In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research
Agronomy research and development can improve yield, yield quality, and profitability; yield stability and risk reduction; utilization of resources efficiency (nutrients, water, and labor); and soil health. To boost crop productivity and agronomic benefits, these need to be integrated and combined...
| Autores principales: | , , , , |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/137433 |
| _version_ | 1855520283860926464 |
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| author | Attaher, Samar Atassi, Layal Al-Shamaa, Khaled Devkota Wasti, Mina Kumari Nangia, Vinay |
| author_browse | Al-Shamaa, Khaled Atassi, Layal Attaher, Samar Devkota Wasti, Mina Kumari Nangia, Vinay |
| author_facet | Attaher, Samar Atassi, Layal Al-Shamaa, Khaled Devkota Wasti, Mina Kumari Nangia, Vinay |
| author_sort | Attaher, Samar |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Agronomy research and development can improve yield, yield quality, and profitability; yield stability
and risk reduction; utilization of resources efficiency (nutrients, water, and labor); and soil health. To
boost crop productivity and agronomic benefits, these need to be integrated and combined with data
from various sources for input into analytical models and decision support systems. By leveraging data
pools, georeferenced datasets, and multivariate data sources, collaborative activities and data sharing
across stakeholders provide insights efficiently. In this sense, it is critical to improve agronomic
research techniques and contexts by utilizing digital tools that enable researchers to develop and
share digital data sets that are FAIR (findable, accessible, interoperable, and reusable). When data is
shared in accordance with the same community-agreed-upon standards, it is easier to reuse it
throughout the data life cycle, and innovation is accelerated, as is the ability to deliver insights and
management options to stakeholders, including the ultimate beneficiaries, who are often poor
farmers. While the culture of data sharing is expanding, agriculture continues to lag in terms of making
data interoperable and reusable, necessitating a significant investment to integrate and demonstrate
the value of data that complies with the FAIR concept. |
| format | Informe técnico |
| id | CGSpace137433 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | CGSpace1374332026-01-17T02:04:29Z In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research Attaher, Samar Atassi, Layal Al-Shamaa, Khaled Devkota Wasti, Mina Kumari Nangia, Vinay agricultural research data collection training report Agronomy research and development can improve yield, yield quality, and profitability; yield stability and risk reduction; utilization of resources efficiency (nutrients, water, and labor); and soil health. To boost crop productivity and agronomic benefits, these need to be integrated and combined with data from various sources for input into analytical models and decision support systems. By leveraging data pools, georeferenced datasets, and multivariate data sources, collaborative activities and data sharing across stakeholders provide insights efficiently. In this sense, it is critical to improve agronomic research techniques and contexts by utilizing digital tools that enable researchers to develop and share digital data sets that are FAIR (findable, accessible, interoperable, and reusable). When data is shared in accordance with the same community-agreed-upon standards, it is easier to reuse it throughout the data life cycle, and innovation is accelerated, as is the ability to deliver insights and management options to stakeholders, including the ultimate beneficiaries, who are often poor farmers. While the culture of data sharing is expanding, agriculture continues to lag in terms of making data interoperable and reusable, necessitating a significant investment to integrate and demonstrate the value of data that complies with the FAIR concept. 2024-01-09T18:15:35Z 2024-01-09T18:15:35Z Report https://hdl.handle.net/10568/137433 en Open Access application/pdf Samar Attaher, Layal Atassi, Khaled Al-Shamaa, Mina Kumari Devkota Wasti, Vinay Nangia. (3/9/2023). In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research. |
| spellingShingle | agricultural research data collection training report Attaher, Samar Atassi, Layal Al-Shamaa, Khaled Devkota Wasti, Mina Kumari Nangia, Vinay In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title | In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title_full | In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title_fullStr | In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title_full_unstemmed | In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title_short | In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research |
| title_sort | in person training report on agronomic data collection and management tools for better agricultural research |
| topic | agricultural research data collection training report |
| url | https://hdl.handle.net/10568/137433 |
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