Quality assurance

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FTA’s Sentinel Landscapes datasets have been peer-reviewed to ensure that they meet CGIAR’s ‘quality of research for development’ (QoR4D) framework. This framework, developed with strong methodological contributions from FTA, comprises criteria for relevance, credibility, legitimacy and effectiveness.

To read more about our peer-review process for data quality, click here.


The Sentinel Landscapes datasets have been independently evaluated as contributing to a well-defined research question important to forests, trees and agroforestry, and to FTA’s Theory of Change. The Sentinel Landscapes datasets also contribute new knowledge on forests, trees and agroforestry.


The credibility of the Sentinel Landscapes datasets has been externally verified. The datasets belong to FTA partners – and can be used by FTA.

The Sentinel Landscapes datasets have been generated through a rigorous research design; they are complete, curated and cleaned. The datasets, the underlying methods and related findings are robust, and sources of knowledge are dependable and sound.


The Sentinel Landscapes datasets have been assessed as meeting the criteria for legitimacy. Data have been collected following both Free Prior Informed Consent (FPIC) and the research ethics guidelines of FTA, ensuring the underlying research process is fair and ethical and perceived as such, including proper representation of all involved and consideration of interests and perspectives of intended users. Gender considerations, and thus a gender lens, is reflected in the data collected.


The Sentinel Landscapes datasets and related products and services are accessible and well positioned for uptake and use (by researchers and stakeholders), including capacity development and proper support to the enabling environment. Sentinel Landscapes data on the FTA website are also available and accessible on the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) interoperable repository site, Dataverse. Data are also described by sufficient metadata (CG-Core).

If you use the Sentinel Landscapes data in any way, we would be happy to hear from you and support the visibility of your work by publishing a data story on your research. To submit a data story, click here.

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