Ejemplo n.º 1
0
def normalize_prefixes(graph, curies):
    mg = makeGraph('nifall',
                   makePrefixes('owl', 'skos', 'oboInOwl'),
                   graph=graph)
    mg.del_namespace('')

    old_namespaces = list(graph.namespaces())
    ng_ = makeGraph('', prefixes=makePrefixes('oboInOwl', 'skos'))
    [ng_.g.add(t) for t in mg.g]
    [ng_.add_namespace(n, p) for n, p in curies.items() if n != '']
    #[mg.add_namespace(n, p) for n, p in old_namespaces if n.startswith('ns') or n.startswith('default')]
    #[mg.del_namespace(n) for n in list(mg.namespaces)]
    #graph.namespace_manager.reset()
    #[mg.add_namespace(n, p) for n, p in wat.items() if n != '']
    return mg, ng_
Ejemplo n.º 2
0
def ilx_json_to_tripples(
    j
):  # this will be much eaiser if everything can be exported as a relationship or an anotation
    g = makeGraph('do not write me',
                  prefixes=makePrefixes('ILX', 'ilx', 'owl', 'skos', 'NIFRID'))

    def pref(inp):
        return makePrefixes('ilx')['ilx'] + inp

    id_ = pref(j['ilx'])
    type_ = {
        'term': 'owl:Class',
        'relationship': 'owl:ObjectProperty',
        'annotation': 'owl:AnnotationProperty'
    }[j['type']]
    out = []  # TODO need to expand these
    out.append((id_, rdflib.RDF.type, type_))
    out.append((id_, rdflib.RDFS.label, j['label']))
    out.append((id_, 'skos:definition', j['definition']))
    for syndict in j['synonyms']:
        out.append((id_, 'NIFRID:synonym', syndict['literal']))
    for superdict in j[
            'superclasses']:  # should we be returning the preferred id here not the ilx? or maybe that is a different json output?
        out.append((id_, rdflib.RDFS.subClassOf, pref(superdict['ilx'])))
    for eid in j['existing_ids']:
        out.append((id_, 'ilx:someOtherId', eid['iri']))  # predicate TODO
    [g.add_trip(*o) for o in out]
    return g.g.serialize(format='nifttl')  # other formats can be choosen
Ejemplo n.º 3
0
def load(file):
    filepath = os.path.expanduser(file)
    _, ext = os.path.splitext(filepath)
    filetype = ext.strip('.')
    if filetype == 'ttl':
        infmt = 'turtle'
    else:
        infmt = None
    print(filepath)
    graph = rdflib.Graph()
    try:
        graph.parse(filepath, format=infmt)
    except rdflib.plugins.parsers.notation3.BadSyntax as e:
        print('PARSING FAILED', filepath)
        raise e
    og = makeGraph('', graph=graph)

    # FIXME this should really just be a function :/
    curie, *prefs = kludge(filepath)

    name = os.path.splitext(os.path.basename(filepath))[0]
    if 'slim' in name:
        name = name.replace('slim', '')
    try:
        version = list(graph.subject_objects(owl.versionIRI))[0][1]
    except IndexError:
        version = list(graph.subjects(rdf.type, owl.Ontology))[0]

    ng = createOntology(
        f'{name}-dead', f'NIF {curie} deprecated',
        makePrefixes('replacedBy', 'NIFRID', curie, *prefs), f'{name}dead',
        f'Classes from {curie} with owl:deprecated true that we want rdfs:subClassOf NIFRID:birnlexRetiredClass, or classes hiding in a oboInOwl:hasAlternativeId annotation. This file was generated by pyontutils/necromancy from {version}.'
    )
    extract(og, ng, curie)
Ejemplo n.º 4
0
def loadGraphFromFile(filename, prefixes=None):
    graph = rdflib.Graph()
    graph.parse(filename, format='turtle')
    fn = os.path.splitext(filename)[0]
    print(fn)
    mg = makeGraph(fn, prefixes=prefixes, graph=graph, writeloc='')
    return mg
Ejemplo n.º 5
0
def do_file(filename, swap, *args):
    print('START', filename)
    ng = rdflib.Graph()
    ng.parse(filename, format='turtle')
    reps = switchURIs(ng, swap, *args)
    wg = makeGraph('', graph=ng)
    wg.filename = filename
    wg.write()
    print('END', filename)
    return reps
Ejemplo n.º 6
0
def import_tree(graph):
    mg = makeGraph('', graph=graph)
    mg.add_known_namespaces('owl', 'obo', 'dc', 'dcterms', 'dctypes', 'skos',
                            'NIFTTL')
    j = mg.make_scigraph_json('owl:imports', direct=True)
    t, te = creatTree(*Query('NIFTTL:nif.ttl', 'owl:imports', 'OUTGOING', 30),
                      json=j,
                      prefixes=mg.namespaces)
    #print(t)
    return t, te
Ejemplo n.º 7
0
def graph_todo(graph, curie_prefixes, get_values):
    ug = makeGraph('big-graph', graph=graph)
    ug.add_known_namespaces('NIFRID')
    fragment_prefixes, ureps = get_values(ug)
    #all_uris = sorted(set(_ for t in graph for _ in t if type(_) == rdflib.URIRef))  # this snags a bunch of other URIs
    #all_uris = sorted(set(_ for _ in graph.subjects() if type(_) != rdflib.BNode))
    #all_uris = set(spo for t in graph.subject_predicates() for spo in t if isinstance(spo, rdflib.URIRef))
    all_uris = set(spo for t in graph for spo in t
                   if isinstance(spo, rdflib.URIRef))
    prefs = set(
        _.rsplit('#', 1)[0] +
        '#' if '#' in _ else (_.rsplit('_', 1)[0] +
                              '_' if '_' in _ else _.rsplit('/', 1)[0] + '/')
        for _ in all_uris)
    nots = set(_ for _ in prefs if _ not in curie_prefixes)  # TODO
    sos = set(prefs) - set(nots)
    all_uris = [u if u not in ureps else ureps[u] for u in all_uris]
    #to_rep = set(_.rsplit('#', 1)[-1].split('_', 1)[0] for _ in all_uris if 'ontology.neuinfo.org' in _)
    #to_rep = set(_.rsplit('#', 1)[-1] for _ in all_uris if 'ontology.neuinfo.org' in _)

    ignore = (
        # deprecated and only in as annotations
        'NIFGA:birnAnatomy_011',
        'NIFGA:birnAnatomy_249',
        'NIFORG:birnOrganismTaxon_19',
        'NIFORG:birnOrganismTaxon_20',
        'NIFORG:birnOrganismTaxon_21',
        'NIFORG:birnOrganismTaxon_390',
        'NIFORG:birnOrganismTaxon_391',
        'NIFORG:birnOrganismTaxon_56',
        'NIFORG:birnOrganismTaxon_68',
        'NIFINV:birnlexInvestigation_174',
        'NIFINV:birnlexInvestigation_199',
        'NIFINV:birnlexInvestigation_202',
        'NIFINV:birnlexInvestigation_204',
    )
    ignore = tuple(ug.expand(i) for i in ignore)

    non_normal_identifiers = sorted(
        u for u in all_uris if 'ontology.neuinfo.org' in u
        and noneMembers(u, *fragment_prefixes) and not u.endswith('.ttl')
        and not u.endswith('.owl') and u not in ignore)
    print(len(prefs))
    embed()
Ejemplo n.º 8
0
def switchURIs(g, swap, *args):
    _, fragment_prefixes = args
    reps = []
    prefs = {None}
    addpg = makeGraph('', graph=g)
    for t in g:
        nt, ireps, iprefs = tuple(zip(*swap(t, *args)))
        if t != nt:
            g.remove(t)
            g.add(nt)

        for rep in ireps:
            if rep is not None:
                reps.append(rep)

        for pref in iprefs:
            if pref not in prefs:
                prefs.add(pref)
                addpg.add_known_namespaces(fragment_prefixes[pref])
    return reps
Ejemplo n.º 9
0
def convert(f):
    if f in exclude:
        print('skipping', f)
        return f
    ps = {
        'PROTEGE': 'http://protege.stanford.edu/plugins/owl/protege#',
    }
    PREFIXES.update(ps)
    pi = {v: k for k, v in PREFIXES.items()}
    pi.pop(None)

    graph = rdflib.Graph()
    graph.parse(f, format='turtle')
    namespaces = [str(n) for p, n in graph.namespaces()]
    prefs = []

    if f == 'NIF-Dysfunction.ttl':
        prefs.append('OBO')
    elif f == 'NIF-Eagle-I-Bridge.ttl':
        prefs.append('IAO')
    elif f == 'resources.ttl':
        prefs.append('IAO')
    elif f == 'NIF-Investigation.ttl':
        prefs.append('IAO')

    asdf = {v: k for k, v in ps.items()}
    asdf.update(pi)

    # determine which prefixes we need
    for rn, rp in asdf.items():
        for uri in list(graph.subjects()) + list(graph.predicates()) + list(
                graph.objects()):
            if type(uri) == rdflib.BNode:
                continue
            elif uri.startswith(rn):
                if rp == 'OBO' or rp == 'IAO' or rp == 'NIFTTL':
                    if rp == 'IAO' and 'IAO_0000412' in uri:  # for sequence_slim
                        pass
                    else:
                        continue
                prefs.append(rp)
                break

    if prefs:
        ps = makePrefixes(*prefs)
    else:
        ps = makePrefixes('rdfs')

    if 'parcellation/' in f:
        nsl = {p: n for p, n in graph.namespaces()}
        if '' in nsl:
            ps[''] = nsl['']
        elif 'hbaslim' in f:
            ps['HBA'] = nsl['HBA']
        elif 'mbaslim' in f:
            ps['MBA'] = nsl['MBA']
        elif 'cocomac' in f:
            ps['cocomac'] = nsl['cocomac']

    ng = makeGraph(os.path.splitext(f)[0],
                   prefixes=ps,
                   writeloc=os.path.expanduser('~/git/NIF-Ontology/ttl/'))
    [ng.add_node(*n) for n in graph.triples([None] * 3)]
    #print(f, len(ng.g))
    ng.write()
    return f
Ejemplo n.º 10
0
def convert(f, prefixes):
    if f in exclude:
        print('skipping', f)
        return f
    pi = {v: k for k, v in prefixes.items()}

    graph = rdflib.Graph()
    graph.parse(f, format='turtle')
    namespaces = [str(n) for p, n in graph.namespaces()]
    prefs = ['']

    asdf = {}  #{v:k for k, v in ps.items()}
    asdf.update(pi)

    # determine which prefixes we need
    for uri in list(graph.subjects()) + list(graph.predicates()) + list(
            graph.objects()):
        if uri.endswith('.owl') or uri.endswith('.ttl'):
            continue  # don't prefix imports
        for rn, rp in sorted(
                asdf.items(),
                key=lambda a: -len(a[0])):  # make sure we get longest first
            lrn = len(rn)
            if type(uri) == rdflib.BNode:
                continue
            elif uri.startswith(
                    rn) and '#' not in uri[lrn:] and '/' not in uri[
                        lrn:]:  # prevent prefixing when there is another sep
                prefs.append(rp)
                break

    if prefs:
        ps = makePrefixes(*prefs)
    else:
        ps = makePrefixes('rdfs')

    if 'parcellation/' in f:
        nsl = {p: n for p, n in graph.namespaces()}
        if '' in nsl:
            ps[''] = nsl['']
        elif 'hbaslim' in f:
            ps['HBA'] = nsl['HBA']
        elif 'mbaslim' in f:
            ps['MBA'] = nsl['MBA']
        elif 'cocomac' in f:
            ps['cocomac'] = nsl['cocomac']

    # special cases for NIFORG, NIFINV, NIFRET where there identifiers in
    # annotation properties that share the prefix, so we warn incase
    # at some point in the future for some reason want them again...
    if f == 'NIF-Organism.ttl':
        print('WARNING: special case for NIFORG')
        ps.pop('NIFORG')
    elif f == 'NIF-Investigation.ttl':
        print('WARNING: special case for NIFINV')
        ps.pop('NIFINV')
    elif f == 'unused/NIF-Retired.ttl':
        print('WARNING: special case for NIFRET')
        ps.pop('NIFGA')

    ng = makeGraph('', prefixes=ps)
    ng.filename = f
    [ng.g.add(t) for t in graph]
    #[ng.add_trip(*n) for n in graph.triples([None]*3)]
    #print(f, len(ng.g))
    ng.write()
    return f
Ejemplo n.º 11
0
            fmt = 'turtle' if ext == '.ttl' else 'xml'
            if noneMembers(o, 'go.owl', 'uberon.owl', 'pr.owl', 'doid.owl',
                           'taxslim.owl') or dobig:
                graph.parse(o, format=fmt)


for i in range(4):
    repeat(True)

with open(
        os.path.expanduser(
            '~/git/NIF-Ontology/scigraph/nifstd_curie_map.yaml'), 'rt') as f:
    wat = yaml.load(f)
vals = set(wat.values())

mg = makeGraph('nifall', makePrefixes('owl', 'skos', 'oboInOwl'), graph=graph)
mg.del_namespace('')

old_namespaces = list(graph.namespaces())
ng_ = makeGraph('',
                prefixes=makePrefixes('oboInOwl', 'skos'),
                graph=rdflib.Graph())
[ng_.g.add(t) for t in mg.g]
[ng_.add_namespace(n, p) for n, p in wat.items() if n != '']
#[mg.add_namespace(n, p) for n, p in old_namespaces if n.startswith('ns') or n.startswith('default')]
#[mg.del_namespace(n) for n in list(mg.namespaces)]
#graph.namespace_manager.reset()
#[mg.add_namespace(n, p) for n, p in wat.items() if n != '']


def for_burak(ng):
Ejemplo n.º 12
0
from IPython import embed

source = 'https://raw.githubusercontent.com/BlueBrain/nat/master/nat/modelingDictionary.csv'
delimiter = ';'

resp = requests.get(source)
rows = [
    r for r in csv.reader(resp.text.split('\n'), delimiter=delimiter)
    if r and r[0][0] != '#'
]
header = [
    'Record_ID', 'parent_category', 'name', 'description', 'required_tags'
]

PREFIXES = makePrefixes('owl', 'skos', 'ILX', 'ILXREPLACE', 'definition')
graph = makeGraph('measures', prefixes=PREFIXES)


class nat(rowParse):
    def Record_ID(self, value):
        print(value)
        self.old_id = value
        self._id = ILXREPLACE(value)

    def parent_category(self, value):
        self.super_old_id = value
        self.super_id = ILXREPLACE(value)

    def name(self, value):
        self.hidden = value
        self.label = value.replace('_', ' ')
Ejemplo n.º 13
0
def main():
    # TODO extracly only NLX only with superclasses for fariba
    # FIXME there is an off by 1 error
    #nlxdb = get_nlxdb()

    scr_graph = get_scr()
    existing_xrefs = set([s_o[1].toPython() for s_o in scr_graph.subject_objects(rdflib.term.URIRef('http://www.geneontology.org/formats/oboInOwl#hasDbXref'))])

    ONT_PATH = 'http:/github.com/tgbugs/nlxeol/'
    filename = 'neurolex_basic'
    PREFIXES = {'to':'do',
                'NLXWIKI':'http://neurolex.org/wiki/',
                'ILX':'http://uri.interlex.org/base/ilx_',
                'ilx':'http://uri.interlex.org/base/',
                'owl':'http://www.w3.org/2002/07/owl#',
                'skos':'http://www.w3.org/2004/02/skos/core#',
                'OBOANN':'http://ontology.neuinfo.org/NIF/Backend/OBO_annotation_properties.owl#',
                'oboInOwl':'http://www.geneontology.org/formats/oboInOwl#',
                }

    ontid = ONT_PATH + filename + '.ttl'
    new_graph = makeGraph(filename, PREFIXES)
    new_graph.add_ont(ontid,
                      'Conversion of the neurolex database to ttl',
                      'Neurolex dump',
                      'This file is automatically generated from nlxeol/process_csv.py',
                      TODAY)
 
    #with open('neuron_data_curated.csv', 'rt') as f:
    with open('neurolex_full.csv', 'rt') as f:
        rows = [r for r in csv.reader(f)]
    new_rows = [list(r) for r in zip(*[c for c in zip(*rows) if any([r for r in c if r != c[0]])])]
    no_data_cols = set(rows[0]) - set(new_rows[0])
    print(no_data_cols)

    #header[header.index('Phenotypes:_ilx:has_location_phenotype')] = 'Phenotypes'
    # convert the header names so that ' ' is replaced with '_'
    state = basicConvert(new_graph, new_rows, existing_xrefs)
    #state = convertCurated(new_graph, new_rows)
    #embed()
    #return

    #_ = [print(i) for i in sorted([datetime.strptime(t, '%d %B %Y') for _ in state._set_ModifiedDate for t in _.split(',') if _])]
    _ = [print(i) for i in sorted(state.chebi_ids)]
    _ = [print(i) for i in sorted(state.drugbank_ids)]
    _ = [print(i) for i in sorted(state.t3db_ids)]
    _ = [print(i) for i in sorted(state.uni_ids)]
    _ = [print(i) for i in sorted(state.bad_ids)]
    #_ = [print(i) for i in sorted(state.failed_resolution)]
    #_ = [print(i) for i in sorted(state._set_LocationOfAxonArborization)]

    # deal with unis TODO needs to be embeded in state.Id or something incase of reference
    unis = {None:[]}
    lookup_new_id = {}
    for id_ in sorted([_.split(':')[1] for _ in state.uni_ids]):
        matches = [_ for _ in scr_graph.triples((None, None, rdflib.Literal(id_)))]
        if len(matches) > 1:
            print(matches)
        elif not matches:
            unis[None].append(id_)
            lookup_new_id[id_] = None
        else:
            match = matches[0]
            unis[match[0].rsplit('/',1)[1].replace('_',':')] = id_
            lookup_new_id[id_] = match[0].rsplit('/',1)[1].replace('_',':')

    #return

    new_graph.write(convert=True)

    embed()
Ejemplo n.º 14
0
def main():
    # load in our existing graph
    # note: while it would be nice to allow specification of phenotypes to be decoupled
    # from insertion into the graph... maybe we could enable this, but it definitely seems
    # to break a number of nice features... and we would need the phenotype graph anyway
    EXISTING_GRAPH = rdflib.Graph()
    sources = ('/tmp/NIF-Neuron-Phenotype.ttl', '/tmp/NIF-Neuron-Defined.ttl',
               '/tmp/NIF-Neuron.ttl', '/tmp/NIF-Phenotype-Core.ttl',
               '/tmp/NIF-Phenotypes.ttl', '/tmp/hbp-special.ttl')
    for file in sources:
        EXISTING_GRAPH.parse(file, format='turtle')
    EXISTING_GRAPH.namespace_manager.bind(
        'ILXREPLACE',
        makePrefixes('ILXREPLACE')['ILXREPLACE'])
    #EXISTING_GRAPH.namespace_manager.bind('PR', makePrefixes('PR')['PR'])

    PREFIXES = makePrefixes(
        'owl',
        'skos',
        'PR',
        'UBERON',
        'NCBITaxon',
        'ILXREPLACE',
        'ilx',
        'ILX',
        'NIFCELL',
        'NIFMOL',
    )
    graphBase.core_graph = EXISTING_GRAPH
    graphBase.out_graph = rdflib.Graph()
    graphBase._predicates = getPhenotypePredicates(EXISTING_GRAPH)

    g = makeGraph('merged',
                  prefixes={k: str(v)
                            for k, v in EXISTING_GRAPH.namespaces()},
                  graph=EXISTING_GRAPH)
    reg_neurons = list(
        g.g.subjects(rdflib.RDFS.subClassOf, g.expand(NIFCELL_NEURON)))
    tc_neurons = [
        _ for (_, ) in
        g.g.query('SELECT DISTINCT ?match WHERE {?match rdfs:subClassOf+ %s}' %
                  NIFCELL_NEURON)
    ]
    def_neurons = g.get_equiv_inter(NIFCELL_NEURON)

    nodef = sorted(set(tc_neurons) - set(def_neurons))
    MeasuredNeuron.out_graph = rdflib.Graph()
    Neuron.out_graph = rdflib.Graph()
    mns = [MeasuredNeuron(id_=n) for n in nodef]
    dns = [Neuron(id_=n) for n in sorted(def_neurons)]
    #dns += [Neuron(*m.pes) if m.pes else m.id_ for m in mns]
    dns += [Neuron(*m.pes) for m in mns if m.pes]

    # reset everything for export
    Neuron.out_graph = rdflib.Graph()
    ng = makeGraph('output', prefixes=PREFIXES, graph=Neuron.out_graph)
    Neuron.existing_pes = {
    }  # reset this as well because the old Class references have vanished
    dns = [Neuron(*d.pes) for d in set(dns)
           ]  # TODO remove the set and use this to test existing bags?
    from neuron_lang import WRITEPYTHON
    WRITEPYTHON(sorted(dns))
    ng.add_ont(ILXREPLACE('defined-neurons'), 'Defined Neurons', 'NIFDEFNEU',
               'VERY EXPERIMENTAL', '0.0.0.1a')
    ng.add_node(ILXREPLACE('defined-neurons'), 'owl:imports',
                'http://ontology.neuinfo.org/NIF/ttl/NIF-Phenotype-Core.ttl')
    ng.add_node(ILXREPLACE('defined-neurons'), 'owl:imports',
                'http://ontology.neuinfo.org/NIF/ttl/NIF-Phenotypes.ttl')
    ng.write()
    bads = [
        n for n in ng.g.subjects(rdflib.RDF.type, rdflib.OWL.Class)
        if len(list(ng.g.predicate_objects(n))) == 1
    ]
    embed()
Ejemplo n.º 15
0
def g(filename):
    return makeGraph('', graph=rdflib.Graph().parse(filename, format='turtle'))
Ejemplo n.º 16
0
 def attachPrefixes(*prefixes, graph=None):
     return makeGraph('', prefixes=makePrefixes(*prefixes), graph=graph)
Ejemplo n.º 17
0
def backend_refactor_values():
    uri_reps_lit = {
        # from https://github.com/information-artifact-ontology/IAO/blob/master/docs/BFO%201.1%20to%202.0%20conversion/mapping.txt
        'http://www.ifomis.org/bfo/1.1#Entity': 'BFO:0000001',
        'BFO1SNAP:Continuant': 'BFO:0000002',
        'BFO1SNAP:Disposition': 'BFO:0000016',
        'BFO1SNAP:Function': 'BFO:0000034',
        'BFO1SNAP:GenericallyDependentContinuant': 'BFO:0000031',
        'BFO1SNAP:IndependentContinuant': 'BFO:0000004',
        'BFO1SNAP:MaterialEntity': 'BFO:0000040',
        'BFO1SNAP:Quality': 'BFO:0000019',
        'BFO1SNAP:RealizableEntity': 'BFO:0000017',
        'BFO1SNAP:Role': 'BFO:0000023',
        'BFO1SNAP:Site': 'BFO:0000029',
        'BFO1SNAP:SpecificallyDependentContinuant': 'BFO:0000020',
        'BFO1SPAN:Occurrent': 'BFO:0000003',
        'BFO1SPAN:ProcessualEntity': 'BFO:0000015',
        'BFO1SPAN:Process': 'BFO:0000015',
        'BFO1SNAP:ZeroDimensionalRegion': 'BFO:0000018',
        'BFO1SNAP:OneDimensionalRegion': 'BFO:0000026',
        'BFO1SNAP:TwoDimensionalRegion': 'BFO:0000009',
        'BFO1SNAP:ThreeDimensionalRegion': 'BFO:0000028',
        'http://purl.org/obo/owl/OBO_REL#bearer_of': 'RO:0000053',
        'http://purl.org/obo/owl/OBO_REL#inheres_in': 'RO:0000052',
        'ro:has_part': 'BFO:0000051',
        'ro:part_of': 'BFO:0000050',
        'ro:has_participant': 'RO:0000057',
        'ro:participates_in': 'RO:0000056',
        'http://purl.obolibrary.org/obo/OBI_0000294': 'RO:0000059',
        'http://purl.obolibrary.org/obo/OBI_0000297': 'RO:0000058',
        'http://purl.obolibrary.org/obo/OBI_0000300': 'BFO:0000054',
        'http://purl.obolibrary.org/obo/OBI_0000308': 'BFO:0000055',

        # more bfo
        'BFO1SNAP:SpatialRegion': 'BFO:0000006',
        'BFO1SNAP:FiatObjectPart': 'BFO:0000024',
        'BFO1SNAP:ObjectAggregate': 'BFO:0000027',
        'BFO1SNAP:Object': 'BFO:0000030',
        #'BFO1SNAP:ObjectBoundary'  # no direct replacement, only occurs in unused
        #'BFO1SPAN:ProcessAggregate'  # was not replaced, could simply be a process itself??
        #'BFO1SNAP:DependentContinuant'  # was not replaced

        # other
        #'ro:participates_in'  # above
        #'ro:has_participant'  # above
        #'ro:has_part',  # above
        #'ro:part_of',  # above
        #'ro:precedes'  # unused and only in inferred
        #'ro:preceded_by'  # unused and only in inferred
        #'ro:transformation_of'  # unused and only in inferred
        #'ro:transformed_into'  # unused and only in inferred
        'http://purl.org/obo/owl/obo#inheres_in': 'RO:0000052',
        'http://purl.obolibrary.org/obo/obo#towards': 'RO:0002503',
        'http://purl.org/obo/owl/pato#towards': 'RO:0002503',
        'http://purl.obolibrary.org/obo/pato#inheres_in': 'RO:0000052',
        'BIRNLEX:17': 'RO:0000053',  # is_bearer_of
        'http://purl.obolibrary.org/obo/pato#towards': 'RO:0002503',
        'ro:adjacent_to': 'RO:0002220',
        'ro:derives_from': 'RO:0001000',
        'ro:derives_into': 'RO:0001001',
        'ro:agent_in': 'RO:0002217',
        'ro:has_agent': 'RO:0002218',
        'ro:contained_in': 'RO:0001018',
        'ro:contains': 'RO:0001019',
        'ro:located_in': 'RO:0001025',
        'ro:location_of': 'RO:0001015',
        'ro:has_proper_part': 'NIFRID:has_proper_part',
        'ro:proper_part_of':
        'NIFRID:proper_part_of',  # part of where things are not part of themsevles need to review
    }
    ug = makeGraph('',
                   prefixes=makePrefixes('ro', 'RO', 'BIRNLEX', 'NIFRID',
                                         'BFO', 'BFO1SNAP', 'BFO1SPAN'))
    ureps = {
        ug.check_thing(k): ug.check_thing(v)
        for k, v in uri_reps_lit.items()
    }

    return ureps