Practical steps to publish the research data
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
Consider submitting your data to discipline-specific, community-recognized repositories when possible. To find a data repository, you can start with these services:
List of approved data repositories by journal Open Research Europe
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.
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.
Check the separate page on commercialisation: Publishing and commercialisation – Can I have both? Read more about Licensing research data at Aalto University.
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:
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)
In your publication manuscript you can then you can include this DOI as a reference to the dataset
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
- ARTS/Department of Media: (Digital) Humanities and Media Labs Around the World
- BIZ/Department of Management Studies: Project Data: Industrial Innovation in Transition - coded interview data
- CHEM/Department of Chemistry and Materials Science: USPEX 9.4.4/CRYSTAL17 interface
- ELEC/Department of Electronics and Nanoengineering: Simulated Self-user Shadowing for Mobile Phone Antennas at 28 GHz and at 60 GHz
- ELEC/Department of Electronics and Nanoengineering: Plane-wave propagation path data from wideband MIMO channel sounding in an urban microcellular scenario
- ELEC/Metsähovi Radio Observatory: Metsähovi Radio Observatory public solar database
- ELEC/Department of Built Environment: Data from: Forest loss in protected areas and intact forest landscapes: a global analysis
- ENG/Department of Built Environment: ActiveAge data (AAGE-2015)
- ENG/Department of Built Environment and SCI/Department of Computer Science: A collection of public transport network data sets for 25 cities
- SCI/Department of Neuroscience and Biomedical Engineering: Maps of subjective feelings
Links to research data management instructions
Follow these links to navigate through research data management instructions.
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.