1. SPARQL + RDF Based on: Prof. Benny Kimelfled’s lecture notes
And Lee Feigenbaum’s “SPARQL By Example” Tutorial
“The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”
• Vision: Web data will entail semantics in a manner that is understood (and processed, and linked) automatically by computers
• The “Semantic Web” is the technical infrastructure – Unambiguous names for resources that may also bind data to real world objects (URI) – A common data model to describe/link resources (RDF) – Expressive language to access to data (SPARQL) – Languages for defining common vocabularies and rules for automated reasoning (e.g., politician is person) (RDFS, OWL)
• Data providers should collaborate: properly publish their data and link it to existing data

2. The Semantic Web
Vision: Web data will entail semantics in a manner that is understood (and processed, and linked) automatically by computers
Data providers should collaborate: properly publish their data and link it to existing data

3. Some Freely Available RDF Repositories
DBPedia (~1.2b triples)
“a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web”
Freebase (~340m triples)
“A community-curated DB of well-known people, places, and things”
DBLP (~58m triples)
Computer science bibliography
WordNet (~3m triples)
English lexical db: synonyms, antonyms, POS, ...
GeoNames (~94m triples)
“Covers all countries, contains over eight million placenames”
Yago (~120m triples)
Information from Wikipedia, Wordnet, Geonames

5. RDF Graph - recap An RDF graph is a finite set of triplets
Given two sets:
𝑈 is a set of URIs (unique resource identifier)
𝐿 is a set of literals (strings, integers, etc..)
A triplet is in the form (𝑈×𝑈× 𝑈∪𝐿 )
subject
object
predicate U L

6. RDF Example from DBPedia
13253
1949

7. Structure of a SPARQL Query
A SPARQL query comprises, in order:
Prefix declarations, for abbreviating URIs
Dataset definition, stating what RDF graph(s) are being queried
A result clause, identifying what information to return from the query
The query pattern, specifying what to query for in the underlying dataset
Query modifiers, slicing, ordering, and otherwise rearranging query results

8. Structure of a SPARQL Query
# prefix declarations PREFIX foo: < ... # dataset definition FROM ... # result clause SELECT ... # query pattern WHERE { ... } # query modifiers ORDER BY ...

9. Endpoints

10. Theory In Practice
Yeah, OK, I think I got how the model works…but what about the ACTUAL QUERY?!?!
PREFIX rdf: <
PREFIX rdfs: <
PREFIX dbp: <
PREFIX dbr: <
PREFIX dbo: <
SELECT DISTINCT ?player ?team {
?player dbp:team <
?player dbp:team ?team.
?team rdf:type ?type
FILTER(
?team = < ||
?type = < ) }
SELECT DISTINCT ?player ?height {
?player dbo:height ?height

11. Maccabi Tel Aviv & NBA Players

12. Basics

13. Projection
SELECT ?x1,...,?xk WHERE {P1} =
π{x1,...,xk}(P1(G))

14. Maccabi Tel Aviv players
PREFIX rdf: < PREFIX rdfs: < PREFIX dbp: < PREFIX dbr: < PREFIX dbo: < SELECT DISTINCT ?player { ?player dbp:team < }
Project out of 𝜇={𝑝𝑙𝑎𝑦𝑒𝑟}
URI
URI
URI / Literal

15. Join
P1 . P2 = P1(G) ⨝ P2(G)

16. Maccabi’s players and their height
Given Retrieve the player’s URI and height
Player URI
Predicate
Maccabi’s URI
Player 1 URI
dbp:team
< …
Player n URI
Player URI
Predicate
Height
Player 1 URI
dbo:height 2 …
1.98
Player n URI
2.10

17. Maccabi’s players and their height
PREFIX rdf: < PREFIX rdfs: < PREFIX dbp: < PREFIX dbr: < PREFIX dbo: < SELECT DISTINCT ?player ?height { ?player dbp:team < ?player dbo:height ?height }
Project out of 𝜇={𝑝𝑙𝑎𝑦𝑒𝑟, ℎ𝑒𝑖𝑔ℎ𝑡}
Join
Create both triplets

18. P1 OPTIONAL {P2} = P1(G) ⟕ P2(G)
Left Outer Join
P1 OPTIONAL {P2} = P1(G) ⟕ P2(G)

19. Maccabi’s players height and nationality
PREFIX rdf: < PREFIX rdfs: < PREFIX dbp: < PREFIX dbr: < PREFIX dbo: < SELECT DISTINCT ?player ?height ?nationality { ?player dbp:team < ?player dbo:height ?height OPTIONAL ?player dbp:nationality ?nationality }
Project out of 𝜇={𝑝𝑙𝑎𝑦𝑒𝑟, ℎ𝑒𝑖𝑔ℎ𝑡, 𝑛𝑎𝑡𝑖𝑜𝑛𝑎𝑙𝑖𝑡𝑦}

20. Selection
{P1 FILTER ( F )} = σFP1(G)

21. Maccabi’s players and their teams
For each Maccabi’s player, return the player and the team he played in 𝑇𝑒𝑎𝑚 ∈{𝑀𝑎𝑐𝑐𝑎𝑏𝑖, 𝑁𝐵𝐴 𝑡𝑒𝑎𝑚𝑠}

22. Maccabi’s players and their teams
PREFIX rdf: < PREFIX rdfs: < PREFIX dbp: < PREFIX dbr: < PREFIX dbo: < SELECT DISTINCT ?player ?team { ?player dbp:team < ?player dbp:team ?team. ?team rdf:type ?type FILTER( ?team = < || ?type = < ) }
Project out of 𝜇={𝑝𝑙𝑎𝑦𝑒𝑟, 𝑡𝑒𝑎𝑚, 𝑡𝑦𝑝𝑒}
Two joins
Filter

23. {P1} MINUS {P2} = P1(G) - P2(G)
Subtraction
{P1} MINUS {P2} = P1(G) - P2(G)

24. Remove all players with height > 2
SELECT DISTINCT ?player ?team { ?player dbp:team < ?player dbp:team ?team. ?team rdf:type ?type FILTER( ?team = < || ?type = ) MINUS ?player dbo:height ?height FILTER ( ?height > 2) }
𝜇 1 ={𝑝𝑙𝑎𝑦𝑒𝑟, 𝑡𝑒𝑎𝑚, 𝑡𝑦𝑝𝑒}
𝜇 2 ={𝑝𝑙𝑎𝑦𝑒𝑟, ℎ𝑒𝑖𝑔ℎ𝑡}
PREFIX rdf: <
PREFIX rdfs: <
PREFIX dbp: <
PREFIX dbr: <
PREFIX dbo: <
PREFIX db: <
SELECT DISTINCT ?player ?team {
?player dbp:team <
?player dbp:team ?team.
?team rdf:type ?type
FILTER(
?team = < ||
?type = < )
MINUS
?player dbo:height ?height
FILTER
( ?height > 2) }

25. Remove all players with height > 2, and team in NBA
SELECT DISTINCT ?player ?team { …..same as before MINUS ?team rdf:type ?type FILTER( ?type = < ) }
𝜇 3 ={𝑡𝑒𝑎𝑚, 𝑡𝑦𝑝𝑒}
PREFIX rdf: <
PREFIX rdfs: <
PREFIX dbp: <
PREFIX dbr: <
PREFIX dbo: <
PREFIX db: <
SELECT DISTINCT ?player ?team {
?player dbp:team <
?player dbp:team ?team.
?team rdf:type ?type
FILTER(
?team = < ||
?type = < )
MINUS
?player dbo:height ?height
FILTER
( ?height > 2) }

26. Remove….wait… What!?
SELECT DISTINCT ?player ?team { Same as before…. MINUS < rdf:type ?a }
𝜇 3 ={𝑎}
PREFIX rdf: <
PREFIX rdfs: <
PREFIX dbp: <
PREFIX dbr: <
PREFIX dbo: <
PREFIX db: <
SELECT DISTINCT ?player ?team {
?player dbp:team <
?player dbp:team ?team.
?team rdf:type ?type
FILTER(
?team = < ||
?type = < )
MINUS
< rdf:type ?a }

27. External Graphs – fetch Hebrew names from Wikidata
SELECT DISTINCT ?player ?e ?h ?wikidatateam { ?player dbp:team < ?player dbp:team ?team. ?player rdfs:label ?e. ?player owl:sameAs ?wikidatateam FILTER( ?team = < || ?type = < ). GRAPH < ?wikidatateam rdfs:label ?h } FILTER(LANG(?h) = "he" && LANG(?e) = "en")
PREFIX rdf: <
PREFIX rdfs: <
PREFIX dbp: <
PREFIX dbr: <
PREFIX dbo: <
PREFIX owl: <
SELECT DISTINCT ?player ?e ?h ?wikidatateam {
?player dbp:team <
?player dbp:team ?team.
?team rdf:type ?type.
?player rdfs:label ?e.
?player owl:sameAs ?wikidatateam
FILTER(
?team = < ||
?type = < ).
GRAPH <
?wikidatateam rdfs:label ?h }
FILTER(LANG(?h) = "he" && LANG(?e) = "en")

28. dbr:Abraham_Lincoln
dbo:party
dbr:Republican_Party
dbr:Whig_Party
dbo:profession
dbr:Lawyer
rdf:type
yago:PresidentsOfTheUnitedStates
dbr:Franklin_D._Roosevelt
dbr:Democratic_Party
dbr:Richard_Nixon
dbr:Bill_Clinton
Ex. 1
SELECT ?president {
?president rdf:type yago:PresidentsOfTheUnitedStates.
?president dbo:profession dbr:Lawyer. }
Lincoln
Roosevelt
Nixon
Clinton ?

29. dbr:Abraham_Lincoln
dbo:party
dbr:Republican_Party
dbr:Whig_Party
dbo:profession
dbr:Lawyer
rdf:type
yago:PresidentsOfTheUnitedStates
dbr:Franklin_D._Roosevelt
dbr:Democratic_Party
dbr:Richard_Nixon
dbr:Bill_Clinton
Ex. 2
SELECT ?president {
?president rdf:type yago:PresidentsOfTheUnitedStates.
?president dbo:profession dbr:Lawyer.
OPTIONAL { ?president dbo:party ?party } }
Lincoln
Roosevelt
Nixon
Clinton ?

30. dbr:Abraham_Lincoln
dbo:party
dbr:Republican_Party
dbr:Whig_Party
dbo:profession
dbr:Lawyer
rdf:type
yago:PresidentsOfTheUnitedStates
dbr:Franklin_D._Roosevelt
dbr:Democratic_Party
dbr:Richard_Nixon
dbr:Bill_Clinton
Ex. 3
SELECT ?president { {
?president rdf:type yago:PresidentsOfTheUnitedStates.
?president dbo:profession dbr:Lawyer.
OPTIONAL { ?president dbo:party ?party } }
MINUS {dbr:Richard_Nixon dbo:party ?party}
Lincoln
Roosevelt
Nixon
Clinton ?