材料数据类型

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
A. O. Erkimbaev, V. Yu. Zitserman, G. A. Kobzev
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引用次数: 0

摘要

基于人工智能方法对多年研究成果的应用,存储和处理大量数据的技术开启了材料科学发展的新阶段。与选择具有特定性质的材料的经验方法相比,大量的异质数据与强大的分析设施相结合,使我们能够显著扩大研究的范围和生产率。重点是这些数据的细节,这主要决定了现代材料科学中信息技术的水平和能力。它们的主要特征被揭示出来,保证了创建和使用各种材料所需信息的充分完整性。这些特征包括材料微观结构和技术数据的覆盖范围以及性能;大量的定性信息;以及半结构化数据类型,即缺乏规则的表示方案。以一些基础设施项目为例,考虑到材料科学数据的数量、逻辑结构和格式,考虑了材料科学数据管理的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Materials Data Typology

Materials Data Typology

Technologies for storing and processing vast amounts of data have opened a new stage in the development of materials science, based on the application of artificial intelligence methods to the results of many years of research. Large volumes of heterogeneous data combined with powerful analytic facilities have allowed us to significantly expand the range and rate of production of research in comparison with empirical methods of selecting materials with specified properties. The emphasis is placed on the specifics of these data, which mainly determines the level and capabilities of information technologies in modern materials science. Their main features are revealed, which guarantee sufficient completeness of the information needed for creating and using various materials. These features include coverage, along with properties, of data on the microstructure and technology of the material; a large amount of qualitative information; and semistructured data type, i.e., the absence of a regular presentation scheme. Using the example of a number of infrastructure projects, the potential of management of materials science data taking into account their volume, logical structure and format are considered.

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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
期刊介绍: Automatic Documentation and Mathematical Linguistics  is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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