Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.
Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.
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DOI：
10.1016/j.agsy.2016.10.002
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发表时间：
2017-07
影响因子：
6.6
通讯作者：
Wheeler TR
中科院分区：
文献类型：
--
作者：
Antle JM;Basso B;Conant RT;Godfray HCJ;Jones JW;Herrero M;Howitt RE;Keating BA;Munoz-Carpena R;Rosenzweig C;Tittonell P;Wheeler TR
本文提出了新一代农业系统模型的想法，可以满足不断增长的最终用户社区的需求，一组用例举例说明。我们设想新的数据，模型和知识产品，可以加速创新过程，这是实现可持续的地方，区域和全球粮食安全的目标所必需的。我们确定理想的功能模型，并描述了一些潜在的进步，我们设想的模型组件及其集成。我们提出了一项实施策略，将模型开发的“竞争前”空间与知识产品开发的“竞争空间”联系起来，并通过公私合作建立新数据基础设施。具体的模型改进将基于对现有模型的进一步测试和评价、模块模型组件和集成的开发和测试以及模型集成平台与新的数据管理和可视化工具的联系。NextGen数据和模型可以加速实现可持续系统和实现全球粮食安全目标所需的创新。我们设想新的数据和模型与支持用户定义的信息需求所需的新知识产品兼容。我们的设计策略涉及数据、模型和知识产品开发的“竞争前”和“竞争”空间。我们确定了学科模型组件及其集成的潜在进展，以解决关键用例。
This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a “pre-competitive” space for model development to a “competitive space” for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools. NextGen data and models could accelerate innovation needed to achieve sustainable systems and meet global food security objectives. We envision new data and models compatible with new knowledge products needed to support user-defined information needs. Our design strategy involves “pre-competitive” and “competitive” spaces for data, model and knowledge product developments. We identify potential advances for disciplinary model components and their integration to address key Use Cases.