Industrial Knowledge Graph & Ontology Architect

Dunhillmedical; Sheffield; Hybrid; GBP 45,000 - 60,000; Full time

Benefits offered by this job

Annual leave and pension benefits

Flexible working opportunities

Hybrid working option

Discounts and staff benefits

Job summary

The University of Sheffield invites applications for a Knowledge Graph and Ontology Specialist within the Advanced Manufacturing Research Centre. You will design and implement semantic architectures to make industrial data interoperable, understandable and queryable, guiding knowledge graph lifecycles and ontological standards across multiple projects.

With 2-3 years in knowledge engineering, you will articulate 4D vs 3D modelling decisions, document ontology releases, and mentor junior staff

Qualifications

• Bachelor's or master's degree in Information Science, Computer Science, Philosophy (with a focus on formal logic/ontology), Systems Engineering, or a related area, coupled with 2-3 years of practical knowledge graph and ontology experience.
• Interview / Application
• Working knowledge of foundational upper ontologies (e.g., BORO, HQDM, IES, ISO 15926, BFO, UFO, SUMO, DOLCE) and a demonstrable understanding of 4D ( perdurantist / spatiotemporal) vs. 3D ( endurantist / spatial) modelling methods in extending domain ontologies.
• Interview / Application
• Deep, practical understanding of the distinctions, limitations, and appropriate applications of formal ontologies versus data dictionaries, vocabularies, and taxonomies.
• Interview / Application
• Experience with semantic web technologies (RDF(S), OWL, SPARQL, SHACL), standard conceptual modelling languages (e.g., UML or similar) and linked data formats (e.g. Turtle).
• Interview / Application
• Practical experience with ontology authoring tools and workflows (e.g., Sparx Enterprise Architect, Protégé) and familiarity with ontology design patterns and common anti-patterns.
• Interview / Application
• Working knowledge and understanding of the differences between graph database technologies (e.g., Neo4j, GraphDB, RDFox) and experience building and managing knowledge graphs that integrate data from multiple sources.
• Interview / Application
• Experience translating raw or semi-structured engineering data into structured semantic models, with an understanding of data pipeline or ETL fundamentals.
• Interview / Application
• Ability to work in an interdisciplinary environment, interviewing domain experts to translate complex subject matter into formal logic and structured models.
• Interview / Application
• Effective communication skills, both written and verbal, including the ability to explain highly abstract conceptual models to non-technical stakeholders.
• Interview / Application
• Ability to work effectively as part of an agile team (e.g. scrum, kanban) with a demonstrated capacity to operate independently, alongside excellent time, project management, and collaborative skills.
• Interview / Application
• Experience applying version control (e.g., Git), continuous integration, or open-source practices specifically tailored to ontology development, model lifecycle management, or semantic data collaboration.
• Interview / Application
• Background or exposure to advanced manufacturing, engineering, or industrial R&D environments.

Responsibilities

• Design, build, and maintain formal, machine-readable ontologies (e.g., using UML, RDF(S), SHACL, OWL) to support knowledge representation across multiple high-impact industrially-focused innovation projects.
• Apply advanced modelling paradigms, explicitly determining the appropriate use of 3D (endurantist/spatial) versus 4D (perdurantist/spatiotemporal) data modelling approaches to capture the state and lifecycle of engineering and research entities.
• Clearly document and differentiate the use of semantic technologies from primitive data dictionaries and taxonomies through to formal ontologies and logic across the project's infrastructure, ensuring the right tool is used for the right semantic requirement.
• Work closely with end users, software engineering and data scientists to ensure that all semantic models are FAIR (Findable, Accessible, Interoperable, and Reusable).
• Collaborate with the senior technical fellow, industry partners, and domain experts to extract implicit domain knowledge into explicit, rigorous conceptual models.
• Design the high-level semantic strategy and lifecycle management for the project's knowledge graphs and data schemas.
• Lead the writing of technical documentation, ontology release notes, and contribute to the dissemination of the project's ontological approach.
• Provide dissemination and mentorship to research teams on the importance of robust knowledge graph development and the practical differences between different semantic approaches (taxonomies vs ontologies).
• Organise technical alignment meetings and supervise/mentor junior staff.
• Make ethical decisions in your role, embedding the University's sustainability strategy into your working activities wherever possible.
• Carry out other duties, commensurate with the grade and remit of the post

Skills

Knowledge graph

Ontology engineering

Semantic modelling

RDF/OWL/SPARQL

UML

Education

Bachelor's or Master's in Information Science/CS/Philosophy (ontology focus)

Tools

Sparx Enterprise Architect

Protégé

GraphDB

Neo4j

Job description

The University of Sheffield invites applications for a Knowledge Graph and Ontology Specialist within the Advanced Manufacturing Research Centre. You will design and implement semantic architectures to make industrial data interoperable, understandable and queryable, guiding knowledge graph lifecycles and ontological standards across multiple projects.

With 2-3 years in knowledge engineering, you will articulate 4D vs 3D modelling decisions, document ontology releases, and mentor junior staff