The advent of data-driven science in the 21st century brought about the need for well-organized structured data and associated infrastructure able to facilitate the applications of Artificial Intelligence and Machine Learning. We present an effort aimed at organizing the diverse landscape of physics-based and data-driven computational models in order to facilitate the storage of associated information as structured data. We apply object-oriented design concepts and outline the foundations of an open-source collaborative framework that is: (1) capable of uniquely describing the approaches in structured data, (2) flexible enough to cover the majority of widely used models, and (3) utilizes collective intelligence through community contributions. We present example database schemas and corresponding data structures and explain how these are deployed in software at the time of this writing.
翻译:21世纪数据驱动科学的出现带来了对组织完善的数据和相关基础设施的需要,从而能够促进人工智能和机器学习的应用。我们介绍了旨在组织基于物理和数据驱动的计算模型的多样化景观的努力,以便利将相关信息作为结构化数据的储存。我们应用了面向目标的设计概念,并概述了开放源合作框架的基础,即:(1) 能够以结构化数据具体描述方法,(2) 足够灵活,能够覆盖大多数广泛使用的模式,(3) 通过社区贡献利用集体情报。我们举例介绍了数据库的模型和相应的数据结构,并解释了在编写本报告时如何在软件中使用这些模型和数据结构。