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ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life.


ABSTRACT:

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The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centralized resources. However, structured annotations are needed to facilitate large-scale analyses. Therefore, we developed ENVIRONMENTS, a fast dictionary-based tagger capable of identifying Environment Ontology (ENVO) terms in text. We evaluate the accuracy of the tagger on a new manually curated corpus of 600 Encyclopedia of Life (EOL) species pages. We use the tagger to associate taxa with environments by tagging EOL text content monthly, and integrate the results into the EOL to disseminate them to a broad audience of users.

Availability and implementation

The software and the corpus are available under the open-source BSD and the CC-BY-NC-SA 3.0 licenses, respectively, at http://environments.hcmr.gr.

SUBMITTER: Pafilis E 

PROVIDER: S-EPMC4443677 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life.

Pafilis Evangelos E   Frankild Sune P SP   Schnetzer Julia J   Fanini Lucia L   Faulwetter Sarah S   Pavloudi Christina C   Vasileiadou Katerina K   Leary Patrick P   Hammock Jennifer J   Schulz Katja K   Parr Cynthia Sims CS   Arvanitidis Christos C   Jensen Lars Juhl LJ  

Bioinformatics (Oxford, England) 20150124 11


<h4>Unlabelled</h4>The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centralized resources. However, structured annotations are needed to facilitate large-scale analyses. Therefore, we developed ENVIRONMENTS, a fast dictionary-based tagger capable of identifying Environment Ontology (ENVO) terms in text. We evaluate  ...[more]

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