2021/09/28 by Alexander Zech, Timur Bazhirov
Computer Science · Decision Sciences · Engineering · Materials Science · Physics and Astronomy · #Artificial intelligence #Categorization #Computer science #Cover (algebra) #Data science #Distributed and Parallel Computing Systems #Engineering #Machine Learning in Materials Science #Scientific Computing and Data Management #Software #cond-mat.mtrl-sci #cs.CE #cs.DB #cs.LG
paper · pdf · doi:10.1021/acs.jcim.2c00112
21 pages, 4 figures, 2 tables
arxiv created 2021/09/28 · openalex publication_date 2022/03/01 · arxiv updated 2022/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.