使用语义网技术对位错动力学数据进行建模
Modeling Dislocation Dynamics Data Using Semantic Web Technologies
AI总结：
本文提出利用语义网技术，通过本体标注对位错动力学模拟数据进行建模，扩展并对齐了多个领域本体，并构建了知识图谱DisLocKG及SPARQL端点以实现高效灵活的数据表示与查询。
摘要：
材料科学与工程领域的研究侧重于材料的设计、合成、性能和表现。被广泛研究的一类重要材料是晶体材料，包括金属和半导体。晶体材料通常包含一种独特的缺陷，称为“位错”。这种缺陷显著影响多种材料特性，包括强度、断裂韧性和延展性。近年来，研究人员通过实验表征技术和模拟（例如位错动力学模拟）投入了大量精力来理解位错行为。本文介绍了如何通过本体对数据进行标注，利用语义网技术对位错动力学模拟的数据进行建模。我们扩展了现有的 Dislocation Ontology，添加了缺失的概念，并将其与另外两个领域相关本体（即 Elementary Multi-perspective Material Ontology 和 Materials Design Ontology）进行对齐，从而能够高效地表示位错模拟数据。此外，我们通过将离散位错动力学数据表示为知识图谱（DisLocKG）展示了一个真实世界的用例，该图谱说明了它们之间的关系。我们还开发了一个 SPARQL 端点，为查询 DisLocKG 带来了极大的灵活性。
英文摘要：
Research in the field of Materials Science and Engineering focuses on the design, synthesis, properties, and performance of materials. An important class of materials that is widely investigated are crystalline materials, including metals and semiconductors. Crystalline material typically contains a distinct type of defect called "dislocation". This defect significantly affects various material properties, including strength, fracture toughness, and ductility. Researchers have devoted a significant effort in recent years to understanding dislocation behavior through experimental characterization techniques and simulations, e.g., dislocation dynamics simulations. This paper presents how data from dislocation dynamics simulations can be modeled using semantic web technologies through annotating data with ontologies. We extend the already existing Dislocation Ontology by adding missing concepts and aligning it with two other domain-related ontologies (i.e., the Elementary Multi-perspective Material Ontology and the Materials Design Ontology) allowing for representing the dislocation simulation data efficiently. Moreover, we show a real-world use case by representing the discrete dislocation dynamics data as a knowledge graph (DisLocKG) that illustrates the relationship between them. We also developed a SPARQL endpoint that brings extensive flexibility to query DisLocKG.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
