Ontology type: schema:Chapter Open Access: True
2016-11-04
AUTHORSMarcus C. Chibucos , Deborah A. Siegele , James C. Hu , Michelle Giglio
ABSTRACTThe Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO describes multiple evidence types, including evidence resulting from experimental (i.e., wet lab) techniques, evidence arising from computational methods, statements made by authors (whether or not supported by evidence), and inferences drawn by researchers curating the literature. In addition to summarizing the evidence that supports a particular assertion, ECO also offers a means to document whether a computer or a human performed the process of making the annotation. Incorporating ECO into an annotation system makes it possible to leverage the structure of the ontology such that associated data can be grouped hierarchically, users can select data associated with particular evidence types, and quality control pipelines can be optimized. Today, over 30 resources, including the Gene Ontology, use the Evidence and Conclusion Ontology to represent both evidence and how annotations are made. More... »
PAGES245-259
The Gene Ontology Handbook
ISBN
978-1-4939-3741-7
978-1-4939-3743-1
http://scigraph.springernature.com/pub.10.1007/978-1-4939-3743-1_18
DOIhttp://dx.doi.org/10.1007/978-1-4939-3743-1_18
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1012630201
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/27812948
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Chemical Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biological Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0399",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Other Chemical Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0601",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biochemistry and Cell Biology",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Animals",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Computational Biology",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Data Curation",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Databases, Genetic",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Gene Ontology",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Internet",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Molecular Sequence Annotation",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Software",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, 801 W. Baltimore Street, 21201, Baltimore, MD, USA",
"id": "http://www.grid.ac/institutes/grid.411024.2",
"name": [
"Department of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, 801 W. Baltimore Street, 21201, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Chibucos",
"givenName": "Marcus C.",
"id": "sg:person.01136407446.04",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136407446.04"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Biology, Texas A&M University, 77843, College Station, TX, USA",
"id": "http://www.grid.ac/institutes/grid.264756.4",
"name": [
"Department of Biology, Texas A&M University, 77843, College Station, TX, USA"
],
"type": "Organization"
},
"familyName": "Siegele",
"givenName": "Deborah A.",
"id": "sg:person.0741637016.36",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0741637016.36"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, 77843, College Station, TX, USA",
"id": "http://www.grid.ac/institutes/grid.264756.4",
"name": [
"Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, 77843, College Station, TX, USA"
],
"type": "Organization"
},
"familyName": "Hu",
"givenName": "James C.",
"id": "sg:person.016511130534.43",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016511130534.43"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Medicine, Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA",
"id": "http://www.grid.ac/institutes/grid.411024.2",
"name": [
"Department of Medicine, Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Giglio",
"givenName": "Michelle",
"id": "sg:person.0637630342.86",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0637630342.86"
],
"type": "Person"
}
],
"datePublished": "2016-11-04",
"datePublishedReg": "2016-11-04",
"description": "The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO describes multiple evidence types, including evidence resulting from experimental (i.e., wet lab) techniques, evidence arising from computational methods, statements made by authors (whether or not supported by evidence), and inferences drawn by researchers curating the literature. In addition to summarizing the evidence that supports a particular assertion, ECO also offers a means to document whether a computer or a human performed the process of making the annotation. Incorporating ECO into an annotation system makes it possible to leverage the structure of the ontology such that associated data can be grouped hierarchically, users can select data associated with particular evidence types, and quality control pipelines can be optimized. Today, over 30 resources, including the Gene Ontology, use the Evidence and Conclusion Ontology to represent both evidence and how annotations are made.",
"editor": [
{
"familyName": "Dessimoz",
"givenName": "Christophe",
"type": "Person"
},
{
"familyName": "\u0160kunca",
"givenName": "Nives",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-1-4939-3743-1_18",
"inLanguage": "en",
"isAccessibleForFree": true,
"isPartOf": {
"isbn": [
"978-1-4939-3741-7",
"978-1-4939-3743-1"
],
"name": "The Gene Ontology Handbook",
"type": "Book"
},
"keywords": [
"annotation system",
"quality control pipeline",
"ontology",
"annotation",
"control pipeline",
"computational methods",
"GO annotations",
"users",
"resources",
"computer",
"researchers",
"pipeline",
"inference",
"data",
"system",
"Gene Ontology",
"assertion",
"particular assertion",
"today",
"technique",
"method",
"types",
"process",
"community resources",
"types of evidence",
"means",
"scientific studies",
"statements",
"humans",
"evidence types",
"authors",
"literature",
"structure",
"addition",
"eco",
"course",
"experimental techniques",
"study",
"evidence"
],
"name": "The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations",
"pagination": "245-259",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1012630201"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-1-4939-3743-1_18"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"27812948"
]
}
],
"publisher": {
"name": "Springer Nature",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-1-4939-3743-1_18",
"https://app.dimensions.ai/details/publication/pub.1012630201"
],
"sdDataset": "chapters",
"sdDatePublished": "2022-06-01T22:31",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/chapter/chapter_280.jsonl",
"type": "Chapter",
"url": "https://doi.org/10.1007/978-1-4939-3743-1_18"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-3743-1_18'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-3743-1_18'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-3743-1_18'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-3743-1_18'
This table displays all metadata directly associated to this object as RDF triples.
180 TRIPLES
23 PREDICATES
76 URIs
67 LITERALS
17 BLANK NODES