程序代写代做 database Bioinformatics graph go html SPARQL By Example: The Cheat Sheet

程序代写 CS代考 / Bioinformatics, database

SPARQL By Example: The Cheat Sheet
Accompanies slides at:
http://www.cambridgesemantics.com/2008/09/sparql-by-example/
Comments & questions to:
Lee Feigenbaum VP Technology & Standards, Cambridge Semantics Co-chair, W3C SPARQL Working Group

Conventions Red text means:
“This is a core part of the SPARQL syntax or language.”
Blue text means:
“This is an example of query-specific text or values that might go into a SPARQL query.”

a  rdf:type
Variables
?var1, ?anotherVar, ?and_one_more
Triple Patterns
Typed literal:
Shortcuts:
Nuts & Bolts
URIs
Write full URIs:
Literals
“a plain literal”
“bonjour”@fr
“13”^^xsd:integer
Plain literals:

Abbreviate URIs with prefixes:
PREFIX foo: … foo:bar …
 http://this.is.a/URI/prefix#bar Shortcuts:
Plain literal with language tag:
true  “true”^^xsd:boolean 3  “3”^^xsd:integer 4.2  “4.2”^^xsd:decimal
Comments
Variables:
Comments:
ex:myWidget ex:partNumber “XY24Z1” . ?person foaf:name “Lee Feigenbaum” . conf:SemTech2009 ?property ?value .
# Comments start with a „#‟
# continue to the end of the line
Match an exact RDF triple: Match one variable: Match multiple variables:

Common Prefixes
prefix… …stands for
rdf: http://xmlns.com/foaf/0.1/
rdfs: http://www.w3.org/2000/01/rdf-schema#
owl: http://www.w3.org/2002/07/owl#
xsd: http://www.w3.org/2001/XMLSchema#
dc: http://purl.org/dc/elements/1.1/
foaf: http://xmlns.com/foaf/0.1/
More common prefixes at http://prefix.cc

Declare prefix shortcuts (optional)
Define the dataset (optional)
Anatomy of a Query
PREFIX foo: <...> PREFIX bar: <...> …
SELECT …
FROM <...>
FROM NAMED <...>
WHERE {
…
}
GROUP BY … HAVING … ORDER BY … LIMIT … OFFSET … BINDINGS …
Query result clause
Query pattern
Query modifiers (optional)

4 Types of SPARQL Queries
SELECT queries
Project out specific variables and expressions:
SELECT ?c ?cap (1000 * ?people AS ?pop) Project out all variables:
SELECT *
SELECT DISTINCT ?country
CONSTRUCT queries
Project out distinct combinations only: Results in a table of values (in XML or JSON):
ex:France a ex:HolidayDestination ; ex:arrive_at ex:Paris ; ex:population 635000000 .
ex:Canada a ex:HolidayDestination ; ex:arrive_at ex:Ottawa ; ex:population 329000000 .
DESCRIBE queries
Describe the resources matched by the given variables:
DESCRIBE ?country
Result is RDF triples (in any RDF serialization) :
ex:France a geo:Country ;
ex:continent geo:Europe ;
ex:flag ; …
CONSTRUCT {
?country a ex:HolidayDestination ;
}
ex:arrive_at ?capital ; ex:population ?population .
Results in RDF triples (in any RDF serialization):
Construct RDF triples/graphs:
?c
?cap
?pop
ex:France
ex:Paris
63,500,000
ex:Canada
ex:Ottawa
32,900,000
ex:Italy
ex:Rome
58,900,000
ASK queries
Ask whether or not there are any matches:
ASK
Result is either “true” or “false” (in XML or JSON): true, false

Combining SPARQL Graph Patterns
Consider A and B as graph patterns.
A Basic Graph Pattern – one or more triple patterns
A.B
 Conjunction. Join together the results of solving A and B by matching the
values of any variables in common.
Optional Graph Patterns
A OPTIONAL { B }
 Left join. Join together the results of solving A and B by matching the values of any variables in common, if possible. Keep all solutions from A whether or not there’s a matching solution in B

Combining SPARQL Graph Patterns
Consider A and B as graph patterns. Either-or Graph Patterns
{ A } UNION { B }
 Disjunction. Include both the results of solving A and the results of
solving B.
A MINUS { B }
“Subtracted” Graph Patterns (SPARQL 1.1)
 Negation. Solve A. Solve B. Include only those results from solving A that are not compatible with any of the results from B.

SPARQL Subqueries (SPARQL 1.1) Consider A and B as graph patterns.
A.
{
SELECT …
WHERE {
B
} }
C.
 Join the results of the subquery with the results of solving A and C.

SPARQL Filters
• SPARQL FILTERs eliminate solutions that do not cause an expression to evaluate to true.
• Place FILTERs in a query inline within a basic graph pattern A . B . FILTER ( …expr… )
Category
Functions / Operators
Examples
Logical
!, &&, ||, =, !=, <, <=, >, >=
?hasPermit || ?age < 25 Math +, -, *, / ?decimal * 10 > ?minPercent
Existence
(SPARQL 1.1)
EXISTS, NOT EXISTS
NOT EXISTS { ?p foaf:mbox ?email }
SPARQL tests
isURI, isBlank, isLiteral, bound
isURI(?person) || !bound(?person)
Accessors
str, lang, datatype
lang(?title) = “en”
Miscellaneous
sameTerm, langMatches, regex
regex(?ssn, “\\d{3}-\\d{2}-\\d{4}”)

Aggregates (SPARQL 1.1)
1. Partition results into groups based on the expression(s) in the GROUP BY clause
2. Evaluate projections and aggregate functions in SELECT clause to get one result per group
3. Filter aggregated results via the HAVING clause
SPARQL 1.1 includes: COUNT, SUM, AVG, MIN, MAX, SAMPLE, GROUP_CONCAT
?key
?val
?other1
1
4
…
1
4
…
2
5
…
2
4
…
2
10
…
2
2
…
2
1
…
3
3
…
?key
?sum_of_val
1
8
2
22
3
3
?key
?sum_of_val
1
8
3
3

Property Paths (SPARQL 1.1)
• Property paths allow triple patterns to match arbitrary-
length paths through a graph
• Predicates are combined with regular-expression-like operators:
Construct
Meaning
path1/path2
Forwards path (path1 followed by path2)
^path1
Backwards path (object to subject)
path1|path2
Either path1 or path2
path1*
path1, repeated zero or more times
path1+
path1, repeated one or more times
path1?
path1, optionally
path1{m,n}
Atleastmandnomorethann occurrencesofpath1
path1{n}
Exactly n occurrences of path1
path1{m,}
At least m occurrences of path1
path1{,n}
At most n occurrences of path1

RDF Datasets
A SPARQL queries a default graph (normally) and zero or
more named graphs (when inside a GRAPH clause).
Default graph
(the merge of zero or more graphs)
PREFIX ex: <...> SELECT …
FROM ex:g1
FROM ex:g4
FROM NAMED ex:g1 FROM NAMED ex:g2 FROM NAMED ex:g3 WHERE {
…A…
GRAPH ex:g3 {
…B… }
GRAPH ?g { …C…
} }
ex:g1
ex:g4
Named graphs
ex:g1
ex:g3
OR
OR
ex:g2

SPARQL Over HTTP (the SPARQL Protocol)
http://host.domain.com/sparql/endpoint? where can include:
query=
e.g. SELECT+*%0DWHERE+{…
default-graph-uri=
e.g. http%3A%2F%2Fexmaple.com%2Ffoo…
n.b. zero of more occurrences of default-graph-uri named-graph-uri=
e.g. http%3A%2F%2Fexmaple.com%2Fbar…
n.b. zero of more occurrences of named-graph-uri
HTTP GET or POST. Graphs given in the protocol override graphs given in the query.

Federated Query (SPARQL 1.1)
LocalGraphStore
ex:g1
PREFIX ex: <...> SELECT …
FROM ex:g1 WHERE {
…A…
SERVICE ex:s1 {
…B… }
SERVICE ex:s2 { …C…
} }
SPARQL Endpoint
ex:s1
Web
SPARQL Endpoint
ex:s2

SPARQL 1.1 Update
SPARQL Update Language Statements
INSERT DATA { triples }
DELETE DATA {triples}
[ DELETE { template } ] [ INSERT { template } ] WHERE { pattern }
LOAD [ INTO GRAPH ]
CLEAR GRAPH
CREATAE GRAPH
DROP GRAPH
[ … ] denotes optional parts of SPARQL 1.1 Update syntax

Some Public SPARQL Endpoints
Name
URL
What’s there?
SPARQLer
http://sparql.org/sparql.html
General-purpose query endpoint for Web-accessible data
DBPedia
http://dbpedia.org/sparql
Extensive RDF data from Wikipedia
DBLP
http://www4.wiwiss.fu-berlin.de/dblp/snorql/
Bibliographic data from computer science journals and conferences
LinkedMDB
http://data.linkedmdb.org/sparql
Films, actors, directors, writers, producers, etc.
World Factbook
http://www4.wiwiss.fu- berlin.de/factbook/snorql/
Country statistics from the CIA World Factbook
bio2rdf
http://bio2rdf.org/sparql
Bioinformatics data from around 40 public databases

SPARQL Resources
• TheSPARQLSpecification
– http://www.w3.org/TR/rdf-sparql-query/
• SPARQLimplementations
– http://esw.w3.org/topic/SparqlImplementations
• SPARQLendpoints
– http://esw.w3.org/topic/SparqlEndpoints
• SPARQL Frequently Asked Questions
– http://www.thefigtrees.net/lee/sw/sparql-faq
• SPARQLWorkingGroup
– http://www.w3.org/2009/sparql/wiki/
• CommonSPARQLextensions
– http://esw.w3.org/topic/SPARQL/Extensions

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