Encourage the widest use of open licences, where these are appropriate.
Open licenses

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Implementation options
Open licenses (e.g., Creative Commons) are widely promoted and required by funding agencies (e.g., Deutsche Forschungsgemeinschaft (DFG), German Federal Ministry of Education and Research (BMBF), European Union (EU)), adoption remains inconsistent across disciplines.
To encourage the widest use of open licenses, policymakers should prioritise awareness-raising, training, and clear requirements.
Policymakers should:
- Mandate the use of open licenses (e.g., Creative Commons (CC)) for publicly funded research outputs, with clearly defined exceptions for sensitive or restricted data.
- Develop machine-actionable licenses tailored for research data and digital objects, inspired by practices in the open-source community, to enable automated use and reuse.
- Ensure publicly funded software is released under open licenses and prioritise such software for open science platforms, including repositories, Current Research Information System (CRIS) systems, and publishing platforms.
Main hurdles and risks
Implementing open licenses faces several hurdles.
- While the necessity for machine-actionable open licenses is clear, research institutions cannot address the complex legal rights surrounding research data alone, requiring legislative or policy initiatives for effective regulation.
- Although mandates like Horizon Europe’s requirement for Creative Commons (CC) BY licenses and the European Commission’s use of CC licenses for publications demonstrate progress, extending these practices to research data, software, and workflows remains challenging.
- In public-private partnerships, concerns about confidentiality and intellectual property often hinder open licensing.
- Additionally, low awareness and understanding of licensing options among researchers further delay adoption, compounded by the diversity of needs across disciplines. Achieving a balance between harmonisation and respecting community-specific requirements is difficult.
- Strategic leadership, collaborative governance, and common best practices are essential. International models, such as NERC and the Australian Code, illustrate potential pathways but highlight the need for a coordinated global effort to address legal complexities and foster adoption.
Other Provisions in Pillar C: Responsibility, ownership and stewardship
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Foster, and require where appropriate, the adoption of good practice for research data and software management across the research system and work with communities of researchers, institutions, repositories, funders, and other stakeholders to support researchers in adopting coherent practices for management of research data and software.Learn more
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Promote, and require where appropriate, the inclusion of information about rights and licensing in the metadata of all research data and other research-relevant digital objects from public funding as part of the implementation of Research Data Management principles.Learn more
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Support scientific advancement by taking the steps where necessary to enable new uses of research data and other research-relevant digital objects from public funding, such as for artificial intelligence and text- and data-mining techniques.Learn more
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Promote access to research data and other research-relevant digital objects resulting from public-private partnerships in ways that helps ensure data collected with public funds is as open as possible while recognizing and protecting legal rights and legitimate interests of stakeholders, including private-sector partners.Learn more