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Research Data Management: Funders' Requirements

Bringing together University resources and services to facilitate researchers in the production of high quality data.

At a Glance

An increasing number of funding bodies request or require that their funding recipients create and follow Data Management Plans (DMP).

Generally at the proposal stage a short DMP is required covering:

  • What standards will be used
  • How data will be shared
  • How data will be curated and preserved

During the project, generally 3-6 months post award, a full DMP is required. However, this is not a fixed document and should evolve throughout the course of the project.

Help@UCD: Horizon Europe Applications - Guidance on Research Data Management (RDM)

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Irish Funders' Data Management Requirements

An increasing number of funding bodies request or require that their funding recipients create and follow plans for managing data, storing or preserving it in the long term, and sharing some, or all data products with the public. Funding agencies require varying degrees of planning and explanation at the grant application stage.

Areas which funding bodies may ask you to consider are:

  • Managing the data you generate – you will be asked to consider how you will document and maintain the research you produce, such as describing raw data and saving files correctly.
  • Sharing your outputs – many funders now require open access of research outputs. You may be required to state if your data will be accessible through channels such as data repositories or archives.

National Framework on the Transition to an Open Research Environment

The National Framework on the Transition to an Open Research Environment has been developed as the first step in a process to create a National Action Plan for the transition to an open research environment in Ireland.

Implementation will be detailed in a National Action Plan which will be commenced with all relevant stakeholders in 2019 and reviewed annually. The National Action Plan will cover concrete objectives and indicators to measure progress on the transition to open research for all disciplines, including scoping potential cost implications and the allocation of responsibilities.

The following sections are of relevance to Research Data Management:

Enabling FAIR research data

15. The following research data management principles are confirmed and supported:

i) Findable, Accessible, Interoperable, and Reusable (FAIR) data contribute to research integrity and reproducibility.

ii) Those involved in each stage of the research process should have the capacity and skills necessary to enable FAIR data.

iii) Prior planning is essential to ensure that research data are managed effectively through all stages of the research cycle, from creation to long-term preservation.

iv) Research data should be interoperable across disciplinary boundaries to enable unrestricted sharing of reusable data between different systems and domains.

v) A robust citation mechanism for referencing data is necessary for research validation and to make data findable and accessible.

16. Data management planning is required as a standard practice from the earliest stage in the research process. Data management plans,14 required as part of that standard practice, should address the following core requirements: data description and collection or reuse of existing data; documentation and data quality; storage and back-up during the research process; legal and ethical requirements; data sharing and long-term preservation; and data management responsibilities and resources.

17. Datasets should be made easily identifiable through persistent identifiers, accompanied by standardised metadata, including funder names and grant numbers.

i) Where appropriate, datasets should be linked to other datasets and publications through recognised mechanisms.

ii) Additional information should be provided to enable the proper evaluation and reuse of data.

iii) Interoperability standards should be applied to facilitate the reuse of data within and across disciplines and to support automated processes acting across large, heterogeneous datasets.

18. Research data should be ‘as open as possible, as closed as necessary’:

i) Research will become and remain findable, accessible, interoperable, and re-usable within a secure and trusted environment, through national and international digital infrastructures, including, where appropriate, within the European Open Science Cloud (EOSC).

ii) Research data may be restricted for justifiable reasons, such as commercial exploitation, confidentiality, security, protection of personal data, the achievement of the project’s aim, and incompatibility with the further exploitation of the research results, or other stated legitimate grounds. Shared metadata are especially important for restricted data and should be made accessible if possible.

iii) Taking into account technological developments (including dynamic [real-time] data), the licensing terms used should not unduly restrict text and data mining of research data resulting from publicly funded research, in accordance with and without prejudice to the applicable copyright legislation.

iv) Any data, know-how, and/or information, whatever its form or nature, which is held by private parties in a joint public/private partnership prior to the research action will not be affected by this policy.

19. Funders and institutions will include, in grant conditions and other support for research, their requirements for data management plans and for data sharing, together with details of their mechanisms for monitoring compliance.