Research

The zcb advances an emerging scientific discipline: biodiversity knowledge science. Its research programme addresses foundational questions of how complex biodiversity knowledge can be semantically modelled, represented, integrated, and made contextually explorable and readily actionable.

Current research directions include:

• Semantic Units and FAIR 2.0: novel frameworks for structuring knowledge graphs to achieve deep semantic and cognitive interoperability
• The CLEAR Principle: a complementary framework to FAIR focused on human cognitive interpretability and contextual explorability of knowledge, making use of natural language representations of data and knowledge
• The Semantic Ladder: a progressive formalisation framework enabling content to enter the knowledge space incrementally, from unstructured text to formal ontology-grounded representations
• The TripleA Principle: extending knowledge graphs toward Actionable, Applicable, and Auditable decision-support systems for conservation and restoration
• Causal Digital Twins of Ecosystems: modelling causal hypotheses about biodiversity change, linking them to empirical evidence from collections and biomonitoring, and supporting "what-if" scenarios for ecosystem management
• Hybrid Intelligence: combining curated knowledge graphs with large language models (LLMs) to enable trustworthy, explainable, and human-led AI-assisted research and curation