用知识图谱整合原子模拟数据，提升跨源复用性
Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
- 基于领域本体构建统一数据表示，支持多源数据融合
- 集成超75万条三元组，涵盖近8000个计算样本
- 可追踪计算流程，适合材料科学数据共享与分析
原子模拟数据的复用常受限于格式不一、元数据不全及工作流与溯源信息缺乏标准表示。本文提出一种基于本体的知识图谱基础设施，用于表示和整合原子模拟数据。该方法结合领域本体与软件框架，既能从现有数据集捕获信息，也能在模拟生成时直接采集数据。来自多个来源的异构数据被统一为一致的本体对齐表示，实现跨数据集的一致查询与分析。我们通过晶界数据整合、跨数据集材料性能对比分析，以及从已有模拟中提取热力学量等案例展示了该系统能力。同时，工作流以机器可读形式表示，支持正向溯源及部分计算过程重建。最终知识图谱包含超过75万条三元组，描述近8000个计算样本。该工作为提升原子模拟数据的可发现性、互操作性与复用性提供了实用框架。
原文摘要 · Abstract (English)
The reuse of atomistic simulation data is often limited by heterogeneous formats, incomplete metadata, and a lack of standardized representations of workflows and provenance. Here we present an ontology-based infrastructure for representing and integrating atomistic simulation data as a knowledge graph. The approach combines domain ontologies with a software framework that enables data capture both from existing datasets and directly from simulation workflows at the point of generation. Heterogeneous data from multiple sources are normalized into a common, ontology-aligned representation, enabling consistent querying and analysis across datasets. We demonstrate these capabilities through the integration of grain boundary data, cross-dataset analysis of material properties, and extraction of derived thermodynamic quantities from existing simulations. In addition, workflows are represented in a machine-readable form, enabling both forward provenance tracking and partial reconstruction of computational procedures. The resulting knowledge graph contains over 750,000 triples describing nearly 8,000 computational samples. This work provides a practical framework for improving the findability, interoperability, and reuse of atomistic simulation data.
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