Research Data / Open Data

Wherever research is conducted, research data is created. Research data refers to all digitally available data that is created during the research process or results from it.

[Translate to Englisch:] FreiDok plus
What is research data / open data?

"Research data is an essential foundation for scientific work. The diversity of this data reflects the wide range of different scientific disciplines, research interests and research methods. Research data might include measurement data, laboratory values, audiovisual information, texts, survey data, objects from collections, or samples that were created, developed or evaluated during scientific work." (DFG Guidelines on the Handling of Research Data)

The responsible handling of such (digital) data created as a precondition, product or result of the research process is an essential component of good research practice. Its long-term preservation and availability ensure the reproducibility of scientific work. Open data in the sense of the Open Definition refers to (research) data that can be freely used, reused and shared by anyone - if necessary under the conditions of a free licence.

Principles for handling research data

FAIR (Findable, Accessible, Interoperable, Reusable)

The FAIR principles define standards for the description, storage and publication of research data. They are intended to ensure that research data can be reliably reused by both humans and machines. The acronym FAIR stands for

  • Findable: The data is provided with a persistent identifier and human- and machine-readable metadata and is registered or indexed in a searchable resource.
  • Accessible: The data can be retrieved and downloaded via a standardized communication protocol. Descriptive metadata is also stored for data that is not directly available.
  • Interoperable: The data is available in a form that allows it to be exchanged, interpreted and linked to other data sets (semi-)automatically. This is achieved, for example, by using standardized formats, ontologies or vocabularies.
  • Reusable: The data is described in terms of its provenance. By using persistent identifiers and issuing standardized licenses, it can be reliably and legally cited and reused.

CARE (Collective Benefit, Authority to Control, Responsibility, Ethics)

The CARE principles emerge from work with data concerning indigenous communities and are complementary to the FAIR principles. More generally, the CARE Principles formulate principles of research and data ethics.

Infrastructures for research data

Researchers are free to choose suitable repositories for their research data. In most cases, supra-regional research data repositories specific to the respective academic field or community are recommended for storing, publishing and archiving the data. The Registry of Research Data Repositories (re3data) provides an overview of repositories worldwide.

German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur, NFDI)

The German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur, NFDI) is intended to systematically index data collections from and for science and research, make them accessible in a sustainable manner and initiate national and international cooperation. It is being set up as a network structure of 26 subject-based consortia. In the NFDI consortia, researchers, specialist societies and communities as well as infrastructure providers and projects work together to develop discipline-specific services, training courses and standards for handling data.

European Open Science Cloud (EOSC)

The European Open Science Cloud (EOSC) is the European Commission's most important infrastructure project for Europe-wide networked research data management. The project's aim is to provide researchers, developers, companies and citizens with a common, open and multidisciplinary environment in which they can publish, find and reuse data, tools and services for research, innovation and education purposes.

What does research data management involve?

Research data management lifecycle

Research data management is a central component of good research practice. It combines methodological, conceptual, technical and organizational decisions and measures to handle research data within its digital lifecycle and beyond. The following diagram illustrates the stages of the research data lifecycle, which begins with project planning and follows the research process through to the eventual reuse of the resulting data:

Figure: Nicolaas Bongaerts/Stefano Della Chiesa, Research Data Management Lifecycle, 25.04.2022, DOI 10.5281/zenodo.6602006, CC BY 4.0 International

Data management plan

A data management plan (DMP) describes and operationalizes the stages of the research data lifecycle with a concrete research project in mind. When submitting a funding application, many funding organizations expect the submission of a data management plan with binding statements on the data created or collected, its organization and quality as well as on storage and accessibility during the project and after its completion.

Research data management at the University of Freiburg

In 2022, the University of Fribourg adopted a "Policy on the handling of research data". It includes a commitment to the principles of open science and open data and defines the responsibilities of researchers and the university across the entire data lifecycle.

Based on the German reference model for strategy processes in institutional research data management ("Referenzmodell für Strategieprozesse im institutionellen Forschungsdatenmanagement", RISE-DE), the university continues to develop its services for researchers on the topic of research data management. Initiatives for research data management are currently coordinated within the university in the Research Data Management Group (RDMG).

Records of research data sets that have been published on a subject-specific repository, for example, can already be included in FreiDok plus. The FreiData research data repository, which is intended to provide members of the university with an institutional platform to publish data and research results and thus open up the research process as part of open science, is currently being set up. It is complementary to discipline-specific repositories and overarching infrastructure projects such as the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur, NFDI).

Further information
University of Freiburg