Description
Ecological knowledge is distributed across many formats, making findings difficult to compare and synthesize. The Causal Mosaic Schema (CAMO) is one approach to synthesize findings as structured data grounded in philosophical understanding. CAMO is being explored as part of EcoWeaver, an initiative to build a machine-readable knowledge base of ecological restoration findings that will allow users to examine causal relationships across hundreds of papers instantly.CAMO represents ecological findings as connected nodes and edges. A node represents an entity in a causal relationship through three components: an ecological entity, an attribute, and a change qualifier. Edges connect causal nodes by detailing the nature of the causal relationship described between them. They record evidential strength, supporting source passages, annotation confidence, and the geographic, temporal, and ecological context. Concepts are grounded in ontologies, including the Ecological Land Management Ontology (ELMO), to support standardized, machine-readable representation. As an EcoWeaver annotator, I will present my experience applying CAMO to three studies. These studies show challenges in selecting level of detail for nodes, representing context-sensitive findings, and determining what the evidence supports without overstating. They also highlight epistemic challenges, such as distinguishing species presence from an increase in abundance and determining how each finding should be represented. Preliminary annotation shows that these decisions affect what remains visible in the graph. For example, a treatment may have little detectable effect on species richness or diversity while still altering species composition. Representing individual species as separate nodes preserves information but increases annotation complexity and labour. Ecological knowledge-graph construction is not fact extraction; it requires interpretation, explicit standards, and documentation of context and uncertainty.
| Topic | Topic 3: Benefits and pitfalls for knowledge graph construction in ecology |
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