Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data

• URL: http://arxiv.org/abs/2604.06230v1
• Date: Tue, 31 Mar 2026 20:01:20 GMT
• Title: Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
• Abstract summary: We present an infrastructure for representing and integrating atomistic simulation data as a knowledge graph.<n>Heterogeneous data from multiple sources are normalized into a common, domain-aligned representation.<n>The resulting knowledge graph contains over 750,000 triples describing nearly 8,000 computational samples.
• Score: 1.631115063641726
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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