#Importing Modules
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
#Loading and Serilizin Combined Dataset
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
#g.parse("C:/publish/RDF/OWL.ttl",format="ttl")
g.parse("C:/publish/RDF/WSP1WS8.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
#qUERY formulation
properties1 = e.select("""
SELECT ?o ?o1 ?o2
WHERE {
?s <http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundOn> ?o .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#HasLat> ?o1 .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#HasLong> ?o2 .
}
""")
properties1
#Saving and Printing Result
print(properties1)
import numpy as np
np.random.seed(5)
from nltk.corpus import wordnet
import rdflib
from rdflib.graph import *
from gastrodon import LocalEndpoint, one, QName
Ont = Graph()
Ont.parse("C:/publish/RDF/OWL.ttl", format="ttl")
OpenOnto = open("OntClasses.txt", "w")
len(Ont)
e = LocalEndpoint(Ont)
Classes = e.select("""
SELECT ?s
WHERE
{
?s ?p ?o .
}
""")
print(Classes)
pit = "Desert"
p = "Mangrove", "adaptation", "Biome", "Desert", "Community", "Conservation", "habitat", "Species", "City", "Population", "Taxon", "Nomenclature", "Landscape", "Extinction", "Diversity", "Ecology", "Environment", "Watershed", "Seagrass", "Assemblage"
def WordsMeanng(c):
for a in c:
i = str(a)
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
import numpy as np
import pandas as pd
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/OWL.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
properties1 = e.select("""
SELECT ?o ?o2
{
?s <http://www.semanticweb.org/yawfrimpong/ontologies/\
untitled-ontology-13#FeedOn> "GrassLand" .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/\
untitled-ontology-13#HasLat> ?o .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/\
untitled-ontology-13#FoundIn> "San Francisco" .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/\
untitled-ontology-13#HasName> "Owl" .
} """)
properties1
file = open("GrassLand.txt", "w")
data = properties1.values
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint,one,QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/Ontology.ttl",format="ttl")
len(g)
e=LocalEndpoint(g)
Q1=e.select("""
SELECT ?p
WHERE
{
?s ?p ?o .
}
""")
Q1
print(Q1)
a =str(Q1)
NewText.write(a)
np.random.seed(5)
from nltk.corpus import wordnet
g = Graph()
g.parse("Ont.owl", format="ttl")
#print(len(g))
m = open("Paul.txt", "w")
pd.DataFrame()
#for a, b, c, in g:
# m.write(a)
e=LocalEndpoint(g)
qres = e.select(
"""
SELECT ?s
WHERE {
?s ?p ?o .
}""")
#print(qres)
df = pd.DataFrame(qres)
random.randrange(20)
#b = random.sample((list(df.iloc[:],20)))
c = df.iloc[:19,-1]
#a = df.iloc[np.random.choice((df.iloc[:],21)),-1]
fit = open("WordMeaning.txt","r+")
#for i in fit:
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint,one,QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/Birds.ttl",format="ttl")
len(g)
e=LocalEndpoint(g)
Q1=e.select("""
SELECT (Distinct ?o as ?Land_Information)
WHERE
{
?s ?p "San Francisco" .
?s <http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundOn> ?o .
}
""")
Q1
print(Q1)
a =str(Q1)
NewText.write(a)
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/WSP1WS8.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
properties1 = e.select("""
select ?o as ?Land_Information
WHERE {
?s ?p ?o .
FILTER(STRSTARTS(STR(?p),"http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundOn"))
} """)
properties1
print(properties1)
f_dbp_onto = input_path + "DBpedia ontology 2016/" + "dbpedia_2016-10.nt"
f_dbp_people = input_path + "DBpedia_people/DBpedia_people_no-semantics/" + "goldStandard_dbp_cleaned.nt"
f_disease = input_path + "Diseases/no-semantics/" + "goldStandard_diseases.nt"
dbpedia_ontology = Graph()
dbpedia_ontology.parse(f_dbp_onto, format="nt")
dbpedia_People = Graph()
dbpedia_People.parse(f_dbp_people, format="nt")
disease_ICD = Graph()
disease_ICD.parse(f_disease, format="nt")
print(len(dbpedia_ontology))
print(len(dbpedia_People))
print(len(disease_ICD))
dbp_p = LocalEndpoint(dbpedia_People)
drug = LocalEndpoint(disease_ICD)
dbp_onto = LocalEndpoint(dbpedia_ontology)
subject = dbp_p.select("""
SELECT ?s (COUNT(*) AS ?count) {
?s ?p ?o .
} GROUP BY ?s ORDER BY DESC(?count)
""")
properties = dbp_p.select("""
SELECT ?p (COUNT(*) AS ?count) {
?s ?p ?o .
} GROUP BY ?p ORDER BY DESC(?count)
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/WSP1WS8.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
properties1 = e.select("""
select DISTINCT ?o
WHERE {
?s "<http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundIn>" ?o .
} """)
properties1
print(properties1)
#print(g.serialize(destination='D:/git/silk/data/staat.rdf',format="application/rdf+xml"))
'''
# in the next step.
g = Graph()
# Walks through output path from the netowlCurl function and parses all RDF/XML Documents
for root, dir, files in os.walk(rdfOutDir):
for file in files:
if file.endswith(rdfOutExt):
filePath = os.path.join(root, file)
print("Parsing " + file + "...")
try:
g.parse(filePath, format='xml')
except Exception as ex:
print(ex)
# Create Local SPARQL Endpoint on graph created in previous step
e = LocalEndpoint(g)
#Queries the SPARQL endpoint for the various addresses located in the documents
address=e.select("""
SELECT ?s ?o ?label{
?s netowl:Entity.Address.Mail..name ?o .
?s rdfs:label ?label .
}
""")
address.set_index("label")
#Geocodes the addresses and adds them to the map widget as a feature collection
locations = gis.content.import_data(address, {"Address" : "label"})
#Creates a hosted feature service from the feature
# collection created in the previous step
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/WSP1WS8.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
properties1 = e.select("""
SELECT ?o
{
?s '<http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundIn>' ?o .
}
""")
properties1
print(properties1)
#print(g.serialize(destination='D:/git/silk/data/staat.rdf',format="application/rdf+xml"))
'''
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
NewText = open("M.txt", "w")
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("C:/publish/RDF/WSP1WS8.ttl", format="ttl")
len(g)
e = LocalEndpoint(g)
Q1 = e.select("""
SELECT ?o (COUNT(?o) as ?oCount)
WHERE
{
?s <http://www.semanticweb.org/yawfrimpong/ontologies/untitled-ontology-13#FoundIn> ?o .
}
GROUP BY ?p
'ORDER BY DESC(?oCount)'
Limit 1
""")
Q1
print(Q1)
#Importing Modules
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
#Loading the Combined Dataset
from gastrodon import LocalEndpoint,one,QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
#g.parse("C:/publish/RDF/OWL.ttl",format="ttl")
g.parse("C:/publish/RDF/WSP1WS8.ttl",format="ttl")
len(g)
e=LocalEndpoint(g)
#Query formulation
properties1=e.select("""
SELECT ?o ?o1 ?o2
WHERE {
?s <http://www.semanticweb.org/
\yawfrimpong/ontologies/untitled-ontology-13#FoundOn> ?o .
?s <http://www.semanticweb.org/yawfrimpong/ontologies\
/untitled-ontology-13#HasLat> ?o1 .
?s <http://www.semanticweb.org/yawfrimpong/ontologies\
/untitled-ontology-13#HasLong> ?o2 .
?s <http://www.semanticweb.org/yawfrimpong/ontologies\
/untitled-ontology-13#HasLong> "San Francisco" .
?s <http://www.semanticweb.org/yawfrimpong/ontologies\
/untitled-ontology-13FeedOn#> "Forest" .
}
""")
properties1
import rdflib
from rdflib.graph import Graph, URIRef
import matplotlib.pyplot as plt
import gzip
from gastrodon import LocalEndpoint, one, QName
#g = rdflib.ConjunctiveGraph()
g = Graph()
g.parse("WSP1WS718295.ttl", format="n3")
len(g)
print(len(g))
e = LocalEndpoint(g)
properties1 = e.select("""
SELECT *
""")
properties1
print(properties1)
print(e.namespaces())