When we process applications, assess and follow up projects

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• Applicants for research and innovation funding
• If you receive a remuneration from the Research Council
• Systems we use
• Publication of who has been awarded funding
• Member of the Research Council's External Appeals Committee
• The Research Council's use of artificial intelligence (AI)

Applicants for research and innovation funding

What is written here also applies to international collaborations/joint calls.

In order to process applications, assess and follow up projects that have received funding, and to control how the funds are used, we need to process personal data about the applicant's contact person and other people involved. We also process your peronal data when we provide guidance in connection with application processing and project follow-up.

The information that is stored depends on your role. Essentially, we store:

• Name
• National identity number, D-number or equivalent assigned to foreign citizens
• Gender
• Email address
• Position
• Place of work
• Role in the project
• Country (foreign users)

We processe personal data based on Article 6(1)(e) of the GDPR, cf. the national supplementary legal basis in Section 2 of the Articles of Association of the Research Council of Norway, the Public Administration Act and the Regulations for Financial Management in the State, as application processing, supervision and project follow-up are part of the official authority invested in us.

The Research Council has a legal basis for further processing of this data because the processing is necessary to comply with a legal obligation or to perform a task carried out in the public interest or to exercise official authority vested in us, cf. Article 17(3)(b) of the GDPR. Further processing is also necessary for statistical purposes, cf. GDPR Article 17(3)(d). Erasure of the data follows the internal guidelines on the erasure of personal data in the grant administration.

In some cases, we also process personal data based on consent in line with GDPR Article 6(1)(a). As an applicant, you have the opportunity on My page to freely choose whether you want us to contact you with relevant information in connection with, among other things, events, and receiving surveys. Consent can be withdrawn by unchecking the box. Your personal data will not be used further.

More about national identification number

A national identification number does not constitute sensitive personal data and is not subject to confidentiality obligations.

The Research Council has a legal basis in Section 12 of the Personal Data Act, cf. Article 6(1)(e) of the GDPR, cf. the supplementary basis in Section 6.3.8.2 of the Regulations for Financial Management in the State, to collect national identification numbers for persons carrying out work on projects funded by the Research Council. This enables us to verify that duplicate funding is not paid for the same work carried out by the same individual.

More on special categories of personal data

In some cases, we collect special categories of personal data, such as health data in connection with you taking statutory leave.

The processing of this data is necessary in order for the Research Council or you as a data subject to be able to fulfil your obligations and exercise special rights in the area of labour law, social security law and social law, cf. Article 9(2)(b) of the GDPR.

If you receive remuneration from the Research Council

If you are an employee, expert, board member or receive a remuneration from the Research Council, we store information that is necessary for you to be able to receive the remuneration. 

This includes national identification number or, where applicable, a D-number, bank account number and gender.

For scientific experts, we will also record information related to previous assessment assignments.

The information to be able to pay remunerations is stored in Unit4, which is our system for financial management. The information is also used to be able to report to the government.

The Research Council processes personal data based on Article 6(1)(c) of the GDPR; Chapter 5.2 of the Regulations for Financial Management in the Central Government.

Systems we use

For applicants, we store the personal data on My RCN web or on My page, depending on which electronic application system you use, and in the archive system Documaster.

To find new experts, we can use several different online sources, such as the Google Scholar author search tool, Web of Science and Scopus.

The archive system

As a general rule, the Research Council cannot delete information contained in documents that are of archival value and subject to a record-keeping obligation, and which must also be submitted to the National Archives once the archives are no longer in active administrative use. The Research Council may only dispose of documentation that is not required to be preserved, or individual information for which the National Archives has granted permission for disposal pursuant to Section 13 of the Archives Act and Sections 43 and 44 of the Archives Regulations.

Publication of who has been granted funding

The Research Council will publish the application results in a separate section on the call for proposal on rcn.no. We publish who receives funding, how much they will receive and what the funds will be used for, as well as the name of the project manager.

Our legal basis for processing this is Article 6(1)(e) of the General Data Protection Regulation, which gives us the authority to process data when it is necessary to perform a task in the public interest.

Member of the Research Council's External Appeals Committee

The Research Council publishes the members of the external appeals committee. We publish your name and place of work. Our legal basis for processing this is Article 6(1)(e) of the General Data Protection Regulation, which gives us the authority to process data when it is necessary to perform a task in the public interest.

The Research Council's use of artificial intelligence (AI)

We use AI in our electronic application processing systems. Here, machine learning is used to analyse applications and categorise them into panel groups, find the most suitable referees/experts as evaluators and predict various examples for the applications. The model is trained on previous years' projects and case officers' markings. The input data thus contains personal data related to project participants that are named in the applications.