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Agricultural Production Data by Commodity for Congo (2014-2018)

<p><strong>Description</strong>: This dataset represents a detailed extraction of agricultural production volumes and cultivated area statistics for staple commodities in the Republic of Congo. The data is sourced from the 2018 national and departmental statistical directories published by the Congolese National Institute for Statistics (INS). These statistics have been compiled and made available on the INS website, with specific access links at <a href="https://ins-congo.cg/annuaire-statistique-du-congo-2018/" target="_new">National Statistical Directory 2018</a> and <a href="https://ins-congo.cg/annuaires-statistiques-du-congo/" target="_new">Departmental Statistical Directories</a>.</p> <p><strong>Scope of Data</strong>: The dataset encompasses data from 2014 to 2018, covering both departmental (administrative level 1, ADM1) and district (administrative level 2, ADM2) levels. The granularity of the data depends on the availability within the accessed directories. It focuses exclusively on staple agricultural commodities, omitting horticultural productions but includes certain arboricultural commodities.</p> <p><strong>Project Context</strong>: This data extraction is part of the <a href="https://www.cirad.fr/dans-le-monde/cirad-dans-le-monde/projets/projet-pudt-congo">PUDT Congo</a> project. </p> <p><strong>List of Commodities Covered</strong>:</p> <ul> <li>Avocado</li> <li>Banana</li> <li>Bean</li> <li>Cassava</li> <li>Cocoa</li> <li>Coffee</li> <li>Ginger</li> <li>Maize</li> <li>Mango</li> <li>Palm oil</li> <li>Peanut</li> <li>Pineapple</li> <li>Plantain</li> <li>Rice (paddy)</li> <li>Safoutier</li> <li>Sesame</li> <li>Sweet potato</li> <li>Taro</li> <li>Voandzou (Bambara groundnut)</li> <li>Watermelon</li> <li>Yam</li> </ul> <p><strong>Data Collection and Processing</strong>: Data were extracted from the aforementioned sources and processed to ensure accuracy and relevance for analytical purposes.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0