Research Data Management (RDM) and Open Science

Good research data management enables open science. Aalto University provides services, instructions and support to help researchers manage their data well. These pages are a collection of instructions and services available at Aalto, with links to selected external instructions added on.

Any data-related requests may be sent to [email protected], which is read by a team of data experts (IT specialists, legal counsels, researchers, information specialists) who can answer your questions or direct the questions to the right specialists.

Data Management Life Cycle

Best Practices for Research Data Management

Whenever you work with the research data or you start a new research project, the following aspects should be planned:

1. Storage and sharing of the research data with collaborators

One always has to estimate the size of the data collected or produced during the project and think where the data will be stored. It is also important to think about possible security level to access your data and regular backups. More information can be found in Sharing, storing, and archiving of the research data section. 

Noteworthy, personal/sensitive and confidential data require a more careful approach when one chooses the platform for their storage and sharing. More information can be found in handling personal data and research ethics sections.

2. Organization and documentation of the research data

Even such an obvious question as organization and documentation of the research data requires careful planning with the key question: Will I be able to find and understand my data in 3 years? Some hints are good practices are described in Documenting, organizing and metadata of research data section.

3. Opening of the research data

Providing access to the research data becomes a general practice to validate scientific results and make the science fully transparent. Furthemore, funding agencies requirements on open data are arising year by year. Therefore, it is important to plan opening of the research data beforehand. More information is given in Publishing and reusing open data section.

4. Preservation of the research data

One has to consider what will happen with the data when the project is ended. Availability of the research data after the research project can be important not only right after the project, but also in 20-30 years. Thus, it is important to preserve the research data and ensure the access to it. More information can be found in Sharing, storing, and archiving of the research data section. Another way of preserving the data could be uploading it to repository. Check Publishing and reusing open data section for more details.

Learn more on research data management

Take a look at these detailed guides to learn how to manage your research data from planning your research to publishing results.

Aalto University RDM

About research data management and open science

Research data management is important to prevent losing valuable data.

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Data Management Plan (DMP)

A Data Management Plan (DMP) is a formal document that specifies how research data are handled during and after a research project. DMP identifies key actions to ensure that research data are of a high quality, safe, sustainable and, if possible, also accessible and reusable.

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Storage services for research data

Store your data in a service that enables backups, confidentiality or collaboration as needed.

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Data documentation, organization, and metadata

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

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Publishing and reusing open data

Overview and instructions to services for sharing and publishing research data

Personal data

How to handle personal data in research?

Recognize whether you are processing personal data and follow these instructions to handle it correctly.


Publishing and commercialization – Can I have both?

When following the guidelines presented in this page, it is possible to both commercialize and publish your research results.


RDM training material

There is a variety of training materials targeted to improve data management skills and knowledge of both researchers and support personnel.


Data support


Data agents and data advisor

Data Agents are researchers who work to improve data management in their department, school, or unit.

Contact info

Data support contacts

Contact interdisciplinary team in [email protected] to help you with your research data management needs.



Group work at Aalto University (photo: Aino Huovio)
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