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

Evangelos Pafilis | Zendy; Sune Pletscher-Frankild | Zendy; Julia Schnetzer | Zendy; Lucia Fanini | Zendy; Sarah Faulwetter | Zendy; Christina Pavloudi | Zendy; Katerina Vasileiadou | Zendy; Patrick Leary | Zendy; Jennifer Hammock | Zendy; Katja Schulz | Zendy; Cynthia Parr | Zendy; Christos Arvanitidis | Zendy; Lars Juhl Jensen | Zendy

Open Access

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

Author(s) -

Evangelos Pafilis,

Sune Pletscher-Frankild,

Julia Schnetzer,

Lucia Fanini,

Sarah Faulwetter,

Christina Pavloudi,

Katerina Vasileiadou,

Patrick Leary,

Jennifer Hammock,

Katja Schulz,

Cynthia Parr,

Christos Arvanitidis,

Lars Juhl Jensen

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv045

Subject(s) - annotation , computer science , dissemination , encyclopedia , identification (biology) , ontology , world wide web , software , information retrieval , key (lock) , artificial intelligence , library science , biology , ecology , telecommunications , philosophy , computer security , epistemology , programming language

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.

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