Agricultural System Data, Models and Knowledge Products for the Big Data Era

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, they are often poorly coupled, their component re-use is rare, and it is frequently difficult to apply them to generate real solutions for the agricultural sector. To improve this situation, the study argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in ICT. Examines how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Evaluates relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. Technologies considered encompass methods for collaborative development involving stakeholders and users in a transdisciplinary manner. Suggests that an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This can enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. It requires the widespread uptake of a set of best practices as standard operating procedures.