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Introduction to research data management and best practices

Properly managed research data creates competitive edge and is an important part of a high-quality research process. Optimal use and reuse of research data is a strategic goal of Aalto University. The objective is to produce data that is FAIR: findable, accessible, interoperable and reusable.

Research data are a valuable resource that often requires a lot of time and money to create. Thus, it is worthwhile to take some time to ensure that data is managed properly. Funding agencies increasingly require data management plans before funding research projects.

What part of data is published, when, and how data is curated, are strategic decisions of the principal investigator (PI). The PI takes into consideration agreements, commercial interests, policies and the law. Decisions are also made on the data repository chosen and whether to publish data and software. University services offer guidance for these decisions.

Please read more in the Aalto University Research Data Management Policy below.

The benefits of Research Data Management and Open Science:

  • Avoids preventable data loss
  • Allows you to find and understand the data quickly
  • Creates transparency of research and makes it easy to open/publish the data
  • Ensures the visibility of research and increases citations
  • Ensures you meet funders'/publishers' and legal requirements
  • Makes it possible to validate research findings
  • Facilitates collaboration
  • Enables data reuse and prevents duplication efforts
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 Storage services for 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 of personal data and research ethics sections.

One can use the most common national solution, Fairdata service IDA. Please, notice that also EOSC-service portal offers several services for common use. 

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 the future? Some hints and good practices are described in Data documentation, organization, and metadata section. Data organization and documentation are important tasks of data curation. FAIR principles give guidance for that. For example, proper versioning keeps track of changes and updates to data.

3. Publishing 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, requirements of funding agencies on open data are gradually arising. Therefore, it is important to plan publishing of the research data on the platforms, which are called repositories. More information is given in Publishing and reusing open data section. Data publishing is an important step towards future reuse of your research data.

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 Storage services for 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.

Recommendations

At the very least, you should:

Links to research data management instructions

Follow these links to navigate through research data management instructions.

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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.

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