Lars Vogt

WORK HISTORY

EDUCATION

SKILLS

ABOUT LARS VOGT

I work at the intersection of semantic modelling, knowledge representation, and FAIR and CLEAR data practices—primarily using OWL/RDF technologies—to make complex scientific knowledge and data more interoperable, machine-actionable, and human-comprehensible.Since 2006, I’ve been developing ontologies and semantic knowledge graphs in the life sciences, with applications ranging from phenotypic and biomedical data to material science, ecology, and biodiversity. A core focus of my work is improving the cognitive interoperability of knowledge graphs—by structuring triples into semantically meaningful subgraphs (i.e, Semantic Units) and enhancing their contextual explorability and human interpretability.I am especially interested in- Applying OWL-based frameworks in domain-specific contexts such as medicine, materials science, and biodiversity research- Enhancing semantic interoperability across disciplines- Modular structuring of knowledge graphs to support contextual explorability (e.g, via Semantic Units)- The FAIR Principles and their extension toward FAIR 2.0- The CLEAR Principle for cognitive interoperability (i.e, human-actionability)- FAIR Digital Objects as infrastructure for knowledge reuse- Semantic modelling of causal relationships (qualitative and quantitative)- Alignment of semantical modelling approaches with natural language statements (e.g, via Rosetta Statements) Earlier in my career, I worked on philosophical and theoretical aspects of evolutionary biology, including phylogenetic inference, species concepts, Popperian Falsificationism, and semiotics.Let’s connect if you’re interested in semantic technologies, FAIR and CLEAR data infrastructures, or making scientific knowledge more intelligible and reusable—both for humans and machines.