“Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical).”
Concordat on Open Research Data, published on 28 July 2016
The SNSF values research data sharing as a fundamental contribution to the impact, transparency and reproducibility of scientific research. In addition to being carefully curated and stored, the SNSF believes research data should be shared as openly as possible.
The SNSF therefore expects all its funded researchers
- to store the research data they have worked on and produced during the course of their research work,
- to share these data with other researchers, unless they are bound by legal, ethical, copyright, confidentiality or other clauses, and
- to deposit their data and metadata onto existing public repositories in formats that anyone can find, access and reuse without restriction.
Research data is collected, observed or generated factual material that is commonly accepted in the scientific community as necessary to document and validate research findings.
SNSF guidelines for researchers
The SNSF has elaborated guidelines for researchers concerning the Data Management Plans (DMPs).
SNSF regulations
The regulations related to the SNSF policy on Open Research Data can be found in the Funding Regulations and in the General Implementation Regulations.
Data repositories
Finding the "perfect" repository providing all necessary features to host FAIR data is challenging. To make the transition towards FAIR research data easier, the SNSF decided to fix a set of minimal criteria that repositories have to fulfil to conform with the FAIR data principles.
FAIR Data Principles
FAIR is a set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable.
Data management monitoring 2017 and 2018
How are researchers implementing the SNSF guidelines? We analysed approx. 1500 applications. The results after two years are encouraging.
Report
Implementation of Science Europe’s recommendations
Science Europe investigated to what extent several member organisations acted on its recommendations on research data management, issued in January 2019. The SNSF contributed to the report.
Report
Landscape and cost analysis of data repositories
This study, jointly commissioned by the SNSF and swissuniversities, examined the data sharing and reuse behaviour of researchers in the Swiss community in 2018.
Science Europe practical guide on RDM
Science Europe has published two sets of recommendations on Research Data Management. As a member of Science Europe, the SNSF supports this initiative.
SNSF Workshop on Open Data in Science
At an international workshop on 14 September 2015, the SNSF discussed the foundations of Open Research Data strategies. The workshop focused on three main areas: (1) Potentials and Challenges: Researchers' Perspective, (2) Policies and Measures: Positioning of Science Funding Agencies and (3) Solutions: Effective Data Storage and Curation.
Workshop report
Concordat on Open Research Data
On 28 July 2016, the four main UK funding agencies launched a concordat that proposes a series of clear and practical principles for working with research data.
Concordat on Open Research Data
Amsterdam Call for Action on Open Science
The Call for Action was the result of the conference "Open Science - From Vision to Action", which took place in Amsterdam on 4/5 April 2016, on the occasion of the EU presidency of the Netherlands.
Amsterdam Call for Action on Open Science
Horizon 2020: Open Data Pilot
Since January 2017, all researchers submitting a project proposal in the context of Horizon 2020 have automatically been included in the Open Data pilot.
FAIR Data Management in Horizon 2020
Science Europe Guidance Document
Science Europe proposes a pragmatic solution for the preparation and control of Data Management Plans (DMPs) through the concept of Data Domain Protocols (DDPs).
OECD Paper on Business Models for Sustainable Research Data Repositories
This document provides a set of recommendations for developing sustainable business models for research data repositories.
CESSDA Data Management Expert Guide
The CESSDA Data Management Expert Guide is intended to help researchers to make their research data Findable, Accessible, Interoperable, and Reusable (FAIR). Although primarily aimed at the social sciences, this guide may be useful for researchers in many disciplines.
CESSDA Data Management Expert Guide
SNSF "Grant Offices Event"
Slides presented during the SNSF "Grant Offices Event" on the 26th and 28th of April 2017
Presentation Grant Offices (PDF, updated 10 July 2017)
Digital Curation Centre
The Digital Curation Centre (DCC) is a centre of expertise in digital curation. The DCC provides case studies, online services and training programmes.
Digital Curation Centre
Data Management and Sharing Guidelines Issued by UK Data Archives
UK Data Archives have published guidelines for researchers on how to manage and share research data.
UK Data Archive – Managing and Sharing Data (PDF)
The P-5 Programme 2017-2020 "Scientific information"
The P-5 Programme of swissuniversities is the continuation of the SUC P-2 programme which aims to bring together the currently disparate efforts of the higher education institutions to curate data and make it accessible.
re3data.org
re3data.org is the largest and most comprehensive registry of data repositories available on the web. It has grown steadily since its launch four years ago to cover a wide range of disciplines from around the world.
re3data.org
Peer Reviewers’ Openness Initiative
Scientists have launched an initiative to make open research an integral part of publishing data. They have stated that they will not act as reviewers whenever open data sharing is not stated.
CoreTrustSeal
CoreTrustSeal proposes a certification for trustworthy data repositories.
CoreTrustSeal
DataCite
In order to give credit to a data set that has been re-used in another paper it needs to be citeable, which calls for persistent identifiers. DataCite is a non-profit organisation that aims to develop and support methods of finding, identifying and citing data.
DataCite