SPARQL. Part III. Jan Pettersen Nytun, UiA

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1 ARQL Part III Jan Pettersen Nytun, UiA 1

2 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 2

3 Example: Explore salaries of the employees of a company Jan Pettersen Nytun, UIA, page 3

4 4

5 Jan Pettersen Nytun, UIA, page 5

6 Jan Pettersen Nytun, UIA, page 6 P List alaries, i.e., list employee, year and amount tep 1: What to list PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < PREFIX : < ELECT?employee?year?amount WHERE { }

7 Jan Pettersen Nytun, UIA, page 7 P tep 2: Get all resources with salary ELECT?employee?year?amount WHERE {?employee :hasalary :salary }?salary :hasalary?employee

8 Jan Pettersen Nytun, UIA, page 8 P :hasalary?salary?employee Totally 6 matches: :bob :hasalary :bobalaray2013. :bob :hasalary :bobalaray2014.

9 What if some other types of resources have salaries? ELECT?employee?year?amount WHERE {?employee :hasalary?salary.?employee rdf:type :Employee }?salary Employee :hasalary rdf:type?employee Jan Pettersen Nytun, UIA, page 9

10 Jan Pettersen Nytun, UIA, page 10 P?salary :hasalary rdf:type Employee?employee Again there are 6 matches. howing one of them: (composed of 2 triples): :bob :hasalary :bobalaray2014. :bob rdf:type :Employee. Totally 6 matches, but showing only one match:

tep 3: Get year and amount also [4] PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX owl: <http://www.w3.org/2002/07/owl#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX xsd: <http://www.

11 tep 3: Get year and amount also [4] PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < PREFIX : < ELECT?employee?year?amount WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} Jan Pettersen Nytun, UIA, page 11

List alaries rdered By Year [4] P PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX owl: <http://www.w3.org/2002/07/owl#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX xsd: <http://www.

12 List alaries rdered By Year [4] P PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < PREFIX : < ELECT?employee?year?amount WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} RDER BY?year Jan Pettersen Nytun, UIA, page 12

13 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 13

14 P Total um f All alaries [4] PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < PREFIX : < ELECT (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} Jan Pettersen Nytun, UIA, page 14

15 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 15

16 How to get: alaries Per Year Jan Pettersen Nytun, UIA, page 16

17 [3] By default a solution set consists of a single group, containing all solutions. WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} Assume this gives the following 4 matches: :e1 :hasalary :s1. :s1 :hasyear :s1 :hasamount 100. :e2 :hasalary :s2. :s2 :hasyear :s2 :hasamount 200. :e3 :hasalary :s3. :s3 :hasyear :s3 :hasamount :e4 :hasalary :s4. :s4 :hasyear :s4 :hasamount 400. Jan Pettersen Nytun, UIA, page 17

18 Grouping may be specified using GRUP BY. ELECT WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} GRUP BY?year Jan Pettersen Nytun, UIA, page 18

19 :e1 :hasalary :s1. :s1 :hasyear :s1 :hasamount 100. :e2 :hasalary :s2. :s2 :hasyear :s2 :hasamount 200. :e3 :hasalary :s3. :s3 :hasyear :s3 :hasamount :e4 :hasalary :s4. :s4 :hasyear :s4 :hasamount 400. WHERE { } GRUP BY?year Gives 2 groups: :e1 :hasalary :s1. :s1 :hasyear :s1 :hasamount 100. :e4 :hasalary :s4. :s4 :hasyear :s4 :hasamount 400. :e2 :hasalary :s2. :s2 :hasyear :s2 :hasamount 200. :e3 :hasalary :s3. :s3 :hasyear :s3 :hasamount page 19

20 Aggregates Aggregates apply expressions over groups of solutions. Aggregates defined in version 1.1 of PARQL are CUNT, UM, MIN, MAX, AVG,... ELECT?year (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount} GRUP BY?year Jan Pettersen Nytun, UIA, page 20

21 :e1 :hasalary :s1. :s1 :hasyear :s1 :hasamount 100. :e4 :hasalary :s4. :s4 :hasyear :s4 :hasamount 400. :e2 :hasalary :s2. :s2 :hasyear :s2 :hasamount 200. :e3 :hasalary :s3. :s3 :hasyear :s3 :hasamount ELECT?year (UM (?amount) A?total). Gives 2 results: year total page 21

22 P alaries Per Year [4] PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < PREFIX : < ELECT?year (UM (?amount) A?total) WHERE {?employee :hasalary?salary. GRUP BY?year?salary :hasyear?year.?salary :hasamount?amount} page 22

23 Adding several salaries per year for some employees : Jan Pettersen Nytun, UIA, page 23

24 ntology : owl: rdf: xml: xsd: rdfs: < < rdf:type owl:ntology. :hasalary rdf:type owl:bjectproperty ; rdfs:domain :Employee ; rdfs:range :alary. :hasamount rdf:type owl:datatypeproperty ; rdfs:range xsd:int. :hasname rdf:type owl:datatypeproperty. :hasyear rdf:type owl:datatypeproperty ; rdfs:range xsd:int. 24

25 How to see the salaries summed up for each employees by year [4] ELECT?year?employee (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount } GRUP BY?year?employee Jan Pettersen Nytun, UIA, page 25

26 P [4] ELECT?year?employee (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount } GRUP BY?year?employee RDER BY?year?employee

27 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 27

nly showing yearly salaries higher than 250000 [4] ELECT?year?employee (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?

28 nly showing yearly salaries higher than [4] ELECT?year?employee (UM (?amount) A?total) WHERE {?employee :hasalary?salary.?salary :hasyear?year.?salary :hasamount?amount } GRUP BY?year?employee HAVING (?total > ) RDER BY?year?employee ld query result: Jan Pettersen Nytun, UIA, page 28

29 [4]: HAVING and FILTER are very similar... FILTER refers to variables bound within a particular graph pattern always appears in the pattern (between { and } ), while HAVING refers to variables defined by aggregations in the ELECT clause, and hence always appears outside a graph pattern. Jan Pettersen Nytun, UIA, page 29

30 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 30

31 Assignment [4]: An assignment lets the query write specifically the value of a variable through some computation assigning a value to that variable, rather than matching some value in the data. Jan Pettersen Nytun, UIA, page 31

32 : :Bart :hasparent :Homer. :Bart :hasparent :Marge. :Lisa :hasparent :Homer. :Lisa :hasparent :Marge. :Maggie :hasparent :Homer. :Maggie :hasparent :Marge. :Ling :hasparent :elma. ### :Herb :hasparent :Abraham. :Herb :hasparent :Mona. :Homer :hasparent :Abraham. :Homer :hasparent :Mona. :Marge :hasparent :Clancy. :Marge :hasparent :Jackie. :Patty :hasparent :Clancy. :Patty :hasparent :Jackie. :elma :hasparent :Clancy. :elma :hasparent :Jackie. ### :Abraham :gender :male. :Mona :gender :female. :Clancy :gender :male. :Jackie :gender :female. :Herb :gender :male. :Homer :gender :male. :Marge :gender :female. :Patty :gender :female. :elma :gender :female. :Bart :gender :male. :Lisa :gender :female. :Maggie :gender :female. :Ling :gender :female.

33 How to also list grandchild which in our example is always :Maggie 2 Etc. Jan Pettersen Nytun, UIA, page 33

34 PREFIX : < PREFIX foaf: < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < ELECT?grandmother WHERE { :Maggie :hasparent?parent.?parent :hasmother?grandmother } RDER BY?grandmother 2 Etc. Jan Pettersen Nytun, UIA, page 34

35 P PREFIX : < PREFIX foaf: < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < ELECT?grandchildName?grandmother WHERE { :Maggie foaf:name?grandchildname. :Maggie :hasparent?parent.?parent :hasmother?grandmother } RDER BY?grandmother 2 Etc. Jan Pettersen Nytun, UIA, page 35

36 P PREFIX : < PREFIX foaf: < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < ELECT?grandchildName?grandmother WHERE { :Maggie :hasparent?parent.?parent :hasmother?grandmother BIND ("some name" as?grandchildname) } RDER BY?grandmother 2 Etc. Jan Pettersen Nytun, UIA, page 36

37 [3]: Jan Pettersen Nytun, UIA, page 37

38 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 38

39 [4]: concat ELECT (concat (?first, " ",?last) A?fullname) WHERE { :Workingntologist dc:creator?author.?author :firstname?first.?author :lastname?last. } [3]: page 39

40 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 40

41 page 41

42 Who is who's grandfather??grandchild :hasparent?parent.?parent :hasparent?grandfather.

43 REFIX xsd: < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX : < ELECT?grandchild?grandfather WHERE {?grandchild :hasparent?parent.?parent :hasparent?grandfather.?grandfather :gender :male }

44 PARQL RULE UING PARQL A A RULE LANGUAGE [4] PARQL CNTRUCT allows us to specify templates of new information based on patterns found in old information sometimes called a Rule Whenever you see this, conclude that. Example.: If John s father is Joe, then Joe s son is John Jan Pettersen Nytun, UIA, page 44

45 CNTRUCT The result of a query may be an RDF graph. [3]: The CNTRUCT query form returns a single RDF graph specified by a graph template. Jan Pettersen Nytun, UIA, page 45

46 CNTRUCT QUERY Returns a single RDF graph specified by a graph template 46

47 UING REULT F CNTRUCT QUERIE [4] ophisticated RDF query systems provide workbenches a variety of options for what to do with constructed triples: Insert the constructed triples back into the original data source tore the constructed triples as a separate graph tore the constructed triples into a new dataset (in another database) erialize the results and save them to a file. Jan Pettersen Nytun, UIA, page 47

48 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 48

49 The CNTRUCT tatement returns a separate graph. Use INERT if you want to have the triples stored in the ontology.

50 REFIX xsd: < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX : < INERT {?grandchild :hasgrandfather?grandfather } WHERE {?grandchild :hasparent?parent.?parent :hasparent?grandfather.?grandfather :gender :male } Adds to ontology: < < < Etc.

51 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 51

52 DELETE tatement 52

53 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 53

54 Rule Example: The Nephew/Niece-Uncle Relation Construct all nephew-uncle triples given the following triples: :Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund. :igmund rdf:type :Man ; :hasister :Ester. :igrund rdf:type :Woman ; :hasparent :igmund. The following triples should be produced: :Jan :hasuncle :lav. :Kirsten :hasuncle :lav. (The niece/nephew-ant relations are ignored.) Jan Pettersen Nytun, UIA, page 54

55 :Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund. :igmund rdf:type :Man ; :hasister :Ester. :igrund rdf:type :Woman ; :hasparent :igmund. PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < CNTRUCT {?n :hasuncle?uncle} WHERE {?n :hasparent?parent.?parent :hasbrother?uncle } The result of this CNTRUCT statement is empty why? Jan Pettersen Nytun, UIA, page 55

56 :Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund. :igmund rdf:type :Man ; :hasister :Ester. :igrund rdf:type :Woman ; :hasparent :igmund. PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < CNTRUCT {?n :hasuncle?uncle} WHERE {?n :hasparent?parent.?parent :hasbrother?uncle } Change order of?parent and?uncle in last triple of the WHERE-clause and there will be match on :lav :hasbrother :igmund. However, one could add triple :igmund :hasbrother :lav. to the RDF data. Jan Pettersen Nytun, UIA, page 56

57 :Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund. :igmund rdf:type :Man ; :hasister :Ester. :igrund rdf:type :Woman ; :hasparent :igmund. PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < CNTRUCT {?n :hasuncle?uncle} WHERE {?n :hasparent?parent.?uncle :hasbrother?parent.?uncle rdf:type :Man. } Jan Pettersen Nytun, UIA, page 57

58 UNIN A graph pattern is made up of several triples all of which have to match in order for the pattern to match there is an implicit and operation between the triples if we want one or another triple to match we may use UNIN (if both match then there will be two different matches). Jan Pettersen Nytun, UIA, page 58

59 Use UNIN to fix the following: PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < CNTRUCT {?n :hasuncle?uncle} WHERE {?n :hasparent?parent.?parent :hasbrother?uncle } We need an or (i.e., UNIN) between?parent :hasbrother?uncle and?uncle :hasbrother?parent Jan Pettersen Nytun, UIA, page 59

:Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund.

60 :Ester rdf:type :Woman ; :hasbrother :lav, :igmund. :Jan rdf:type :Man ; :hasparent :igmund. :Kirsten rdf:type :Woman ; :hasparent :igmund. :lav rdf:type :Man ; :hasister :Ester ; :hasbrother :igmund. :igmund rdf:type :Man ; :hasister :Ester; :hasbrother :Rolf. :igrund rdf:type :Woman ; :hasparent :igmund. :Rolf rdf:type :Man. PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < CNTRUCT {?n :hasuncle?uncle} WHERE {?n :hasparent?parent. {?uncle :hasbrother?parent.} UNIN {?parent :hasbrother?uncle }.?uncle rdf:type :Man. } Jan Pettersen Nytun, UIA, page 60

61 [4] Mapping several related relationships (mother, father, son, daughter) onto a single hierarchy (parent); CNTRUCT {?s :hasparent?o} WHERE{ {?s :hasmother?o} UNIN {?s :hasfather?o} UNIN {?o :hason?s} UNIN {?o :hasdaughter?s}} Jan Pettersen Nytun, UIA, page 61

62 Agenda P Example with: - RDER BY - UM Example continues with: - GRUP BY - GRUP BY together with UM Example continues with: - HAVING - BIND - CNCAT New example with: - CNTRUCT - INERT - DELETE - UNIN - CUNT page 62

63 Aggregates And Grouping [3] Aggregates apply expressions over groups of solutions. By default a solution set consists of a single group, containing all solutions. Grouping may be specified using the GRUP BY. Aggregates: CUNT, UM, MIN,. Jan Pettersen Nytun, UIA, page 63

64 Count [3]: Count is a PARQL set function which counts the number of times a given expression has a bound... [4]: For example, we could find out how many movies James Dean has played in: ELECT (CUNT (?movie) A?howmany) WHERE {:JamesDean?playedIn?movie.} Jan Pettersen Nytun, UIA, page 64

65 How many uncles do :Jan have? Jan Pettersen Nytun, UIA, page 65

66 PREFIX : < PREFIX rdf: < PREFIX owl: < PREFIX rdfs: < PREFIX xsd: < ELECT DITINCT (CUNT (?uncle) A?numberfUnclesForJan) WHERE { :Jan :hasparent?parent. {?uncle :hasbrother?parent.} UNIN {?parent :hasbrother?uncle }.?uncle rdf:type :Man. } Jan Pettersen Nytun, UIA, page 66

67 References [1] Book: David Poole and Alan Mackworth, Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010, [2] [3] PARQL 1.1 Query Language, W3C Recommendation 21 March 2013, [4] emantic Web for the Working ntologist, econd Edition: Effective Modeling in RDF and WL, May 20, 2011, by Dean Allemang, James Hendler [5] Appreciating PARQL CNTRUCT more, Bob DuCharme's weblog, Jan Pettersen Nytun, UIA, page 67

Knowledge Representation VII - IKT507. SPARQL stands for SPARQL Protocol And RDF Query Language

Knowledge Representation VII - IKT507 This sentence is false! PARQL stands for PARQL Protocol And RDF Query Language Jan Pettersen Nytun, UiA 1 The emantic Web tack Hierarchy of languages, where each layer