Merge branch 'master' of https://github.com/PabloMartin2006/Curso2025-2026-DataScience

Author: PabloMartin2006

Assignment1/DatasetDescriptions.csv

@@ -1,4 +1,5 @@
 Your name; Your GitHub user; Dataset name; Dataset URL; Dataset brief description
+Alberto Barreiro Tasende; albertobarreiro1; Contaminación acústica. Estaciones de medida; https://datos.madrid.es/egob/catalogo/211346-0-estaciones-acusticas.dcat; Red fija de 31 estaciones de medición de ruido ambiental en Madrid, con su localización geográfica, altitud y fecha de alta. El sistema SIVCA monitoriza el ruido en la ciudad para evaluar el impacto acústico. 
 Daniel Arias Suárez	Mangurrineiro; Flora Urbana de Madrid; https://datos.madrid.es/egob/catalogo/300607-0-flora-mapas.dcat; Registros de especies vegetales distribuidas en los distritos de Madrid desde el año 1758 a 2020.	
 Kleart Laci Dreshaj; kleartlaci; Ruido ambiental en la ciudad de Madrid: niveles de ruido por estaciones; https://datos.madrid.es/egob/catalogo/210227-2-ruido-mensual.rdf; Dataset que recoge los niveles mensuales de ruido ambiental registrados en las diferentes estaciones de medición de la ciudad de Madrid. 
 Pablo Grano de oro Sevillano; pablogranodeoro; Mapa Estratégico del Ruido 2021 en Madrid.; https://servpub.madrid.es/IDEAM_WBGEOPORTAL/dcat?id=470b89af-5d64-41d3-8bdb-2fe6badd0364; Refleja los niveles de ruido provocados por el tráfico rodado en Madrid correspondientes a 2021. Los metadatos de este conjunto de datos están en formato RDF.
@@ -15,3 +16,4 @@ Rodrigo Nieto Rodríguez; Rodrix505; Puntos limpios fijos; https://datos.madrid.
 Yi Chen Chen; yichenchen2006; Principales parques y jardines municipales; https://datos.madrid.es/sites/v/index.jsp?vgnextoid=dc758935dde13410VgnVCM2000000c205a0aRCRD&vgnextchannel=374512b9ace9f310VgnVCM100000171f5a0aRCRD; Madrid ofrece un patrimonio verde de excepcional extensión y diversidad (más de 6.000 hectáreas, que suponen más de 18 metros cuadrados de parques y zonas verdes públicas por habitante de la ciudad).
 Carolina Simal;carol-2406;Arbolado en parques y zonas verdes de Madrid;https://datos.madrid.es/egob/catalogo/300264-81-Arbolado-parques-historico.csv;Número de arboles por parque de Madrid de cada especie. 
 Luca Alvarez; lucaam06; Bomberos. Parques de bomberos; https://datos.madrid.es/egob/catalogo/211642-0-bomberos-parques.rdf; En este conjunto de datos, puede encontrar la relación de los trece parques de bomberos existentes en la ciudad de Madrid.
+Carla Jiménez Arganda; carlajimenezarganda; Zonas verdes de Madrid: zonas estanciales y ajardinadas; https://datos.madrid.es/egob/catalogo/300226-0-zonas-verdes-estanciales.rdf; Localización, características y tipologías de las zonas verdes estanciales y ajardinadas de Madrid.

Assignment4/Alberto_Barreiro_24C008/task06.py

@@ -0,0 +1,165 @@
+#%% [markdown] 
+# **Task 06: Modifying RDF(s)**
+
+# %%
+
+
+# %%
+#%pip install rdflib
+import urllib.request
+url = 'https://raw.githubusercontent.com/FacultadInformatica-LinkedData/Curso2025-2026/refs/heads/master/Assignment4/course_materials/python/validation.py'
+urllib.request.urlretrieve(url, 'validation.py')
+github_storage = "https://raw.githubusercontent.com/FacultadInformatica-LinkedData/Curso2025-2026/master/Assignment4/course_materials"
+
+# %% [markdown]
+# Import RDFLib main methods
+
+# %%
+from rdflib import Graph, Namespace, Literal, XSD
+from rdflib.namespace import RDF, RDFS
+from validation import Report
+g = Graph()
+g.namespace_manager.bind('ns', Namespace("http://somewhere#"), override=False)
+r = Report()
+
+# %% [markdown]
+# Create a new class named Researcher
+
+# %%
+ns = Namespace("http://mydomain.org#")
+g.add((ns.Researcher, RDF.type, RDFS.Class))
+for s, p, o in g:
+  print(s,p,o)
+
+# %% [markdown]
+# **Task 6.0: Create new prefixes for "ontology" and "person" as shown in slide 14 of the Slidedeck 01a.RDF(s)-SPARQL shown in class.**
+
+# %%
+person = Namespace("http://oeg-upm.net/people#") 
+ontology = Namespace("http://oeg-upm.net/ontology#")
+
+g.bind('person', person)
+g.bind('ontology', ontology)
+
+# %% [markdown]
+# **TASK 6.1: Reproduce the taxonomy of classes shown in slide 34 in class (all the classes under "Vocabulario", Slidedeck: 01a.RDF(s)-SPARQL). Add labels for each of them as they are in the diagram (exactly) with no language tags. Remember adding the correct datatype (xsd:String) when appropriate**
+# 
+
+# %%
+people = Namespace("http://oeg.fi.upm.es/def/people#")
+g.bind("people", people)
+
+
+person = people.Person
+professor = people.Professor
+associate = people.AssociateProfessor
+interim = people.InterimAssociateProfessor
+full = people.FullProfessor
+
+g.add((person, RDF.type, RDFS.Class))
+g.add((person, RDFS.label, Literal("Person", datatype=XSD.string)))
+
+g.add((professor, RDF.type, RDFS.Class))
+g.add((professor, RDFS.label, Literal("Professor", datatype=XSD.string)))
+g.add((professor, RDFS.subClassOf, person))
+
+g.add((associate, RDF.type, RDFS.Class))
+g.add((associate, RDFS.label, Literal("AssociateProfessor", datatype=XSD.string)))
+g.add((associate, RDFS.subClassOf, professor))
+
+g.add((interim, RDF.type, RDFS.Class))
+g.add((interim, RDFS.label, Literal("InterimAssociateProfessor", datatype=XSD.string)))
+g.add((interim, RDFS.subClassOf, associate))
+
+g.add((full, RDF.type, RDFS.Class))
+g.add((full, RDFS.label, Literal("FullProfessor", datatype=XSD.string)))
+g.add((full, RDFS.subClassOf, professor))
+
+
+# Visualize the results
+for s, p, o in g:
+  print(s,p,o)
+
+# %%
+# Validation. Do not remove
+r.validate_task_06_01(g)
+
+# %% [markdown]
+# **TASK 6.2: Add the 3 properties shown in slide 36. Add labels for each of them (exactly as they are in the slide, with no language tags), and their corresponding domains and ranges using RDFS. Remember adding the correct datatype (xsd:String) when appropriate. If a property has no range, make it a literal (string)**
+
+# %%
+hasName = people.hasName
+hasColleague = people.hasColleague
+hasHomePage = people.hasHomePage
+
+g.add((hasName, RDF.type, RDF.Property))
+g.add((hasName, RDFS.label, Literal("hasName", datatype=XSD.string)))
+g.add((hasName, RDFS.domain, person))
+g.add((hasName, RDFS.range, RDFS.Literal))
+
+g.add((hasColleague, RDF.type, RDFS.subPropertyOf))
+g.add((hasColleague, RDFS.label, Literal("hasColleague", datatype=XSD.string)))
+g.add((hasColleague, RDFS.domain, person))
+g.add((hasColleague, RDFS.range, person))
+
+g.add((hasHomePage, RDF.type, RDFS.subPropertyOf))
+g.add((hasHomePage, RDFS.label, Literal("hasHomePage", datatype=XSD.string)))
+g.add((hasHomePage, RDFS.domain, full))
+g.add((hasHomePage, RDFS.range, RDFS.Literal))
+
+for s, p, o in g:
+  print(s,p,o)
+
+# %%
+# Validation. Do not remove
+r.validate_task_06_02(g)
+
+# %% [markdown]
+# **TASK 6.3: Create the individuals shown in slide 36 under "Datos". Link them with the same relationships shown in the diagram."**
+
+# %%
+indiv = Namespace("http://oeg.fi.upm.es/resource/person/")
+
+oscar = indiv.Oscar
+asun = indiv.Asun
+raul = indiv.Raul
+g.add((oscar, RDF.type, full))
+g.add((oscar, RDFS.label, Literal("Oscar", datatype=XSD.string)))
+g.add((oscar, hasColleague, indiv.Asun))
+g.add((oscar, hasName, Literal("Oscar García", datatype=XSD.string)))
+
+g.add((asun, RDF.type, full))
+g.add((asun, RDFS.label, Literal("Asun", datatype=XSD.string)))
+g.add((asun, hasColleague, oscar))
+g.add((asun, hasHomePage, Literal("https://www.oeg-upm.net/", datatype=XSD.string)))
+
+g.add((raul, RDFS.label, Literal("Raul", datatype=XSD.string)))
+g.add((raul, RDF.type, interim))
+
+# Visualize the results
+for s, p, o in g:
+  print(s,p,o)
+
+# %%
+r.validate_task_06_03(g)
+
+# %% [markdown]
+# **TASK 6.4: Add to the individual person:Oscar the email address, given and family names. Use the properties already included in example 4 to describe Jane and John (https://raw.githubusercontent.com/FacultadInformatica-LinkedData/Curso2025-2026/master/Assignment4/course_materials/rdf/example4.rdf). Do not import the namespaces, add them manually**
+# 
+
+# %%
+vcard = Namespace("http://www.w3.org/2001/vcard-rdf/3.0/")
+foaf = Namespace("http://xmlns.com/foaf/0.1/")
+
+g.add((oscar, vcard.Given, Literal("Oscar", datatype=XSD.string)))
+g.add((oscar, vcard.Family, Literal("García", datatype=XSD.string)))
+g.add((oscar, foaf.email, Literal("ocorcho@fi.upm.es", datatype=XSD.string)))
+for s, p, o in g:
+  print(s,p,o)
+
+# %%
+# Validation. Do not remove
+r.validate_task_06_04(g)
+r.save_report("_Task_06")
+
+

Assignment4/Alberto_Barreiro_24C008/task07.py

@@ -0,0 +1,170 @@
+# %% [markdown]
+# **Task 07: Querying RDF(s)**
+
+# %%
+#!pip install rdflib
+import urllib.request
+url = 'https://raw.githubusercontent.com/FacultadInformatica-LinkedData/Curso2025-2026/refs/heads/master/Assignment4/course_materials/python/validation.py'
+urllib.request.urlretrieve(url, 'validation.py')
+github_storage = "https://raw.githubusercontent.com/FacultadInformatica-LinkedData/Curso2025-2026/master/Assignment4/course_materials"
+
+# %%
+from validation import Report
+
+# %% [markdown]
+# First let's read the RDF file
+
+# %%
+from rdflib import Graph, Namespace, Literal
+from rdflib.namespace import RDF, RDFS
+# Do not change the name of the variables
+g = Graph()
+g.namespace_manager.bind('ns', Namespace("http://somewhere#"), override=False)
+g.parse(github_storage+"/rdf/data06.ttl", format="TTL")
+report = Report()
+
+# %% [markdown]
+# **TASK 7.1a: For all classes, list each classURI. If the class belogs to another class, then list its superclass.**
+# **Do the exercise in RDFLib returning a list of Tuples: (class, superclass) called "result". If a class does not have a super class, then return None as the superclass**
+
+# %%
+result = []
+for cls in g.subjects(RDF.type, RDFS.Class):
+    superclasses = list(g.objects(cls, RDFS.subClassOf))
+    if superclasses:
+        for sup in superclasses:
+            result.append((str(cls), str(sup)))
+    else:
+        result.append((str(cls), None))
+for r in result:
+  print(r)
+
+# %%
+## Validation: Do not remove
+report.validate_07_1a(result)
+
+# %% [markdown]
+# **TASK 7.1b: Repeat the same exercise in SPARQL, returning the variables ?c (class) and ?sc (superclass)**
+
+# %%
+query = """
+SELECT ?c ?sc
+WHERE {
+  ?c rdf:type rdfs:Class .
+  OPTIONAL { ?c rdfs:subClassOf ?sc . }
+}
+"""
+
+for r in g.query(query):
+  print(r.c, r.sc)
+
+
+# %%
+## Validation: Do not remove
+report.validate_07_1b(query,g)
+
+# %% [markdown]
+# **TASK 7.2a: List all individuals of "Person" with RDFLib (remember the subClasses). Return the individual URIs in a list called "individuals"**
+# 
+
+# %%
+people = Namespace("http://oeg.fi.upm.es/def/people#")
+
+def is_subclass_of_person(c):
+    if c == people.Person:
+        return True
+    for _, _, sup in g.triples((c, RDFS.subClassOf, None)):
+        if is_subclass_of_person(sup):
+            return True
+    return False
+
+individuals = []
+vistos = set()
+
+for s, p, o in g.triples((None, RDF.type, None)):
+    if o == people.Person or is_subclass_of_person(o):
+        if s not in vistos:
+            vistos.add(s)
+            individuals.append(s)
+
+for i in individuals:
+    print(i)
+
+# %%
+# validation. Do not remove
+report.validate_07_02a(individuals)
+
+# %% [markdown]
+# **TASK 7.2b: Repeat the same exercise in SPARQL, returning the individual URIs in a variable ?ind**
+
+# %%
+
+query = """
+PREFIX people: <http://oeg.fi.upm.es/def/people#>
+SELECT DISTINCT ?ind
+WHERE {
+  ?ind rdf:type ?c .
+  ?c rdfs:subClassOf* people:Person .
+}
+"""
+for r in g.query(query):
+  print(r.ind)
+# Visualize the results
+
+# %%
+## Validation: Do not remove
+report.validate_07_02b(g, query)
+
+# %% [markdown]
+# **TASK 7.3:  List the name and type of those who know Rocky (in SPARQL only). Use name and type as variables in the query**
+
+# %%
+
+query =  """
+PREFIX people: <http://oeg.fi.upm.es/def/people#>
+SELECT ?name ?type
+where{
+?x people:knows people:Rocky .
+?x rdfs:label ?name .
+?x a ?type .
+}
+"""
+# Visualize the results
+for r in g.query(query):
+  print(r.name, r.type)
+
+# %%
+## Validation: Do not remove
+report.validate_07_03(g, query)
+
+# %% [markdown]
+# **Task 7.4: List the name of those entities who have a colleague with a dog, or that have a collegue who has a colleague who has a dog (in SPARQL). Return the results in a variable called name**
+
+# %%
+query =  """
+PREFIX people: <http://oeg.fi.upm.es/def/people#>
+SELECT DISTINCT ?name WHERE {
+    ?x rdfs:label ?name .
+    {
+        ?x people:hasColleague ?colleague .
+        ?z people:ownsPet ?pet .
+    } UNION {
+        ?x people:hasColleague ?colleague1 .
+        ?y people:hasColleague ?colleague2 .
+        ?z people:ownsPet ?pet .
+    }
+}
+"""
+
+for r in g.query(query):
+  print(r.name)
+
+# TO DO
+# Visualize the results
+
+# %%
+## Validation: Do not remove
+report.validate_07_04(g,query)
+report.save_report("_Task_07")
+
+