In-person training report on: Agronomic Data Collection and Management Tools for Better Agricultural Research

Abstract

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.