Research Data

Research data are data acquired or collected for scientific work.

Research data serve as evidence to confirm a hypothesis, support scientific conclusions, and validate findings. Data can appear in many forms: digital, printed, or physical materials. Data collection methods include experiments, observations, surveys, but data can also be derived from existing sources such as statistical databases, texts, manuscripts, archival materials, photos, and artworks.

Open research data are research data made available with open access. Alongside data, it is equally important to provide access to software, algorithms, protocols, methods, workflows, etc., necessary for data processing.

However, open research data is not an end in itself. The entire open science paradigm is based on the desire to make science reliable, ethical, and accessible to all stakeholders. For this, data should be published as FAIR data, enabling other researchers to reuse already collected data.

According to FAIR principles, research data should be understandable to both humans and machines and be: findable, accessible, interoperable with other information systems, reusable by other researchers. FAIR principles are explained in detail in the document FAIR Principles.

You can assess your knowledge using the FAIR-Aware online tool.

Researchers are not left alone in this process—they are supported by repositories that ensure long-term preservation of data.

Many research datasets cannot be opened due to sensitive content, but they should still be properly managed and preserved as FAIR data to allow sharing with other researchers under confidentiality agreements.

It is important to realize that open data is not always FAIR data, and FAIR data may not be open data, and neither says anything about the scientific quality of the data!

The European Commission’s slogan as a science funder is: “As open as possible, as closed as necessary”, but in recent years this has been complemented by the requirement that data must always be FAIR: “As open as possible, as closed as necessary, but always FAIR!”

Science Europe Research Data Management

Science Europe’s Practical Guide to International Alignment of Research Data Management provides guidance for organizations, disciplines, and individual researchers. Originally published in 2019 and widely adopted, it was updated in January 2021 to include guidance for assessing Data Management Plans (DMPs).

Elixir Europe. FAIR Guide for Natural Scientists.

A web-based, open, and continuously updated resource for natural scientists with guidelines to make data Findable, Accessible, Interoperable, and Reusable (FAIR).

CESSDA Data Management Expert Guide (DMEG) for Social Scientists

DMEG was created by European experts to help social scientists make their research data findable, accessible, interoperable, and reusable (FAIR).

Open Science Passport

Part of the “Open Science Passport,” this guide addresses challenges related to opening source code used in research and understanding software’s role in the open science ecosystem.

Open Science – Source Code and Software

This brochure, based on the Passport for Open Science, addresses challenges related to opening source code and software produced in research.