, you can find more information about the correct contributor role taxonomy.
To facilitate reuse of your published data, consider using a Creative Commons licence. For licenses covering code and software, we recommend this resource: Choose a licence.
Data that can not be published openly
For legal and/or ethical reasons, some research data is not suitable to be published open. Examples of this are e.g. personal data that are covered by the GDPR legislation, classified data (OSL, SFS 2009:400) and trade secrets. If your data is of this kind, it can still be registered and indexed in repositories, together with relevant metadata and specifications for conditional release if applicable.
Benefits from publishing research data
Impact: Publishing data gives you more opportunities for impact (i.e., more citable documents).
Collaboration: Your open data can be the catalyst for more research collaborations.
Efficiency: As more and more research data is shared openly, the research community can focus on generating new data instead of wasting time and resources on generating the same data.
Research ethics: Sharing data increases the transparency and reproducibility in research.
Benefit to society: It is valuable in itself that publicly funded research is available to its ultimate funder, i.e., the public.
Complying with demands and recommendations: Funding organisations, publishers, academia and other actors often mandate or recommend the publication of open research data.
Citing research data
Research data can also be cited in the same way as articles in research journals. A prerequisite is that the dataset is provided with a persistent identifier such as a Digital Object Identifier (DOI) or Uniform Resource Names for National Bibliography Numbers (URN:NBN). Publication of research data can create more opportunities for researchers to acquire qualifications, such as citations and registered downloads. In this way it is possible to gain recognition for more contributions to the research process, and not just publications of articles.
DataCite is an organisation working to make research data citable, including by helping data archives assign DOIs to their datasets.
- Examples of data citing with DOIs (DataCite)
- “Fler citeringar med återbruk av data” (More citations with reuse of data), Swedish-language article in the Swedish Research Council’s web magazine, Curie.
In the autumn of 2012, Clarivate launched a citation index for research data, Data Citation Index. Clarivate has previously made available a scientific citation index for research publications, and Clarivate is the organisation that calculates the impact factors of journals.
"More Citations from reusable data", article in the VR paper Curie (in Swedish)
"Making data available in the research process", Article in Swedish from SND (Svensk Nationell Datatjänst)
Open access to research data
Research data is a valuable resource that often requires a lot of time and money to produce. That is why a growing number of research funding bodies demand that researchers who receive funding give thought to how the collected data will be taken care of, be documented and in what form it can be made available for future research.
On the basis of the European Commission’s recommendations to member states, in 2015 the Swedish Research Council submitted a proposal for national guidelines on open access to research information to the government. The vision for 2015–2020 is that all research data produced with public funds is to be made readily available. During these years pilot calls for proposals are to be implemented with requirements that the research data be made readily available.
It’s possible to upload the datasets in DiVA (Academic Archive Online) to make it readily available or to simply archive it. The dataset receives a unique ID (URN:NBN) and a persistent link that you can use to refer to the material in a publication. To make it easier to find research data, you can also link from publications in DiVA to datasets that are readily available in other databases.
In the re3data.org register, you can search for data archives in different subject areas.
In addition to DiVA, you can also make the data available in:
Data management refers to how the research material is handled, organised and preserved during the research process. Several research funding bodies today require that a data management plan be included in applications for funding, such as Wellcome Trust and the EU’s Horizon 2020 research and innovation programme. As from spring 2019, all who receive grants from the Swedish Research Council, must have a plan for how the research data generated within the project shall be managed. The plan must not be sent when applying for a grant, but it must be in place when starting a new project and be maintained.
A data handling plan (DHP) or data management plan (DMP) is an effective way to exercise control over data management. The data management plan is a formal document that should contain information about how data is collected and managed during the research project, and how it is taken care of afterwards. A DHP can facilitate collaboration and access to data and also clarify security issues. More information about data handling is available at the Swedish National Data Service (SND).
In 2018 the association of European research funding organisations, Science Europe, launched a framework for data management protocols to make it easier for researchers to administer their research data.
SHERPA/JULIET is a database that lists and provides information on research funding bodies.
Checklist för Data Management Plan (SND, Swedish National Data Service)
Data management (Horizon 2020)
Data Management Plans (Digital Curation Centre, DCC)