Models of everywhere revisited: A technological perspective
Models of everywhere revisited: A technological perspective
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DOI：
10.1016/j.envsoft.2019.104521
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发表时间：
2019-12-01
影响因子：
4.9
通讯作者：
Towe, Ross
中科院分区：
文献类型：
--
作者：
Blair, Gordon S.;Beven, Keith;Towe, Ross
“无处不在的模型”的概念最初是在2000年代中期引入的，作为一种推理一个地方的环境科学的手段，改变了基本建模过程的性质，从使用一般模型结构的过程转变为建模成为一个关于特定地方的学习过程，特别是捕捉那个地方的特质。在某种程度上，这是一个简单的概念，但在另一个层面上，它是一个丰富的多维度概念框架，涉及以下关键维度：无处不在的模型，一切的模型和任何时候的模型，不断根据最新的证据进行重新评估。这是一个令人信服的方法，有可能处理认识上的不确定性和非线性。然而，这一办法尚未得到充分利用或探讨。本文根据技术的最新进展，研究了无处不在模型的概念。该论文认为，在最初提出时，技术是一个限制因素，但现在，随着物联网、云计算和数据分析等领域的进步，许多障碍已经得到缓解。因此，现在是时候重新审视在实际条件下的无处不在的模型的概念，作为跨学科努力解决剩余的研究问题的一部分。本文最后确定了研究议程的关键要素，应该支持这种实验和部署。
The concept 'models of everywhere' was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and non-linearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment.