Research Data Management

Research data refers to data produced or utilised in scientific or artistic research that can be used to validate and, if necessary, repeat research results. This guide provides basic information on research data management and research data management planning at the University of Lapland. In addition, it includes recommendations for resources produced by other actors that can be consulted for more extensive and detailed information on the subject.

At the University of Lapland, management and opening of research data is informed by the University’s Data Policy (in Finnish). Making research data related to publicly funded published research openly accessible wherever possible is a prerequisite stated in the University’s data policy. Research data management and opening of research data must follow the Responsible Conduct of Research and guidelines for ethical research of the Finnish National Board on Research Integrity (TENK).

Support in research data management, opening of research data, and making a data management plan (DMP) is available by contacting research.library @ulapland.fi

For a quick introduction into the basics of research data management, watch the CSC's video on research data management and the FAIR principles. (CC BY-ND 4.0)

The purpose of research data management is to ensure that research data are easily accessible, interpretable, and appropriately protected during and after the research process. Proper planning and implementation of research data creation, storing, description and organisation is a prerequisite for this. Research data management has always been part of research, but the increasing steering and regulation in recent years has increased its visibility.

Proper research data management:

• helps you save time and effort
• facilitates your research and ensures its quality
• will function as a backup if necessary
• helps you gain merit as a researcher
• ensures that you meet the requirements of funders and the University of Lapland
• ensures data-secure processing of your datasets
• ensures data protection of your research participants
• helps you to agree on user and ownership rights of research data
• helps you to be prepared for the workload, costs, and software and equipment needs
• facilitates opening of the data for re-use
• makes the data easily accessible for others and renders it possible to refer to them
• ensures compliance with Responsible Conduct of Research.

Following the FAIR principles promotes quality of research and research datasets as well as re-use and openness of data. FAIR stands for findable, accessible, interoperable (i.e. something that can be transferred and combined) and re-usable. Opening of research data is not a prerequisite for compliance with the FAIR principles. The data can also partially satisfy the FAIR principles.

In practice, the FAIR principles can be satisfied, for example, by

• providing detailed descriptions of the data
• using open and durable file formats
• publishing the data and/or its metadata
• obtaining a persistent identifier for your dataset
• obtaining a license to determine re-use of the data.

Picture: Tampere University (CC BY 4.0.)

In addition to this guide, we recommend consulting the following resources in research data management planning.

General Finnish DMP-guidance

Data management guides

Videos and training materials

Funders' open science requirements