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

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...

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Detalles Bibliográficos
Autores principales: Coetzer, Willem, Moodley, Deshendran, Gerber, Aurona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5113002/
https://www.ncbi.nlm.nih.gov/pubmed/27851814
http://dx.doi.org/10.1371/journal.pone.0166559
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author Coetzer, Willem
Moodley, Deshendran
Gerber, Aurona
author_facet Coetzer, Willem
Moodley, Deshendran
Gerber, Aurona
author_sort Coetzer, Willem
collection PubMed
description 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.
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spelling pubmed-51130022016-12-08 Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data Coetzer, Willem Moodley, Deshendran Gerber, Aurona PLoS One Research Article 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. Public Library of Science 2016-11-16 /pmc/articles/PMC5113002/ /pubmed/27851814 http://dx.doi.org/10.1371/journal.pone.0166559 Text en © 2016 Coetzer et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Coetzer, Willem
Moodley, Deshendran
Gerber, Aurona
Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title_full Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title_fullStr Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title_full_unstemmed Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title_short Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data
title_sort eliciting and representing high-level knowledge requirements to discover ecological knowledge in flower-visiting data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5113002/
https://www.ncbi.nlm.nih.gov/pubmed/27851814
http://dx.doi.org/10.1371/journal.pone.0166559
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