Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PLoS One. 2016 Nov 16;11(11):e0166559. doi: 10.1371/journal.pone.0166559. eCollection 2016.

Abstract

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower-visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics.

MeSH terms

  • Animals
  • Bayes Theorem
  • Behavior, Animal
  • Biodiversity
  • Ecosystem*
  • Flowers / physiology*
  • Insecta / physiology*
  • Knowledge*
  • Pollen / physiology
  • Probability
  • Reproducibility of Results

Grants and funding

The authors received no specific funding for this work.