“Recognizing the crucial role of open and effective data and information exchange to the Belmont Challenge, the Belmont Forum adopted open Data Policy and Principles based on the recommendations from the Community Strategy and Implementation Plan (CSIP) at its 2015 annual meeting of Principals in Oslo, Norway. The policy signals a commitment by funders of global environmental change research to increase access to scientific data, a step widely recognized as essential to making informed decisions in the face of rapid changes affecting the Earth’s environment….

Data should be:

Discoverable through catalogues and search engines
Accessible as open data by default, and made available with minimum time delay
Understandable in a way that allows researchers—including those outside the discipline of origin—to use them
Manageable and protected from loss for future use in sustainable, trustworthy repositories…

Research data must be:

Discoverable through catalogues and search engines, with data access and use conditions, including licenses, clearly indicated. Data should have appropriate persistent, unique and resolvable identifiers.
Accessible by default, and made available with minimum time delay, except where international and national policies or legislation preclude the sharing of data as Open Data. Data sources should always be cited.
Understandable and interoperable in a way that allows researchers, including those outside the discipline of origin, to use them. Preference should be given to non-proprietary international and community standards via data e-infrastructures that facilitate access, use and interpretation of data. Data must also be reusable and thus require proper contextual information and metadata, including provenance, quality and uncertainty indicators. Provision should be made for multiple languages.
Manageable and protected from loss for future use in sustainable, trustworthy repositories with data management policies and plans for all data at the project and institutional levels. Metrics should be exploited to facilitate the ability to measure return on investment, and can be used to implement incentive schemes for researchers, as well as provide measures of data quality.
Supported by a highly skilled workforce and a broad-based training and education curriculum as an integral part of research programs. …”