  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.
