The DSSAT community has long emphasized the importance of relating model evaluations and applications to real world data. In recent years, we have welcomed interest in making datasets openly accessible and compliant with the FAIR principles whereby data are Findable, Accessible, Interoperable and Reusable (https://www.go-fair.org/fair-principles/). To this end, we have new initiatives to strengthen the ICASA Data Dictionary (ICASA DD) and to develop spreadsheet-based templates for documenting experiments. Both activities are now organized around github repositories hosted by DSSAT:
ICASA Data Dictionary: https://github.com/DSSAT/ICASA-Dictionary
Spreadsheet-based templates: https://github.com/DSSAT/Florida_Crop_BMP_Datasets
Ongoing work includes development of templates that are more closely aligned with the ICASA DD and include various tools to assist users in loading data into templates and exporting data to the CSM, other crop models, or applications such as artificial intelligence (AI).
