Researchers and staff from different agricultural institutions across the Philippines, India, Indonesia, Nepal, Tanzania, Benin, and Ethiopia successfully completed the online training on Good Practices on Managing Research Data and Basic Data Analysis from August 28 – September 8, 2023.
The first part of the training, aims to provide participants with basic good practices for managing data, which covers organizing raw data in spreadsheets, data cleaning, checking, and validation. Participants were be given basic knowledge and several hands-on exercises promoting good practices in managing research data.
Participants share their experiences during the course and how it is relevant to their current work. “From day 1 to day 3, all the materials the resource person delivered helped support my daily work as an assistant scientist. Before, I just did minimum management of my research data, like doing simple spreadsheets with no metadata and using Google Drive to share and store my research data. However, after this training, I know that research data management is more complex than that,” said Ms. Devanda Putri.
Another participant, Mr. Guy Marius Assogba, shares “The course on Good Practices in Managing Research Data is an opportunity for me as junior scientist to be aware about the fraud in research and to have a good knowledge about how to collect my data in good way.”
On the second week, the training focused more on data analysis, acquainting the participants with the principles of experimental design, basic experimental designs used in crop research, analysis of variance, correlation analysis, and regression analysis. It introduced the Statistical Tool for Agricultural Research (STAR), a user-friendly software that uses GUI created in Java and functions developed in R to assist crop scientists in the design and analysis of data.
Participants expressed their satisfaction with the training on the STAR software. Mr. Rajan Chaudhary said, “As far as online courses go, this is among the best I’ve taken. There is no coding knowledge required for STAR, which is great for those who fear intense coding languages for data analysis. Overall, the resource persons did their best to make things clear to the participants. Thanks for giving us exercises and home assignments to boost our confidence“.
The training used a blend of synchronous and asynchronous sessions with lectures, group discussions, and practical hands-on exercises.
IRRI Education offers a variety of learning engagement for all stakeholders in the rice-based agri-food systems.
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