Notebook

Practical introduction to RDF and SPARQL¶

Reminder: IRIs and Literals¶

Literals refer two simple values (numerical values, strings, boolean, dates, etc.)

Resource refers to complex objects identified by an IRI (International Resource Identifier == URI allowing international characters). Note that URLs are IRIs pointing to web accessible documents/data. URIs can be shortened with PREFIX. As an example <http://my/super/vocab/my_term> can be shortened as ns:my_term if ns is defined as a prefix for http://my/super/vocab/.

Reminder: RDF, triples¶

an RDF statement represents a relationship between two resources: a subject and an object
relationships are directional and are called a predicates (or RDF properties)
(logical) statements are called triple : {subject, predicate, object}
a set of triples form a directed labelled graph : subject nodes are IRIs, edges are predicate (IRIs only), object nodes are IRIs or Literals.

Go through https://www.w3.org/TR/rdf11-primer/ to have more details on RDF.

Reminder: Turtle syntax¶

header to define prefix
- example: with @prefix ns: http://my_voc# ., http://my_voc#term can be written as ns:term
generally one line per triple with a . at the end: <subject> <predicate> <object> .
possible shortcuts to share the same subject: ;

s p1 o1 ; 
    p2 o2 .

possible shortcuts to share the same subject-predicate: ,

s p o1, o2, o3 .

Example¶

turtle syntax:

<http://HG37> rdf:type <http://human_genome> .
<http://sample1> <http://is_aligned_with> <http://HG37> .
<http://sample1> rdfs:comment "Sample 1 from Study X [...]"^^xsd:string .

<http://HG37> rdf:type <http://human_genome> .
<http://sample1> <http://is_aligned_with> <http://HG37> ;
              rdfs:comment "Sample 1 from Study X [...]"^^xsd:string .

Question 1¶

Consider the following RDF properties family:has_mother, family:has_father, family:has_sister
Only using these predicates, represent with RDF triples the following family:
- The mother of John is Mary,
- Mickael is the son of Mark,
- John and Mickael are cousins (because Mark and Mary are siblings).
Go to https://www.ldf.fi/service/rdf-grapher
Generate a graphical representation of the RDF graph.

Answer¶

@prefix family: <http://family.org/> .

<http://John> family:has_mother <http://Mary> .
<http://Mickael> family:has_father <http://Mark> .
<http://Mark> family:has_sister <http://Mary> .

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SPARQL hands-on¶

SPARQL is the standards language to query multiple data sources expressed in RDF. The principle consists in defining a graph pattern to be matched against an RDF graph.

Definition¶

Triple Patterns (TPs) are like RDF triples except that each of the subject, predicate and object may be a variable. Variables are prefixed with a ? .

Example¶

Triple pattern

?x <is_a_variant_of> <RAC1> .

RDF graph

<SNP:123> <is_a_variant_of> <NEMO> .
<SNP:rs527330002> <is_a_variant_of> <RAC1> .
<SNP:rs527330002> <refers_to_organism> <http://www.uniprot.org/taxonomy/9606> .
<SNP:rs61753123> <is_a_variant_of> <RAC1> .

Bindings of variables ?x

?x = <SNP:rs527330002>
?x = <SNP:rs61753123>

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Definition¶

Basic Graph Patterns (BGPs) consist in a set of triple patterns to be matched against an RDF graph.

Example¶

Basic graph pattern

?x <is_a_variant_of> <RAC1> .
?x <is_a_risk_factor_for> ?z

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4 Types of SPARQL queries¶

SELECT : returns the variables values (i.e. bound variables) for each graph pattern match ;
CONSTRUCT : returns an RDF graph constructed by substituting variables in a set of triple patterns ;
ASK : returns a boolean (true/false) indicating whether a query pattern matches or not ;
DESCRIBE : returns an RDF graph that describes the resources found (resources neighborhood).

Additional features: Optional BGPs, union, filters, aggregate functions, negation, service, *etc.*

Anatomy of a SPARQL query¶

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Question 2¶

We will now use the RDFlib package to parse RDF Data and do some very basic SPARQL queries.

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from rdflib import Graph

# RDF graph, in turtle syntax, stored in a string
my_rdf_data = """
@prefix ns: <http://my_voc/> .
@prefix snp: <http://my_snps/> .

snp:123 ns:is_a_variant_of "NEMO" .
snp:rs527330002 ns:is_a_variant_of "RAC1" .
snp:rs527330002 ns:refers_to_organism <http://www.uniprot.org/taxonomy/9606> .
snp:rs61753123 ns:is_a_variant_of "RAC1" .
"""

# Initialization of the in-memory RDF graph, RDFlib Graph object
kg = Graph()

# Parsing of the RDF data
kg.parse(data=my_rdf_data, format='turtle')

# Printing the size of the graph and serializing it again. 
print(f'the knowledge graph contains {len(kg)} triples\n')
print(kg.serialize(format="turtle"))

We now execute a simple query to search for all "variants" of RAC1.

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q = """

"""

res = kg.query(q)
for row in res:
    print(f"{row['x']} is a variant of RAC1")

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# SOLUTION:
!echo "ClNFTEVDVCA/eCBXSEVSRSB7CiAgICA/eCBuczppc19hX3ZhcmlhbnRfb2YgUkFDMSAuCn0K" | base64 --decode

Question 3¶

Generalize this query to show all is a variant of relations. You can use two variables ?x and ?y.

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q = """

"""

res = kg.query(q)
for row in res:
    print(f"{row['x']} is a variant of {row['y']}")

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# SOLUTION:
!echo "ClNFTEVDVCA/eCA/eSBXSEVSRSB7CiAgICA/eCBuczppc19hX3ZhcmlhbnRfb2YgP3kgLgp9Cg==" | base64 --decode

Question 4¶

Search for the name of the gene who has a variant refering to the http://www.uniprot.org/taxonomy/9606 organism

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q = """

"""

res = kg.query(q)
for row in res:
    print(row['y'])

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# SOLUTION:
!echo "ClNFTEVDVCA/eSBXSEVSRSB7CiAgICA/eCBuczpyZWZlcnNfdG9fb3JnYW5pc20gPGh0dHA6Ly93d3cudW5pcHJvdC5vcmcvdGF4b25vbXkvOTYwNj4gLgogICAgP3ggbnM6aXNfYV92YXJpYW50X29mID95IC4KfQo=" | base64 --decode

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