Data Management Plan (DMP) - Guidelines for researchers

1. Introduction

Managing and sharing research data as openly as possible is one of the principles of good scientific practice. The SNSF adheres to this principle, as stated in Article 47 of its Funding Regulations: in stating that "[…] grantees are obliged to make available to the public in an appropriate manner the research results obtained with the help of SNSF funding, […]". The SNSF has set out the criteria it expects funded researchers to meet in its Open Research Data Policy statement For the implementation of these principles, the SNSF favours a bottom-up approach. It provides best practice guidelines and gives each scientific community sufficient flexibility in defining and applying its own standards. In particular, the best way of managing and sharing data depends on the research field.

The aim of a Data Management Plan (DMP) is to plan the life cycle of data. It offers a long-term perspective by outlining how data will be generated, collected, documented, shared and preserved. The SNSF provides a template to help researchers complete their data management plan. Each project's DMP will refer to discipline specific standards and practices and thus its content may be different.

The SNSF expects that researchers share at least the data underlying their publications, but only to the extent to make the published results reproducible. This data should be shared as soon as possible, but at the latest together with the relevant scientific publication. Data can be raw or processed, depending on the project and the discipline. Datasets must always be carefully documented with associated metadata, such that other researchers understand how the data was collected, as well as under which conditions and how it can be re-used. If specific tools are needed to re-use the data, this needs to be documented and, if possible, the tools made available. In any case, the provided data and documentation (metadata) must be sufficient to ensure their reusability. Researchers are asked to explain in their DMP wherever these requirements cannot be met.

Data sharing – best practices

To facilitate the discovery, access, re-use and citation of datasets, it is important that the publication of research data follows a set of clearly defined and broadly applicable best practices. The FAIR Data Principles define a range of qualities a published dataset should have in order to be Findable, Accessible, Interoperable and Reusable (see Explanation of the FAIR Data Principles, Dokument auf Englisch). The SNSF expects researchers to share their data according to the FAIR Data Principles on publicly accessible, digital and non-commercial repositories. It is important to note that the FAIR Data Principles do not require researchers to share all their data without any restrictions. Rather they advocate applying a standard procedure when sharing research data for reuse, so that humans and computer systems can easily find, interpret and use them under clearly defined conditions. The FAIR Data Principles are being adopted by a growing number of research funding organisations (e.g. Horizon 2020, NIH).

2. The SNSF's Data Management Plan

To implement its Research Data Policy the SNSF requires information on the life cycle of data at the time when a grant application is submitted. In order to account for different data management practices between disciplines, the SNSF has defined minimum standards for the structure and content of the information to be provided.

2.1. How to submit a DMP

While completing their grant application on mySNF, researchers will be asked to provide information regarding their data management. The DMP form comprises four sections: (1) data collection and documentation, (2) ethics, legal and security issues, (3) data storage and preservation, and (4) data sharing and reuse. Sub-questions and online help texts will help researchers to complete the form (see details).

The DMP is an integral part of the grant proposal. The proposal can only be submitted once the DMP has been completed.

Some research projects do not produce or reuse any data. If this is the case, applicants do not have to complete the whole DMP form. However, they are asked to explain why they do not expect to generate or reuse any data in their proposed research.

Some data cannot be shared because applicants are bound by legal, ethical, copyright, confidentiality or other clauses. They will be asked to explain their specific constraints.

2.2. Assessment of the DMP

The submitted DMP is considered a notice of intention. Its content is assessed by the SNSF Administrative Offices for its plausibility and adherence to the SNSF policy on open research data. It is not part of the scientific evaluation process. Members of the Research Council or Evaluation Panel have access to the DMPs, but will not evaluate these documents. DMPs are not sent out for external review

Submission of a plausible DMP is a requirement for any transfer of funding. If there are shortcomings in the submitted information provided by the applicants, they will receive a "task" in mySNF to complete/amend specific sections of the DMP at the time of the funding decision.

2.3. Lifetime management

The DMP remains editable during the entire lifetime of the grant. Its contents can be adapted as the project evolves.

In any case, researchers will be prompted to update their DMP at the end of the grant. This updated version will be assessed together with the final scientific report. The SNSF Administrative Offices retain the right to request additional information and/or amendments to the contents of the final DMP.

The final version of the DMP will be made available on the SNSF's P3 database.This will increase the visibility and impact of the research outcomes by making it easier for other researchers to access and reuse the datasets.

3. Examples of data management plans

DMPs are very individual. They can be of various types and their composition can differ. The examples provided by the Digital Curation Centre (UK) show this diversity.

4. Eligible Costs

The costs of enabling access to research data that is collected, observed or generated under an SNSF grant are eligible if the research data is deposited in recognised scientific, digital data archives (data repositories) that meet the FAIR principles and do not serve any commercial purposes (IR 2.13). It is permissible to upload data to commercial repositories, but only the data preparation costs will be covered by the SNSF.

5. Examples of repositories that comply with the FAIR Data Principles and are non-commercial

Requesting that researchers apply the FAIR Data Principles in every detail is an ambitious policy. In addition, finding the "perfect" repository providing all necessary features to host FAIR data can be a challenge. To make the transition towards FAIR research data easier, the SNSF decided to define a set of minimum criteria that repositories have to fulfil to conform with the FAIR Data Principles (see checklists below).

Four repositories which accept datasets from different research fields and fulfill the SNSF requirements are shown here. It is, of course, possible to archive data on other (field-specific) repositories. Researchers can proceed as follows to ensure that the chosen repository is in line with the SNSF requirements (non-commercial, FAIR Data Principles).

5.1. Checklist to identify non-commercial repositories

The first step is to consult, where most repositories are listed.

  • Under the tab "Institutions", check if a commercial entity is involved in 'general' or 'technical' responsibility (categories "Type of institution" and "Type(s) of responsibility")
  • If not, SNSF considers the repository to be non-commercial (even if ‘funding’ or ‘sponsoring’ is provided by a commercial entity).
  • If yes, the SNSF considers the solution to be a commercial repository (see details)

If the repository is not listed on, the repository should be contacted to clarify this point. Researchers should also suggest that the repository be included in

5.2. Checklist to identify repositories complying with the FAIR Data Principles

Researchers should check if the repository is compatible with the FAIR Data Principles. The answer to each of the questions below must be "yes" (see the examples).

  • Are datasets (or ideally single files in a dataset) given globally unique and persistent identifiers (e.g. DOI)?
  • Does the repository allow the upload of intrinsic (e.g. author's name, content of dataset, associated publication, etc.) and submitter-defined (e.g. definition of variable names, etc.) metadata?
  • Is it clear under which licence (e.g. CC0, CC BY, etc.) the data will be available, or can the user upload/choose a licence?
  • Are the citation information and metadata always (even in the case of datasets with restricted access) publicly accessible?
  • Does the repository provide a submission form requesting intrinsic metadata in a specific format (to ensure machine readability/interoperability)?
  • Does the repository have a long-term preservation plan for the archived data?