Lead Semantic Engineer

We are looking for a colleague to take on the role of maintaining, extending and querying the Coral Reef knowledge graph with future releases under our DevOps processes and help with the following activities:

1) business analysis and communication of features involving the knowledge graph,

2) maintenance and extension of the Coral Reef Ontology (modeling of new entities and properties),

3) acting as an interface onto the Graph and facilitating interaction for developers,

4) development of GraphQL and SPARQL queries,

5) development of SHACL shapes for validation,

6) development JSON-LD to enable metadata integrations

In detail, we are looking for a selection of the following skills & attributes in our new colleague.

Expertise and hands on experience with the Semantic Web technology stack

• RDF development
• OWL ontology development
• SHACL shapes development for data validation
• Development of SPARQL queries
• WIDOCO documentation generation
• JSON-LD context management and development
• Knowledge of strategies and tools for generation of URIs (frameworks, know/hoc)
• Extensive experience with a variety of commercial (Ontotext GraphDB, Anzo Cambridge Semantics, TopBraid, PoolParty, ...) and open source (Protegé, Apache Jena Fuseki, RML, Ontop, ...) solutions for working with RDF and ontologies.
• Development of FAIR data solutions
• Knowledge on GraphDB and GraphQL schema development and query language
• Cloud experience with Azure and AWS
• With regards to domain knowledge:
• Knowledge and experience in ontology development in the life science domain
• Knowledge on clinical trial conduct and standards (e.g. SDTM, ADaM) is of advantage
• Knowledge of ontologies used in the life science domain
• Knowledge of standard ontologies (e.g. PROV, DCAT)
• Standardization of properties - looking at Standard ontologies
• Understanding and discussing with the data providers and stakeholders
• Ontology modeling
• Re-use of controlled terminologies and generation of new terms - looking into available vocabularies in RTS, GDSR or establishing new ones with SMEs
• Participates in Architecture discussions and assists with data-centricity components
• Knowledge of Graph database management, Kafka, DocumentDB
• Applied knowledge of various modern data technologies, including Kafka, Spark, StreamSets, S3 object storage, Data Mesh, NoSQL, graph and RDF databases
• Development of knowledge graph related PBIs
• Discussing and explaining knowledge graph related PBIs to developers and GUI team
• Team player, strong interactions with all the team members
• RPLN will be provided soon