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.
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Photo credit: Aalto University / Unto Rautio

Step I. Prepare data for publishing

Start preparing your dataset by choosing what data to publish. This could include:  

  • Data that is needed to replicate findings published in a journal/conference 

  • Data with long-term value that can be reused by the scientific community  

Typical types of data are:  

  • Measurement data from experimental research including raw and/or processed data  

  • Interview/survey data (if data is anonymized, see below)  

  • Software, research protocols and methods, see Software as a research outcome   

Before releasing your research data openly, make sure it is not subject to legal restrictions, such as privacy protection. Whenever in doubt, contact [email protected]. Reasons not to openly disseminate your data set include:  

  • Your data contains personal data collected from human subjects, and the data cannot be anonymized to protect the privacy of the subjects (see Handling personal data)   

  • Your research data is related to research outcomes that can be used commercially or industrially (see Publishing and commercialization)  

Step II. Upload your data to repository

We recommend publishing your data in scientific data journals or in reliable discipline-specific repositories, if such are available in your research community. In other cases, we recommend Zenodo as a general-purpose data repository. Here’s a more detailed list of options: 

Scientific data journals  

  • Scientific data journals describe sets of research data instead of presenting analyses and findings based on these data sets. Scientific data journals may be a good option if you have research data with long-term value. Multidisciplinary scientific data journals include Data in Brief and Scientific Data. Discipline specific data journals include Chemical Data Collections, Geoscience Data Journal and Journal of Chemical & Engineering Data.  

Discipline-specific data repositories  

General-purpose data repositories  

General-purpose repositories are not limited to any domain or discipline, but they accept any kind of research data. We recommend Zenodo as a general-purpose repository. Below are service descriptions for three repositories:   

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

To make your dataset understandable enough for reuse, write a good description for it to the repository.  

In the process of uploading the dataset to the repository, you will also need to choose the license for your data set. Creative Commons licenses are standard to define the terms of use for published datasets.  

Step III. Make your dataset known 

The best way to make your dataset known is to include a link to the dataset in the publication where this data was used. To achieve this please follow this process:  

  1. In order to first get the DOI (a unique identifier) for the dataset, you upload the data to a repository and instead of making it openly accessible, you restrict access to it (i.e. set an embargo)  

  1. In your publication manuscript you can then you can include this DOI as a reference to the dataset  

  1. You open the dataset (remove the restriction in the repository) after the publication is out  

After you publish your dataset, please send the link or a dataset identifier to[email protected]. Your dataset will be registered in Aalto Current Research Information System (ACRIS) for you. 

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

Links to research data management instructions

Follow these links to navigate through research data management instructions.

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Publishing and reusing open data

Overview and instructions to services for sharing and publishing research data

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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

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