Modeling Dislocation Dynamics Data Using Semantic Web Technologies

TL;DR

This paper demonstrates how dislocation dynamics simulation data in materials science can be effectively modeled using semantic web technologies, enhancing data representation and querying capabilities through ontologies and knowledge graphs.

Contribution

It extends existing dislocation ontologies and integrates them with related domain ontologies to create a comprehensive semantic model and knowledge graph for dislocation simulation data.

Findings

Extended Dislocation Ontology with new concepts

Created DisLocKG knowledge graph for dislocation data

Developed a SPARQL endpoint for flexible data querying

Abstract

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.