Dataset supporting: 'A systematic map of cassava farming practices and their agricultural and environmental impacts using new ontologies: Agri-ontologies 1.0'

How to cite this Dataset

Hood, Amelia S C, Christie, Alec P, Sutherland, William and Shackelford, Gorm E (2022): Dataset supporting: 'A systematic map of cassava farming practices and their agricultural and environmental impacts using new ontologies: Agri-ontologies 1.0'. University of Reading. Dataset. https://doi.org/10.17864/1947.000429

Description

These data support a systematic map of scientific studies about cassava farming practices, which was made with the aim of identifying knowledge gaps and clusters. A secondary aim of the study was to develop a hierarchical classification system for [1] farming interventions, and [2] agricultural, economic, and environmental outcomes. This standardized classification system for agricultural metadata can facilitate dataset reuse and promote research efficiency across syntheses. Following our published protocol [2], we searched eight publication databases/repositories using the search string “cassava OR mandioca OR manihot OR manioc OR yuca” in December 2017. We screened 36,580 records at title and abstract and then at full text stage, and included publications that measured the impact of cassava farming practices on agricultural or environmental outcomes, including: yield, soil, water, wildlife, pests, pollutants, profits, and labour. We classified the resultant 1,599 publications by interventions, outcomes, study location, study years, and study design. We assessed coding consistency using Kappa scores. This map is available online via an interactive database: https://www.metadataset.com/ (registration required). The Kappa scores indicated that we successfully developed a consistent intervention and outcome ontology that can be applied to other systems.

Resource Type:

Dataset

Creators:

Hood, Amelia S C