environmental-exposure-ontology

Modular environmental exposures ontology

https://github.com/EnvironmentOntology/environmental-exposure-ontology

Science Score: 46.0%

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  • .zenodo.json file
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    Links to: zenodo.org
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    1 of 8 committers (12.5%) from academic institutions
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    Low similarity (9.9%) to scientific vocabulary

Keywords

environment exposure health monarchinitiative obo obofoundry ontology owl

Keywords from Contributors

semantic-web annotation bioinformatics life-sciences linkml ontology-registry open-science rdf data-modeling biocuration
Last synced: 6 months ago · JSON representation

Repository

Modular environmental exposures ontology

Basic Info
  • Host: GitHub
  • Owner: EnvironmentOntology
  • License: other
  • Language: Makefile
  • Default Branch: master
  • Homepage:
  • Size: 138 MB
Statistics
  • Stars: 33
  • Watchers: 8
  • Forks: 18
  • Open Issues: 70
  • Releases: 22
Topics
environment exposure health monarchinitiative obo obofoundry ontology owl
Created almost 10 years ago · Last pushed 9 months ago
Metadata Files
Readme License

README.md

Build Status DOI

logo

Environmental conditions, treatments and exposures ontology (ECTO)

The purpose of this ontology is to create compositional classes that assemble existing OBO ontologies such as ExO, CHEBI and ENVO to make ready-made precomposed classes for use in describing:

  • experimental treatments of plants and model organisms (e.g. modification of diet, lighting levels, temperature)
  • exposures of humans or any other organisms to stressors through a variety of routes, for purposes of public health, environmental monitoring etc
  • stimuli, natural and experimental
  • any kind of environmental condition or change in condition that can be experienced by an organism or population of organisms on earth

The scope is very general and can include for example plant treatment regimens, as well as human clinical exposures (although these may better be handled by a more specialized ontology)

An example of a class (in manchester syntax) is:

Class: ECTO:0000977 Annotations: rdfs:label "exposure to ultrafine respirable suspended particulate matter via inhalation" Annotations: IAO:0000115 "A exposure event involving the interaction of an exposure receptor to ultrafine respirable suspended particulate matter via inhalation." Annotations: oio:hasExactSynonym "ultrafine respirable suspended particulate matter exposure, via inhalation" EquivalentTo: ExO:0000002 and RO:0002233 some ENVO:01000416 and BFO_0000050 some ExO:0000057 ## 'exposure event' and 'has input' some ultrafine respirable suspended particulate matter and 'part of' some inhalation

Quick Start

There is no public browser yet. Use one of the following files:

Note: to open the OWL in Protege you will need to check out the repo so that the catalog can be used.

Relationships to other ontologies

Ontologies used in composition (largely orthogonal):

Similar ontologies (overlapping/non-orthogonal)

See below for the merge experiment with these ontologies.

We aim to reuse existing open ontologies as far as possible; for orthogonal ontologies, this is via axiomatization.

Note on ENVO: it may seem that ENVO is an overlapping/non-orthogonal ontology, but following our design patterns here this should be considered orthogonal; analogous to the relationship between an anatomical ontology and a variant/aberrant phenotype ontology.

Another new ontology to note is the UNEP Sustainable Development Goals ontology -- https://github.com/SDG-InterfaceOntology/sdgio/ -- this is being built in a modular fashion using ENVO and is seeding the creation of many useful social classes we will need, e.g. poverty, access to resources, etc.

Releases

Release files are in top level

Note: these are only for testing so far, not stable! These should not be considered real releases.

The proposed ID space is very tentative

Modeling

The model we are using is aligned with the environmental conditions model in Phenopackets. We attempt to follow ExO where possible.

We treat exposures as events; in ontological terms, they are types of occurrents. Specifically, they are interactions between a receptor (typically an organism, but could be a population of organisms) and a stressor (an agent or process that has a potential effect on the receptor). The stressor may interact with the organism through some kind of environmental medium (e.g. air, water, soil), and may enter via some route (e.g. permeating the skin or analogous barrier).

In some cases the route may be indirect: passive smoking or drug use by a mother during pregnancy.

This model permits a variety of pre-composed classes. We defined and generate these using Dead Simple OWL Design Patterns (DOSDPs)

See src/patterns for the list of patterns in use.

The basic idea is that a term like 'increased exposure to arsenic through ingestion/diet' can be composed using classes from ontologies such as ExO and CHEBI. We can see this as filling in slots in our datamodel.

Annotation Guide

Broadly speaking, this ontology is designed to support both pre- and post-composed use cases.

With the pre-composed approach, the curator uses a "ready-made" ECTO class expressing the combination of values required for different slots.

With the post-composed approach, ECTO can largely be disposed of, and instead the description is assembled by the curator by filling in the required slots like 'stressor'.

The two approaches are compatible. Post-composed descriptions can be automatically classified against the pre-composed ECTO. Similarly any description that uses ECTO can be unwound (or 'unfolded') to a pre-composed description, using the OWL equivalence axioms in the ontology.

Ontology Source

Most of the ontology is stored as CSVs in src/ontology/modules

See the Makefile for how the ontology is compiled from CSV modules.

See the .omn files for a human-readable set of descriptions

See the README-editors.md file in the src/ontology directory for instructions on how to edit, maintain or release the ontology.

Merge Experiment

See src/mappings for an exploration of merging multiple exposure ontologies using kboom

The intent is not to make a usable ontology, but rather to help gap fill and understand what is out there.

Edit this ontology!

We welcome suggestions from the community for new terms or changes to existing terms! Please create an issue using our issue tracker.

Owner

  • Name: The Environment Ontology
  • Login: EnvironmentOntology
  • Kind: organization

The public code repository of the Environmental Ontology project and GAZ, a gazetteer build on ontological principles

GitHub Events

Total
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 2
  • Pull request event: 2
  • Create event: 1
Last Year
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 2
  • Pull request event: 2
  • Create event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 522
  • Total Committers: 8
  • Avg Commits per committer: 65.25
  • Development Distribution Score (DDS): 0.634
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Lauren 4****n 191
Chris Mungall c****m@b****g 128
Nico Matentzoglu n****u@g****m 91
Anne Thessen a****n@g****m 58
Bill Duncan w****n@g****m 27
Nicole Vasilevsky v****s@o****u 25
Nomi Harris n****s 1
Julie McMurry j****y 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 35
  • Total pull requests: 72
  • Average time to close issues: 8 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 14
  • Total pull request authors: 9
  • Average comments per issue: 6.71
  • Average comments per pull request: 0.9
  • Merged pull requests: 58
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • laurenechan (7)
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  • dillerm (2)
  • LCCarmody (1)
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  • PaulNSchofield (1)
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Pull Request Authors
  • laurenechan (46)
  • matentzn (17)
  • diatomsRcool (6)
  • rays22 (2)
  • anitacaron (2)
  • yifengcao3 (1)
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  • nicolevasilevsky (1)
  • wdduncan (1)
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Dependencies

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