Research Data Management Guide

At the beginning of a research project, even before starting to collect or generate data, it is useful to plan how the data will be managed: what software to use, how to organize and store the data, privacy issues, and consent agreements that will influence what can be done and which data can be shared in the future. This set of considerations forms the Data Management Plan (DMP). The DMP is a document that describes which research data will be created, how they will be managed during and after the project, and the various responsibilities involved.

Most research funding bodies, including European funding programs, require that grant recipients, in addition to making resulting research articles available through Open Access, also create a DMP from the beginning of the project. Any reasons that may limit or prevent open access to the data or parts of it (such as confidentiality, security, intellectual property rights, etc.) must be carefully documented in writing.

However, even informally outlining your plans and project guidelines can make your life easier, especially if you plan to reuse the data or manage it collaboratively with colleagues. Research data management practices should aim to produce reusable data in accordance with the FAIR principles: the data must be Findable, Accessible, Interoperable, and Reusable.

The objectives of data management are to:

Save time by reducing the duplication of efforts
Identify and control potential risks, such as data loss or misuse
Ensure data integrity and quality
Guarantee that data remains accessible and understandable both now and in the distant future
Ensure adequate resources are available (e.g., storage space, staff support)
Increase the dissemination and reuse of data
Clarify the necessary budget (for data curation, storage, and management)

Further information on research data management can be found in the subsections of this guide and the list of suggested readings below.