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csv_to_turtle.py
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#!/usr/bin/env python3
######################################################
# File: csv_to_turtle.py
# Author: Bart Gajderowicz
# Date: May 6, 2022
# Description:
# create a turtle (.ttl) file from csv/excel data files
######################################################
import os
from datetime import datetime
from misc_lib import *
import numpy as np
import pandas as pd
import xlsxwriter
filein = 'unit_tests3.xlsx'
dirin = 'csv'
fileout = 'unit_test3.ttl'
dirout = 'turtle'
class_map = {
"Organization":"Organization",
"Funding":"cp:Funding",
"Service":"cp:Service",
"Client":"cp:Client",
'Client Code':"cp:Code",
'Service Code':"cp:Code",
"Stakeholder":"cids:Stakeholder",
"Program":'cp:Program',
'ImpactModel':'cids:ImpactModel',
'LogicModel':'cids:LogicModel',
'Community':'cp:Community',
'Code':'cids:Code',
'Characteristic':'cids:Characteristic',
'PrimitiveCharacteristic':'cids:PrimitiveCharacteristic',
'CompositeCharacteristic':'cids:CompositeCharacteristic',
'CommunityCharacteristic':'CommunityCharacteristic',
'LandArea':'LandArea',
'Feature':'loc_50871:Feature',
'OrganizationID':'org:OrganizationID'
}
prop_map = {
'hasLegalName':'org:hasLegalName',
'receivedAmount':'cp:receivedAmount',
'requestedAmount':'cp:requestedAmount',
'fundersProgram':'cp:fundersProgram',
'hasProgram':'cids:hasProgram',
'forProgram':'cp:forProgram',
'hasImpactModel': 'cids:hasImpactModel',
'hasService':'cids:hasService',
'hasCode':'cids:hasCode',
'forStakeholder':'cids:forStakeholder',
'locatedIn':'i72:located_in',
'hasCommunityCharacteristic':'cp:hasCommunityCharacteristic',
'hasCharacteristic':'cids:hasCharacteristic',
'hasRequirement':'cp:hasRequirement',
'hasFocus':'cp:hasFocus',
'hasLocation':'landuse_50872:hasLocation',
'satisfiesStakeholder':'cp:satisfiesStakeholder',
'hasLandArea':'landuse_50872:hasLandArea',
'hasIdentifier':'org:hasIdentifier',
'hasStakeholder':'cids:hasStakeholder',
'hasName':'cids:hasName',
'hasPart':'oep:hasPart',
'hasDescription':'cids:hasDescription',
'hasContributingStakeholder':'cids:hasContributingStakeholder',
'hasBeneficialStakeholder':'cids:hasBeneficialStakeholder',
'partOf':'oep:partOf',
'hasMode':'cp:hasMode',
'forOrganization':'cids:forOrganization',
'hasIndicator':'cids:hasIndicator',
'hasOutcome':'cids:hasOutcome',
'hasID':'org:hasID',
'hasNumber':'hasNumber',
}
PREFIX = 'cp'
# @prefix geo: <http://release.niem.gov/niem/adapters/geospatial/3.0#>.
# w3_org = default_world.get_namespace("http://www.w3.org/ns/org#")
# @prefix gml: <http://www.opengis.net/gml/3.2#>.
# @prefix loc: <http://ontology.eil.utoronto.ca/5087/1/SpatialLoc/>.
text = '''
################################################################
# Turtle File Generated by: csv_to_turtle.py
# Date : %s
# github: https://github.com/csse-uoft/csv2turtle
################################################################
'''%(datetime.now().strftime("%B %d, %Y %H:%M:%S"))
text += '''
@prefix act: <http://ontology.eil.utoronto.ca/tove/activity#>.
@prefix dcat: <http://www.w3.org/ns/dcat#>.
@prefix ic: <http://ontology.eil.utoronto.ca/tove/icontact#">.
@prefix owl: <http://www.w3.org/2002/07/owl#>.
@prefix sur: <http://ontology.eil.utoronto.ca/tove/survey#>.
@prefix dqv: <http://www.w3.org/ns/dqv#>.
@prefix qb: <http://purl.org/linked-data/cube#>.
@prefix dcterms: <http://purl.org/dc/terms#>.
@prefix loc_50871: <http://ontology.eil.utoronto.ca/5087/1/SpatialLoc/>.
@prefix act_50871: <http://ontology.eil.utoronto.ca/5087/1/Activity#>.
@prefix city_50872: <http://ontology.eil.utoronto.ca/5087/2/City#>.
@prefix cityservice_50872: <http://ontology.eil.utoronto.ca/5087/2/CityService#>.
@prefix landuse_50872: <http://ontology.eil.utoronto.ca/5087/2/LandUse/>.
@prefix time: <http://www.w3.org/2006/time#>.
@prefix oep: <http://www.w3.org/2001/sw/BestPractices/OEP/SimplePartWhole/part.owl#>.
@prefix xsd: <http://www.w3.org/2001/XMLSchema#>.
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>.
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix rel: <http://purl.org/vocab/relationship/> .
@prefix geo: <http://www.opengis.net/ont/geosparql#>.
@prefix i72: <http://ontology.eil.utoronto.ca/ISO21972/iso21972#>.
@prefix org: <http://ontology.eil.utoronto.ca/tove/organization#>.
@prefix cids: <http://ontology.eil.utoronto.ca/cids/cids#>.
@prefix cp: <http://helpseeker.co/compass#> .
@prefix : <http://helpseeker.co/compass#> .
<local> rdf:type owl:Ontology ;
owl:imports <https://github.com/csse-uoft/compass-ontology/releases/download/latest/compass.owl> .
'''
def entity_str(e,prefix=PREFIX):
e=e.strip()
return e if ':' in e else "%s:%s"%(prefix,e)
def format_lists(insts, entity=True):
insts = flatten([s.split(',') for s in insts if s == s])
insts = list(set([s.strip() for s in insts]))
if entity:
insts = [entity_str(s) for s in insts]
return insts
def format_characteristics_text(inst, chars, prop0='hasCharacteristic'):
text = ''
if type(chars) == str:
# tmp = chars.strip().split()
tmp = [c.strip() for c in chars.split(',')]
elif type(chars) == list:
tmp = chars
# tmp = ','.join(chars)
# tmp = ','.join([c.strip() for c in chars])
else:
raise ValueError("chars parameter must be a str or a list")
# if tmp.startswith('Comp-CL-'):
# tmp = [c.strip() for c in tmp.split(',')]
for code_text in tmp:
if code_text != code_text:
return ''
elif code_text.startswith('cids:hasCode '):
code_text = code_text.replace('cids:hasCode ','')
prop = entity_str(prop_map['hasCode'])
text1 = None
if code_text.startswith('Comp-CL-'):
# providing list of composite char labels
code_text = entity_str(code_text)
prop1 = entity_str(prop_map[prop0])
text += "%s %s %s.\n"%(inst,prop1,code_text)
klass = entity_str(class_map['CompositeCharacteristic'])
prop1 = entity_str(prop_map['hasPart'])
codes = [entity_str('CL-%s'%(c)) for c in re.sub(r'[a-z:]*Comp\-CL\-','',code_text).split('_')]
text1 = '; '.join(["%s %s"%(prop,c) for c in codes])
text += "%s rdf:type %s.\n"%(code_text,klass)
text += "%s %s [%s].\n"%(code_text,prop1,text1)
elif code_text.startswith('CL-'):
# providing list of codes
codes = [entity_str(c.strip()) for c in code_text.split(',')]
codes.sort()
if len(codes) == 1:
klass = entity_str(class_map['PrimitiveCharacteristic'])
prop1 = entity_str(prop_map[prop0])
code = codes[0]
text += "%s %s [%s %s].\n"%(inst,prop1,prop,code)
elif len(codes) > 1:
comp_inst = entity_str('Comp-CL-'+'_'.join([re.sub(r'[a-z:]*CL-','',c) for c in codes]))
klass = entity_str(class_map['CompositeCharacteristic'])
prop1 = entity_str(prop_map['hasPart'])
prop0 = entity_str(prop_map[prop0])
text1 = '; '.join(["%s %s"%(prop,c) for c in codes])
text += "%s rdf:type %s.\n"%(comp_inst,klass)
text += "%s %s [%s].\n"%(comp_inst,prop1,text1)
text += "%s %s %s.\n"%(inst, prop0, comp_inst)
return text
# Read main Ex ffle
xls = pd.ExcelFile(dirin+'/'+filein)
# stakeholders
df = pd.read_excel(xls,'Stakeholders', header=1)
df = df.dropna(how='all')
sids = []
for _,row in df.iterrows():
sids.append(row['Stakeholder'].split(','))
sids = list(set(flatten(sids)))
sids.sort()
stakeholders = {}
for sid in sids:
stakeholders[sid] = {'hasCode':[], "location":np.nan}
for _,row in df.iterrows():
for sid in row['Stakeholder'].split(','):
if row['hasCode'] == row['hasCode']:
for code in [c.strip() for c in row['hasCode'].split(',')]:
stakeholders[sid]['hasCode'].append(code)
if row['location'] == row['location']:
stakeholders[sid]['location'] = row['location']
for k,v in stakeholders.items():
stakeholders[k]['hasCode'] = list(set(v['hasCode']))
# insert stakeholders
text += "#####################\n# Stakeholders\n####################\n"
for sid,props in stakeholders.items():
text += "\n# Stakeholder (%s)\n"%(sid)
sklass = entity_str(class_map["Stakeholder"])
sinst = entity_str(sid)
text += "%s rdf:type %s.\n"%(sinst, sklass)
prop = prop_map['locatedIn']
if props['location']== props['location']:
inst = entity_str(props['location'])
text += "%s %s %s.\n"%(sinst, prop, inst)
text += format_characteristics_text(sinst, props["hasCode"])
text += "\n"
# insert Taxonomy and CodeList
text += "#####################\n# Taxonomies\n####################\n"
df = pd.read_excel(xls,'Taxonomies', header=1)
df = df.dropna(how='all')
for _,row in df.iterrows():
subj, obj = entity_str(row['Class']),entity_str(row['subClassOf'])
text += "%s rdfs:subClassOf %s.\n"%(subj, obj)
if row['Instance'] == row['Instance']:
subj, obj = entity_str(row['Instance']), entity_str(row['Class'])
text += "%s rdf:type %s;\n"%(subj,obj)
obj = entity_str(row['CodeValue'])
prop = prop_map['hasCode']
text += " %s %s;\n"%(prop, obj)
text += ".\n"
text += "\n"
# Communities
df = pd.read_excel(xls,'Communities', header=1)
df = df.dropna(how='all')
communities = {}
for _,row in df[~df['Community'].isnull()].iterrows():
comm = row['Community']
communities[comm] = {}
chars = []
for s in [s.strip() for s in row['CommunityCharacteristic'].split(',')]:
chars.append(s)
communities[comm]['CommunityCharacteristic'] = list(set(chars))
communities[comm]['hasNumber'] = row['hasNumber']
communities[comm]['hasLandArea'] = row['hasLandArea']
communities[comm]['parcelHasLocation'] = row['parcelHasLocation']
# CityDivition
# cp:Community subClassOf iso5087-2:CityDivision
# ios5087-2:CityDivision iso5087 hasLandArea iso5087-2:LandArea
# iso587-2:LandArea subClassOf iso5078-1:Manifestation
# landuse_50872:hasLocation exactly 1 iso5087-1:Feature
# isoFeature subClassOf loc:Feature
# >>>>>> If Feauter was geo:Feature we woudl use the gml:hasIdentifier
# isoFeature subClassOf geo:Feature
# geo:Feature gml:identifier "Area1"
text += "#####################\n# Communities\n####################\n"
for comm, props in communities.items():
inst = entity_str(comm)
klass = entity_str(class_map['Community'])
text += "%s rdf:type %s.\n"%(inst,klass)
if props['hasNumber'] == props['hasNumber']:
num = float(props['hasNumber'])
prop = entity_str(prop_map['hasNumber'])
text += "%s %s %s.\n"%(inst,prop,num)
land = entity_str(props['hasLandArea'])
prop = entity_str(prop_map['hasLandArea'])
text += "%s %s %s.\n"%(inst,prop,land)
laklass = entity_str(class_map['LandArea'])
text += "%s rdf:type %s;\n"%(land,laklass)
parcel = entity_str(props['parcelHasLocation'])
prop = 'landuse_50872:parcelHasLocation'
text += " %s %s.\n"%(prop, parcel)
fklass = entity_str(class_map['Feature'])
text += "%s rdf:type %s.\n"%(parcel, fklass)
# Community Char
cklass = entity_str(class_map['CommunityCharacteristic'])
compchar_inst = entity_str("%s_CommunityCharacteristic"%(inst))
text += "%s rdf:type %s.\n"%(compchar_inst, cklass)
prop = entity_str(prop_map['hasCommunityCharacteristic'])
text += "%s %s %s.\n"%(inst, prop, compchar_inst)
# Characteristic
char_inst = entity_str("%s_Characteristic"%(inst))
prop = entity_str(prop_map['hasCharacteristic'])
text += "%s %s %s.\n"%(compchar_inst, prop,char_inst)
text += format_characteristics_text(char_inst, [','.join(props['CommunityCharacteristic'])])
text += "\n\n"
# Org properties
text += "#####################\n# Organizations\n####################\n"
df = pd.read_excel(xls,'Organizations', header=1)
df = df.dropna(how='all')
klass = entity_str(class_map["Organization"])
for _,row in df.iterrows():
idinst = row['hasID']
text += "# ------------------\n# Org (%s)\n# ------------------\n"%(idinst)
oinst = entity_str(row['Organization'])
text += "%s rdf:type %s;\n"%(oinst, klass)
nminst = row["hasLegalName"]
prop = entity_str(prop_map['hasLegalName'])
text += " %s \"%s\";\n"%(prop, nminst)
iminst = row["hasImpactModel"]
iminst = format_lists([iminst])
prop = entity_str(prop_map['hasImpactModel'])
text += " %s %s;\n"%(prop, ','.join(iminst))
iminst = row["hasIndicator"]
iminst = format_lists([iminst])
prop = entity_str(prop_map['hasIndicator'])
text += " %s %s;\n"%(prop, ','.join(iminst))
iminst = row["hasOutcome"]
iminst = format_lists([iminst])
prop = entity_str(prop_map['hasOutcome'])
text += " %s %s;\n"%(prop, ','.join(iminst))
inst = entity_str(idinst)
prop = entity_str(prop_map["hasID"])
text += " %s %s;\n"%(prop, inst)
text += ".\n"
# Org hasID
prop = entity_str(prop_map['hasIdentifier'])
idklass = entity_str(class_map['OrganizationID'])
text += "%s rdf:type %s;\n"%(inst, idklass)
text += " %s \"%s\".\n"%(prop,idinst)
# Characteristics
text += format_characteristics_text(inst, row['hasCharacteristic'])
text += "\n"
text += "#####################\n# Funding\n####################\n"
df = pd.read_excel(xls,'Funding', header=1)
df = df.dropna(how='all')
klass = entity_str(class_map["Funding"])
for (finst, receivedFrom, fundersProgram, receivedAmount, requestedAmount),grp in df.groupby(['Funding','receivedFrom','fundersProgram','receivedAmount','requestedAmount']):
finst = entity_str(finst)
text += "\n# Funding %s ------------------\n"%(finst)
# generate Funding instances, includes organizations and programs
fklass = entity_str(class_map["Funding"])
text += "%s rdf:type %s ;\n"%(finst, fklass)
prop = entity_str(prop_map['receivedAmount'])
inst = grp["receivedAmount"]
text += " %s %s ;\n"%(prop, receivedAmount)
prop = entity_str(prop_map['requestedAmount'])
inst = grp["requestedAmount"]
text += " %s %s ;\n"%(prop, requestedAmount)
prop = entity_str(prop_map['fundersProgram'])
inst = entity_str(fundersProgram)
text += " %s %s ;\n"%(prop, inst)
insts = format_lists(grp["forProgram"])
prop = entity_str(prop_map['forProgram'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["forStakeholder"])
prop = entity_str(prop_map['forStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
text += '.\n'
text += '\n'
# Logic Models
text += "#####################\n# Logic Models\n####################\n"
df = pd.read_excel(xls,'LogicModels', header=1)
df = df.dropna(how='all')
klass = entity_str(class_map["LogicModel"])
for (lminst, ninst),grp in df.groupby(['LogicModel','hasName']):
lminst = entity_str(lminst)
text += "%s rdf:type %s ;\n"%(lminst, klass)
insts = format_lists(grp["forOrganization"])
prop = entity_str(prop_map["forOrganization"])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
prop = entity_str(prop_map['hasName'])
text += " %s \"%s\";\n"%(prop, ninst)
inst = '; '.join(grp["hasDescription"].unique())
prop = entity_str(prop_map['hasDescription'])
text += " %s \"%s\";\n"%(prop, inst)
insts = format_lists(grp["hasProgram"])
prop = entity_str(prop_map["hasProgram"])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasStakeholder"])
prop = entity_str(prop_map['hasStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
text += ".\n"
# Characteristic
text += format_characteristics_text(lminst, format_lists(grp['hasCharacteristic'],entity=False))
text += "\n"
# Programs
text += "#####################\n# Programs\n####################\n"
df = pd.read_excel(xls,'Programs', header=1)
df = df.dropna(how='all')
klass = entity_str(class_map["Program"])
for (pinst,ninst),grp in df.groupby(['Program','hasName']):
#################################################
# generate Program Class and links for Service to Program to and Code
pinst = entity_str(pinst)
text += "%s rdf:type %s ;\n"%(pinst, klass)
prop = entity_str(prop_map['hasName'])
text += " %s \"%s\";\n"%(prop, ninst)
inst = '; '.join(grp["hasDescription"].values)
prop = entity_str(prop_map['hasDescription'])
text += " %s \"%s\";\n"%(prop, inst)
insts = format_lists(grp["hasService"])
prop = entity_str(prop_map['hasService'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasContributingStakeholder"])
prop = entity_str(prop_map['hasContributingStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasBeneficialStakeholder"])
prop = entity_str(prop_map['hasBeneficialStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
text += ".\n"
text +="\n"
text += "#####################\n# Services\n####################\n"
df = pd.read_excel(xls,'Services', header=1)
df = df.dropna(how='all')
klass = entity_str(class_map["Service"])
for (sinst,ninst),grp in df.groupby(['Service','hasName']):
if sinst == 'S12-3-Education':
break
#################################################
# generate Program Class and links for Service to Program to and Code
sinst = entity_str(sinst)
text += "%s rdf:type %s ;\n"%(sinst, klass)
prop = entity_str(prop_map['hasName'])
text += " %s \"%s\";\n"%(prop, ninst)
inst = '; '.join(grp["hasDescription"].unique())
prop = entity_str(prop_map['hasDescription'])
text += " %s \"%s\";\n"%(prop, inst)
insts = format_lists(grp["oep:partOf"])
prop = entity_str(prop_map['partOf'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasCode"])
prop = entity_str(prop_map['hasCode'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasContributingStakeholder"])
prop = entity_str(prop_map['hasContributingStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasBeneficialStakeholder"])
prop = entity_str(prop_map['hasBeneficialStakeholder'])
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
if len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
insts = format_lists(grp["hasMode"], entity=False)
insts = ["\"%s\""%(t) for t in insts]
prop = prop_map['hasMode']
if len(insts)==1:
text += " %s %s;\n"%(prop, insts[0])
elif len(insts)>1:
text += " %s %s;\n"%(prop,', '.join(insts))
text += ".\n"
# generate Service hasRequirement to Client Codes
for r in list(set(grp['hasRequirement'].values)):
text += format_characteristics_text(sinst, [r], prop0='hasRequirement')
# generate Service hasFocus to Client Codes
for r in list(set(grp['hasFocus'].values)):
text += format_characteristics_text(sinst, [r], prop0='hasFocus')
text += "\n"
f = open(dirout+'/'+fileout, "w")
f.write(text)
f.close()