Practical guide for international harmonization of search data management
Quality research data are key elements of the research process. They should be available at all times, publicly and free of charge for possible reuse. In recent years, various stakeholders, from research funding agencies to publishers, have endorsed a concise set of principles, known as FAIR data principles: Easy to find, Accessible, Interoperable and Reusable.
The Practical Guide to International Harmonization of Research Data Management outlines the minimum requirements for data management plans (DMPs) and criteria for selecting trusted warehouses that comply with FAIR principles, and goes beyond them in areas such as data storage and archiving during the project and long-term preservation.
This guide is divided into three parts:
- Minimum requirements for data management plans
- Data description and collection or reuse of existing data
- Documentation and data quality
- Storage and backup during the search process
- Legal and ethical requirements, codes of conduct
- Data sharing and long-term storage
- Data management responsibilities and resources
- Criteria for selecting trustworthy deposits
- Assignment of unique and permanent identifiers (PIDs)
- Access to data and user licenses
- Implementation guidance containing detailed information and examples to guide the implementation of requirements and criteria in settlement policies.
The minimum requirements for DMPs and the criteria for selecting trustworthy warehouses can be used independently, but it is recommended that these two sets be taken into account when developing or updating an institutional or disciplinary data policy.
This Practical Guide to International Harmonization of Research Data Management is the French translation of the Practical Guide to the international alignment of research data management published in November 2018 by Science Europe, whose production was coordinated by the Science Europe Working Group on Research Data.
The French translation was carried out as part of the work of the Data College of the Permanent Secretariat for Open Science. This translation is published under a Creative Commons Attribution 4.0 license.