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

Abstract

Summary: 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.grContact: pafilis@hcmr.gr or lars.juhl.jensen@cpr.ku.dkSupplementary information: Supplementary data are available at Bioinformatics online.

TraitBank: Practical semantics for organism attribute data

“…Legacy or previously unpublished data are also represented, and some data are derived from text mining projects [28,40]. Access to the data is free and open.…”

“…However, only three TraitBank data partners, Environments-EOL [28], Global Biotic Interaction [36], and Polytraits [14] fall into this category. Most of the resources we aggregate are not "born semantic," i.e., the data come to us with labels, some metadata, and sometimes an associated article explaining the rationale and methods of the study.…”

“…Most of the resources we aggregate are not "born semantic," i.e., the data come to us with labels, some metadata, and sometimes an associated article explaining the rationale and methods of the study. In these cases, EOL staff analyze the meaning of each attribute and select formally-defined semantic terms to represent 21 http://eol.org/info/structured_data_archives 22 http://eol.org/info/cp_spreadsheet 23 Plant Ontology (PO), 24 Phenotypic Quality (PATO) 25 and Chemical Entities of Biological Interest (CHEBI), 26 as well as OBO Foundry candidate ontologies such as Environment Ontology (ENVO), 27 Plant Trait Ontology (TO), 28 Uber Anatomy Ontology (UBERON) 29 and Ontology of Biological Attributes (OBA) 30 (Table 2). Not all concepts encountered in TraitBank data sets can be matched to terms in current ontologies or controlled vocabularies.…”

“…To promote progress in the aggregation of comprehensive data sets of particular interest to scientists and the public, EOL has funded projects like GloBi (Global Biotic Interactions) [36] and Environments-EOL [28]. For these communities and other ongoing projects like Polytraits and OBIS, TraitBank provides a live platform for distribution and re-use that exposes their data to broader audiences and promotes significant community curation.…”

“…Most of this information survives in the form of free text or data tables in published papers, if it survives at all [20]. Lately communities have started to annotate those papers [3], extract information from text [28,40], and build special-purpose databases of trait data, for example, TRY 1 for plants [24] and SeaLifeBase 2 for marine organisms. In addition, modern researchers are more likely to archive and share data sets associated with their published studies in open data repositories such as Dryad 3 [42], Ecological Archives 4 and PANGAEA.…”