Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we 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 information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as 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 will 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. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

中文翻译：

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迈向新一代农业系统数据、模型和知识产品：信息和通信技术

长期以来，农业建模在模型实施方面一直存在碎片化问题。开发了许多模型，存在很多冗余，模型通常耦合性差，模型组件重用很少，并且通常难以应用模型为农业部门生成真正的解决方案。为了改善这种情况，我们认为需要一个开放、自我维持和忠诚的社区来共同开发农业模型和相关数据和工具作为公共资源。这样的社区可以受益于信息和通信技术 (ICT) 的最新发展。我们研究了如何利用这些发展来设计和实施用于农业生产系统的下一代数据、模型和决策支持工具。我们的目标是评估相关技术的成熟度，预期的发展，以及使农业建模社区受益的潜力。所考虑的技术包括协作开发的方法以及让利益相关者和用户以跨学科的方式参与开发的方法。我们的定性评估表明，作为一项整体研究挑战，需要解决数据源的互操作性、模块化粒度开放模型、应用程序参考数据集和特定用户需求分析方法，以允许农业建模进入大数据时代。这将实现更高的分析能力和新数据源的综合使用。整体农业系统建模需要快速采用和吸收最先进的数据和 ICT 技术，重点关注受益人的需求并为开发其模型应用程序的人提供便利。这种采用需要广泛采用一组最佳实践作为标准操作程序。