DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials

TL;DR

The paper presents DISO, a domain ontology for modeling dislocations in crystalline materials, to enable interoperable, machine-actionable data across experimental and simulation workflows. It adopts a top-down design, reuses concepts from CSO and CDO, and extends them with new DISO classes (e.g., Dislocation, SlipPlane, SlipDirection, DiscretizedLine) and properties, documented with rich metadata and published as Linked Data at a persistent URL. The authors demonstrate two use cases—dislocation dynamics data and TEM experiment data—by mapping data to RDF and evaluating the ontology with competency questions and OntoQA, showing favorable attribute and inheritance richness and acceptable relationship richness. The work advances FAIR data practices in materials science by enabling semantic search, cross-domain interoperability, and future expansion to a DISOS suite and alignment with EMMO. Future efforts include modeling elasticity and other defect types, and deeper integration with standards like RO-Crate for reproducible data packaging.

Abstract

Crystalline materials, such as metals and semiconductors, nearly always contain a special defect type called dislocation. This defect decisively determines many important material properties, e.g., strength, fracture toughness, or ductility. Over the past years, significant effort has been put into understanding dislocation behavior across different length scales via experimental characterization techniques and simulations. This paper introduces the dislocation ontology (DISO), which defines the concepts and relationships related to linear defects in crystalline materials. We developed DISO using a top-down approach in which we start defining the most general concepts in the dislocation domain and subsequent specialization of them. DISO is published through a persistent URL following W3C best practices for publishing Linked Data. Two potential use cases for DISO are presented to illustrate its usefulness in the dislocation dynamics domain. The evaluation of the ontology is performed in two directions, evaluating the success of the ontology in modeling a real-world domain and the richness of the ontology.

Figures (4)

• Figure 1: The idealization represents the dislocation in the mesoscale. Here, the individual atoms are no longer visible. This idealization reduced the tube-like defect "region" to a mathematical line. On the rightmost, the numerical representation of a mathematical line as the discretized line is illustrated.
• Figure 2: The workflow of the dislocation ontology development, illustrating the main phases, subprocesses, and roles involved in the whole process.
• Figure 3: Core concepts and interconnected relationships in the DISO ontology. Arrows with open arrow heads denote rdfs:subClassOf properties between classes. Regular arrows visualize rdfs:domain and rdfs:range restrictions on properties. Furthermore, colored boxes represent different ontologies, e.g., MDO, CDO, CSO, and DISO.
• Figure 4: Sample of the instances of the dislocation dynamic data. Yellow points denote individuals of classes. Each individual is defined by an arrow having rdf:type relationship to the respective class and individuals are connected by object properties defined in DISO. Colored boxes represent classes from different ontologies, e.g., CDO, CSO, and DISO.