Practical steps to publish the research data

Publishing the underlying research data increases citations to your journal articles and other publications. Follow these instructions to get maximum impact with reasonable effort.
The image is from Aalto University material bank.

Examples of datasets from different disciplines which are published in trusted repositories and have a detailed description 

Step I. Prepare data for publishing

(1) Check what data you can publish

Aalto University community follows the principle “as open as possible, as closed as necessary”. Some limitations in opening the research data are possible if you have:

  • Personal data or personal sensitive data which cannot be anonymized (more information can be found from handling personal data section)
  • Confidential data
  • Research outcomes which can be commercially or industrially exploited (more information can be found from Publishing and Commercialization section)

(2) Choose data for publishing

Start preparing your dataset by choosing what data to publish and preserve. Some options include:

  • At minimum, the data that is needed to validate your results
  • Everything that is needed to replicate a study
  • Everything that is potentially useful for scientific community

Dataset could include:

  • Measured/measurement data from experiments including raw and/or processed data
  • Interview/survey data if data is anonymized
  • Software, research protocols and methods

Check the link below to learn more about making software open i.e. how to make your software citable, what license to choose for your software, etc.

The image is from Aalto University material bank.

Software as a research outcome

In many disciplines, researchers develop software as part of their research work. Software can either be a primary academic output to be widely used, or a byproduct of getting other work done.


To maximise the impact of your dataset and make it FAIR (Findable, Accessible, Interoperable, Reusable), it is important that you provide all necessary details to reproduce your results and/or reuse the dataset. Therefore, it is important that you document your data during the research projects and attach these files to the dataset so that description of the dataset is understandable for researchers in your discipline. 

For more information about FAIR, look at the principles:

Check the link below to learn more about good practices for data documentation.

The image is from Aalto University material bank.

Data documentation, organization, and metadata

Metadata describes the research data. Information about the creator, license, relevant dates, and summary statistics can all be metadata.


Step II. Upload your data to repository

(1) Choose repository

We recommend using a reliable discipline-specific repository to maximize impact of your dataset. If a suitable discipline-specific repository is not available, we recommend Zenodo as a general purpose data repository.

Check the link below to learn more about data repositories and other publishing options like data journals.

The image is from Aalto University material bank

Data publishing repositories

Data publishing repositories used in Aalto University


(2) Upload your data to the repository

Once dataset is prepared, it is time to upload it to the repository. You will get a persistent identifier to your dataset (DOI, URN or similar), making it findable and citable.

How to upload a dataset to Zenodo (video, 3'55")

Remember to add your ORCID iD when you publish dataset. More information can be found in Researcher Identification and Research Profiles section. 

    (3) Describe your dataset in repository

    To ensure that your dataset will be found and it is understandable enough for reuse, write a good description of it to the repository you have chosen.

    Computer screen with several windows open, showing cylindrical shapes on topmost windoe and three-dimensional grid structure underneath it. Photo by Mikko Raskinen.

    Describing datasets in the data repositories

    Make a brilliant description to maximize re-use, citation and findability of your dataset.


    (4) Choose the license for your data set

    The Principal Investigator is responsible for choosing the appropriate license. When choosing the license, comply with the possible restrictions on openness, e.g. project agreements and confidentiality of data. If there are no limitations to make the data open, choose the license that maximises the re-use of your data.

    Creative Commons licenses are standard licences used to define the terms of use for datasets. The Creative Commons license CC BY 4.0 is compulsory for publicly funded research data published in a data repository, compliant with the requirement of Open data directive, implemented in Finland with the national law Laki julkisin varoin tuotettujen tutkimusaineistojen uudelleenkäytöstä. Please note that Open data directive does not concern software.

    CC BY 4.0 allows sharing, copying and redistributing and adapting the material for any purpose, even commercially. The terms of the license require users to give appropriate credit to the authors, so authors of datasets will always get the citations.

    Check the separate page on commercialisation:

    Publishing and commercialisation – Can I have both?

    To license a dataset that has been created in other than externally funded projects, the creators have to make  written agreements on the ownership and licensing of the data. In research projects receiving external funding, data ownership is transferred to Aalto University and thus licensing is possible without extra agreements.

    Comprehensive information about the CC licenses

    Tool to help you in selecting the proper CC license

    The CC license information and tool are translated to several languages. Scroll to the end of the page to see the language options.

    Read more about Licensing research data at Aalto University

    Step III. Make your dataset known

    (1) Add the identifier of the dataset to your publication

    To open an underlying dataset together with a publication, follow this process:

    1. Upload data to a repository and set an embargo to it to first get the DOI
    2. Then use the DOI to cite the dataset in your publication
    3. Open the dataset after the publication is out

    (2) Register the dataset to ACRIS

    After you publish your dataset, send the link or a dataset identifier to [email protected]. Your dataset will be registered in Aalto Current Research Information System (ACRIS) for you. ACRIS collects research outputs of Aalto researchers and functions as the metadata catalogue of datasets. The results are reported to departments and schools. The future metrics on openly accessible data will be based on the metadata of data that is collected in ACRIS.

      Links to research data management instructions

      Follow these links to navigate through research data management instructions.

      Aalto univerisity library

      Publishing and reusing open data

      Overview and instructions to services for sharing and publishing research data

      People talking with each other

      Research Data Management (RDM) and Open Science

      Properly managed research data creates competitive edge and is an important part of a high-quality research process. Here you will find links to support, services and instructions for research data management.

      This service is provided by:

      Research and Innovation Services

      Did you find what you were looking for? If not, please contact us.
      • Published:
      • Updated:
      URL copied!