def metric_138_institution(doc):
institutions = set(creators['name'] for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'creators': {
'@type': 'Organization',
'name': {},
}
})['@graph'] if node['creators']
for creators in force_list(node['creators'])
if creators['name'])
affiliated_institutions = list(
map(
json.loads,
set(
json.dumps({
'person': creators['fullName'],
'organization': affiliations['name']
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'creators': {
'@type': 'Person',
'fullName': {},
'affiliations': {
'@type': 'Organization',
'name': {}
}
}
})['@graph'] if node['creators']
for creators in force_list(node['creators'])
if creators['fullName'] and creators['affiliations']
for affiliations in force_list(creators['affiliations'])
if affiliations['name'])))
if institutions:
yield {
'value':
1,
'comment':
'Found institution(s): {}'.format(', '.join(institutions), ),
}
elif affiliated_institutions:
yield {
'value':
0.75,
'comment':
'Found affiliated institution(s): {}'.format(
', '.join(
'{} <{}>'.format(person['person'], person['organization'])
for person in affiliated_institutions), ),
}
else:
yield {
'value': 0,
'comment': 'No institution was identified',
}
def metric_145_landing_page(doc):
landingPages = set(
node['access']['landingPage']
for node in jsonld_frame(doc, {
'@type': 'DatasetDistribution',
'access': {
'landingPage': {},
}
})['@graph']
if node['access'] and node['access']['landingPage']
)
if landingPages:
for landingPage in landingPages:
if requests.get(landingPage).status_code < 400:
yield {
'value': 1,
'comment': 'Landing page found {} and seems to be accessible'.format(landingPage)
}
else:
yield {
'value': 0.75,
'comment': 'Landing page found {} but seems to report a problem'.format(landingPage)
}
else:
yield {
'value': 0,
'comment': 'Could not identify any landing pages'
}
def metric_136_program(doc):
programs = set(
node['program']['name']
for node in jsonld_frame(doc, {
'@type': 'Dataset',
'program': {
'name': {}
}
})['@graph']
if node['program']
for program in force_list(node['program'])
if program['name']
)
if programs:
yield {
'value': 1,
'comment': 'Identified program(s): {}'.format(
', '.join(programs)
)
}
else:
yield {
'value': 0,
'comment': 'Could not identify any programs',
}
def metric_104_doi(doc):
dois = set(node['identifier'] for node in jsonld_frame(
doc, {
'@type':
['Identifier', 'relatedIdentifier', 'alternateIdentifiers'],
'description': ['doi', 'DOI'],
'identifier': {}
})['@graph'] if node['identifier'] and node['description'])
if dois:
for doi in dois:
try:
urllib.request.urlopen(doi if doi.startswith('http') else
'https://doi.org/{}'.format(doi))
yield {
'value': 1,
'comment': 'DOI {} was identified and verified'.format(doi)
}
except urllib.error.HTTPError:
yield {
'value':
0.25,
'comment':
'DOI {} was identified but could not be verified'.format(
doi)
}
else:
yield {
'value': 0,
'comment': 'No DOIs could be identified',
}
def metric_27_contact_pi(doc):
people = list(map(json.loads, set(
json.dumps({
'fullName': creators['fullName'],
'roles': creators.get('roles', []),
})
for node in jsonld_frame(doc, {
'@type': 'Dataset',
'creators': {
'@type': 'Person',
'fullName': {},
'roles': {
'@default': []
},
}
})['@graph']
if node['creators']
for creators in force_list(node['creators'])
if creators['fullName']
)))
PIs = [
person
for person in people
if 'Principal Investigator' in person['roles']
]
if PIs:
yield {
'value': 1,
'comment': 'Found PI(s): {}'.format(
', '.join([person['fullName'] for person in PIs])
),
}
elif people:
yield {
'value': 0.5,
'comment': 'Found {}, but cannot determine a PI'.format(
[
person['fullName'] + ('(' + ', '.join(person['roles']) + ')') if person['roles'] else ''
for person in people
]
),
}
else:
yield {
'value': 0,
'comment': 'No PI or people could be identified'
}
def metric_137_project(doc):
projects = set(storedIn['name'] for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'storedIn': {
'@type': 'DataRepository',
'name': {}
}
})['@graph'] if node['storedIn']
for storedIn in force_list(node['storedIn'])
if storedIn['name'])
if projects:
yield {
'value': 1,
'comment': 'Identified project(s): {}'.format(', '.join(projects)),
}
else:
yield {
'value': 0,
'comment': 'Could not identify any projects',
}
def metric_110_access_protocol(doc):
access_protocols = set(
access['accessURL'] for node in jsonld_frame(doc, {
'@type': 'DatasetDistribution',
'access': {
'accessURL': {},
}
})['@graph'] if node['access'] for access in force_list(node['access'])
if access['accessURL'])
if access_protocols:
yield {
'value':
1,
'comment':
'Access protocol(s) found: {}'.format(', '.join(access_protocols))
}
else:
yield {
'value': 0,
'comment': 'Could not identify any access protocols'
}
def metric_108_resource_identifier(doc):
identifiers = set(
node['identifier'].get('identifierSource', '') +
node['identifier']['identifier'] for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'identifier': {
'identifier': {},
'identifierSource': {
'@default': ''
},
}
})['@graph']
if node['identifier'] and node['identifier']['identifier'])
if identifiers:
for identifier in identifiers:
if '://' in identifier and requests.get(
identifier).status_code < 400:
yield {
'value':
1,
'comment':
'Resource identifier {} was identified and verified'.
format(identifier)
}
else:
yield {
'value':
0.75,
'comment':
'Resource identifier {} was identified but could not be verified'
.format(identifier)
}
else:
yield {
'value': 0,
'comment': 'No resource identifier was found',
}
def metric_143_ncbitaxon(doc):
taxonomies = list(
map(
json.loads,
set(
json.dumps({
'value':
isAbout['name'],
'valueIRI':
isAbout.get('identifier', {}).get('identifierSource', '') +
isAbout.get('identifier', {}).get('identifier', '')
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'isAbout': {
'@type': 'TaxonomicInformation',
'name': {},
'identifier': {
'identifier': {},
'identifierSource': {
'@default': ''
},
}
}
})['@graph'] if node['isAbout']
for isAbout in force_list(node['isAbout'])
if isAbout['name'])))
if taxonomies:
for taxonomy in taxonomies:
value_ns = IRI_to_NS(taxonomy.get('valueIRI'))
if taxonomy.get(
'value') and taxonomy.get('valueIRI') and pronto.Term(
value_ns, taxonomy['value']) in NCBITaxon:
yield {
'value':
1,
'comment':
'Ontological IRI for taxonomy {} and term match what is found in NCBITaxon.'
.format(value_ns),
}
elif taxonomy.get('valueIRI') and value_ns in NCBITaxon:
yield {
'value':
0.75,
'comment':
'Ontological IRI for taxonomy {} found in NCBITaxon.'.
format(value_ns),
}
elif taxonomy.get(
'value') and taxonomy['value'] in NCBITaxon_reversed:
yield {
'value':
0.75,
'comment':
'Taxonomy `{}` found in NCBITaxon.'.format(
taxonomy['value']),
}
elif taxonomy.get('value') and taxonomy[
'value'] in NCBITaxon_reversed_synonyms:
yield {
'value':
0.5,
'comment':
'Taxonomy `{}` found in NCBITaxon synonyms.'.format(
taxonomy['value']),
}
else:
yield {
'value':
0.25,
'comment':
'Taxonomy `{}` found but not in NCBITaxon.'.format(
taxonomy.get('value', '') +
(('<' + value_ns + '>') if value_ns else '')),
}
else:
yield {
'value': 0.0,
'comment': 'Taxonomy could not be identified',
}
def metric_142_edam(doc):
filetypes = list(map(json.loads,set(
json.dumps({
'value': information['value'],
'valueIRI': information['valueIRI'],
})
for node in jsonld_frame(doc, {
'@type': 'Dataset',
'types': {
'information': {
'value': { '@default': '' },
'valueIRI': { '@default': '' }
}
}
})['@graph']
if node['types']
for types in force_list(node['types'])
if types['information']
for information in force_list(types['information'])
if information['value'] and information['valueIRI']
)))
if filetypes:
for filetype in filetypes:
value_ns = IRI_to_NS(filetype.get('valueIRI'))
if filetype.get('value') and filetype.get('valueIRI') and pronto.Term(value_ns, filetype['value']) in EDAM:
yield {
'value': 1,
'comment': 'Ontological IRI for file type {} and term match what is found in EDAM.'.format(
value_ns
),
}
elif filetype.get('valueIRI') and value_ns in EDAM:
yield {
'value': 0.75,
'comment': 'Ontological IRI for filetype {} found in EDAM.'.format(
value_ns
),
}
elif filetype.get('value') and filetype['value'] in EDAM_reversed:
yield {
'value': 0.75,
'comment': 'Filetype `{}` found in EDAM.'.format(
filetype['value']
),
}
elif filetype.get('value') and filetype['value'] in EDAM_reversed_synonyms:
yield {
'value': 0.5,
'comment': 'Filetype `{}` found in EDAM synonyms.'.format(
filetype['value']
),
}
else:
yield {
'value': 0.25,
'comment': 'Filetype `{}` found but not in EDAM.'.format(
filetype.get('value', '') + (('<' + value_ns + '>') if value_ns else '')
),
}
else:
yield {
'value': 0.0,
'comment': 'filetype could not be identified',
}
def metric_144_cellosaurus(doc):
cell_lines = list(
map(
json.loads,
set(
json.dumps({
'value':
isAbout['name'],
'valueIRI':
isAbout.get('identifier', {}).get('identifierSource', '') +
isAbout.get('identifier', {}).get('identifier', '')
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'isAbout': {
'@type': 'BiologicalEntity',
'name': {},
'identifier': {
'identifier': {},
'identifierSource': {
'@default': ''
},
}
}
})['@graph'] if node['isAbout']
for isAbout in force_list(node['isAbout'])
if isAbout['name'])))
if cell_lines:
for cell_line in cell_lines:
value_ns = IRI_to_NS(cell_line.get('valueIRI'))
if cell_line.get(
'value') and cell_line.get('valueIRI') and Cellosaurus.get(
value_ns, {}).get('name') == cell_line['value']:
yield {
'value':
1,
'comment':
'Ontological IRI for cell line {} and term match what is found in Cellosaurus.'
.format(value_ns),
}
elif cell_line.get('valueIRI') and value_ns in Cellosaurus:
yield {
'value':
0.75,
'comment':
'Ontological IRI for cell line {} found in Cellosaurus.'.
format(value_ns),
}
elif cell_line.get('value') and value_ns in Cellosaurus_reversed:
yield {
'value':
0.75,
'comment':
'Cell line `{}` found in Cellosaurus.'.format(
cell_line['value']),
}
elif cell_line.get('value') and cell_line[
'value'] in Cellosaurus_reversed_synonyms:
yield {
'value':
0.5,
'comment':
'Cell line `{}` found in Cellosaurus synonyms.'.format(
cell_line['value']),
}
else:
yield {
'value':
0.25,
'comment':
'Cell line `{}` found but not in Cellosaurus.'.format(
cell_line.get('value', '') +
(('<' + value_ns + '>') if value_ns else '')),
}
else:
yield {
'value': 0.0,
'comment': 'Cell line could not be identified',
}
def metric_140_uberon(doc):
anatomical_parts = list(
map(
json.loads,
set(
json.dumps({
'value':
isAbout['name'],
'valueIRI':
isAbout.get('identifier', {}).get('identifierSource', '') +
isAbout.get('identifier', {}).get('identifier', '')
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'isAbout': {
'@type': 'AnatomicalPart',
'name': {},
'identifier': {
'identifier': {},
'identifierSource': {
'@default': ''
},
}
}
})['@graph'] if node['isAbout']
for isAbout in force_list(node['isAbout'])
if isAbout['name'])))
if anatomical_parts:
for anatomical_part in anatomical_parts:
value_ns = IRI_to_NS(anatomical_part.get('valueIRI'))
if anatomical_part.get('value') and anatomical_part.get(
'valueIRI') and pronto.Term(
value_ns, anatomical_part['value']) in UBERON:
yield {
'value':
1,
'comment':
'Ontological IRI for anatomical part {} and term match what is found in UBERON.'
.format(value_ns),
}
elif anatomical_part.get('valueIRI') and value_ns in UBERON:
yield {
'value':
0.75,
'comment':
'Ontological IRI for anatomical part {} found in UBERON.'.
format(value_ns),
}
elif anatomical_part.get(
'value') and anatomical_part['value'] in UBERON_reversed:
yield {
'value':
0.75,
'comment':
'Anatomical part `{}` found in UBERON.'.format(
anatomical_part['value']),
}
elif anatomical_part.get('value') and anatomical_part[
'value'] in UBERON_reversed_synonyms:
yield {
'value':
0.5,
'comment':
'Anatomical part `{}` found in UBERON synonyms.'.format(
anatomical_part['value']),
}
else:
yield {
'value':
0.25,
'comment':
'Anatomical part `{}` found but not in UBERON.'.format(
anatomical_part.get('value', '') +
(('<' + value_ns + '>') if value_ns else '')),
}
else:
yield {
'value': 0.0,
'comment': 'Anatomical part could not be identified',
}
def metric_141_mondo(doc):
diseases = list(
map(
json.loads,
set(
json.dumps({
'value':
isAbout['name'],
'valueIRI': (
isAbout['identifier'].get('identifierSource', '') +
isAbout['identifier'].get('identifier', '')
) if isAbout['identifier'] else ''
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'isAbout': {
'@type': 'Disease',
'name': {},
'identifier': {
'identifier': {},
'identifierSource': {
'@default': ''
},
}
}
})['@graph'] if node['isAbout']
for isAbout in force_list(node['isAbout'])
if isAbout['name'])))
if diseases:
for disease in diseases:
value_ns = IRI_to_NS(disease.get('valueIRI'))
if disease.get(
'value') and disease.get('valueIRI') and pronto.Term(
value_ns, disease['value']) in MONDO:
yield {
'value':
1,
'comment':
'Ontological IRI for disease {} and term match what is found in MONDO.'
.format(value_ns),
}
elif disease.get('valueIRI') and disease['valueIRI'] in MONDO:
yield {
'value':
0.75,
'comment':
'Ontological IRI for disease {} found in MONDO.'.format(
value_ns),
}
elif disease.get('value') and disease['value'] in MONDO_reversed:
yield {
'value':
0.75,
'comment':
'Disease `{}` found in MONDO.'.format(disease['value']),
}
elif disease.get(
'value') and disease['value'] in MONDO_reversed_synonyms:
yield {
'value':
0.5,
'comment':
'Disease `{}` found in MONDO synonyms.'.format(
disease['value']),
}
else:
yield {
'value':
0.5,
'comment':
'Disease `{}` found but not in MONDO.'.format(
disease.get('value', '') +
(('<' + value_ns + '>') if value_ns else '')),
}
else:
yield {
'value': 0.0,
'comment': 'Disease could not be identified',
}
def metric_139_bao(doc):
assays = list(
map(
json.loads,
set(
json.dumps({
'value':
method if type(method) == str else method['value'],
'valueIRI':
'' if type(method) == str else method['valueIRI'],
}) for node in jsonld_frame(
doc, {
'@type': 'Dataset',
'types': {
'method': {
'value': {
'@default': ''
},
'valueIRI': {
'@default': ''
}
}
}
})['@graph'] if node['types']
for types in force_list(node['types']) if types['method']
for method in force_list(types['method'])
if type(method) == str or
(type(method) == dict and method['value'] or method['valueIRI']
))))
if assays:
for assay in assays:
value_ns = IRI_to_NS(assay.get('valueIRI'))
if assay.get('value') and assay.get('valueIRI') and pronto.Term(
value_ns, assay.get('value')) in BAO:
yield {
'value':
1,
'comment':
'Ontological IRI for Assay {} and term match what is found in BAO.'
.format(assay['valueIRI']),
}
elif value_ns and assay['valueIRI'] in BAO:
yield {
'value':
0.75,
'comment':
'Ontological IRI for Assay {} found in BAO.'.format(
assay['valueIRI']),
}
elif assay.get('value') and assay['value'] in BAO_reversed:
yield {
'value': 0.75,
'comment': 'Assay {} found in BAO.'.format(assay['value']),
}
elif assay.get(
'value') and assay['value'] in BAO_reversed_synonyms:
yield {
'value':
0.5,
'comment':
'Assay `{}` found in BAO synonyms.'.format(assay['value']),
}
else:
yield {
'value':
0.25,
'comment':
'Assay {} found but not in BAO.'.format(
assay.get('value', '') +
(('<' + value_ns + '>') if value_ns else '')),
}
else:
yield {
'value': 0.0,
'comment': 'Assay could not be identified',
}
