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Abstract
As biological and biomedical research increasingly reference the environmental context of the biological entities under study, the need for formalisation and standardisation of environment descriptors is growing. The Environment Ontology (ENVO; http://www.environmentontology.org) is a community-led, open project which seeks to provide an ontology for specifying a wide range of environments relevant to multiple life science disciplines and, through an open participation model, to accommodate the terminological requirements of all those needing to annotate data using ontology classes. This paper summarises ENVO’s motivation, content, structure, adoption, and governance approach. The ontology is available from http://purl.obolibrary.org/obo/envo.owl - an OBO format version is also available by switching the file suffix to “obo”.
Highlights
Motivated research is generating [1,2,3] and archiving [4,5] ever-larger quantities of computerised data from environmental samples
Full URIs are of the form: http://purl.obolibrary. org/obo/ENVO_00002297, and are resolved to Web ontology language (OWL) as well as to human-readable web pages
Conclusions & outlook Environment Ontology (ENVO) is a community-led ontology that supports the representation of environments across and beyond the biological and biomedical domains
Summary
Motivated research is generating [1,2,3] and archiving [4,5] ever-larger quantities of computerised data from environmental samples. Biomedical researchers have begun to take particular interest in the physical environment of organisms at all scales, from microbes to patients [6,7,8,9], while scientists in epidemiology and public health are developing a stronger interest in location- and environment-based information for purposes of disease tracking [10,11]. In these complex and data-rich fields, the need to describe systematically the environmental context of biological entities is being increasingly acknowledged as a means to mobilise data for environment-aware analyses ENVO offers terminology resources both for specialists and for non-experts, a feature useful in scenarios where citizen scientists and volunteers are involved in sampling or observational campaigns (for example as described in [21])
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