GDG Meets U event - Big data & Wikidata - no lies codelab

BigData & Wikidata - no lies
SPARQL queries on DBPedia
Camelia Boban

Resources for the codelab:
Eclipse Luna for J2EE developers - https://www.eclipse.org/downloads/index-developer.php
Java SE 1.8 - http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html
Apache Tomcat 8.0.5 - http://tomcat.apache.org/download-80.cgi
Axis2 1.6.2 - http://axis.apache.org/axis2/java/core/download.cgi
Apache Jena 2.11.1 - http://jena.apache.org/download/
Dbpedia Sparql endpoint: - dbpedia.org/sparql

JAR needed:
httpclient-4.2.3.jar httpcore-4.2.2.jar Jena-arq-2.11.1.jar
Jena-core-2.11.1.jar Jena-iri-1.0.1.jar jena-sdb-1.4.1.jar jena-tdb-1.0.1.jar
slf4j-api-1.6.4.jar slf4j-log4j12-1.6.4.jar
xercesImpl-2.11.0.jar xml-apis-1.4.01.jar
Attention!!
NO jcl-over-slf4j-1.6.4.jar (slf4j-log4j12-1.6.4 conflict, “Can’t override final class exception”)
NO httpcore-4.0.jar (made by Axis, httpcore-4.2.2.jar conflict, don’t let create the WS)

The Semantic Web
The Semantic Web is a project that intends to add computer-processable meaning
(semantics) to the Word Wide Web.
SPARQL
A a protocol and a query language SQL-like for querying RDF graphs via pattern
matching
VIRTUOSO
Both back-end database engine and the HTTP/SPARQL server.

DBpedia.org
Is the Semantic Web mirror of Wikipedia.
RDF
Is a data model of graphs on subject, predicate, object triples.
APACHE JENA
A free and open source Java framework for building Semantic Web and Linked
Data applications.
ARQ - A SPARQL Processor for Jena for querying Remote SPARQL Services

DBpedia.org extracts from Wikipedia editions in 119 languages, convert it into RDF
and make this information available on the Web:
★ 24.9 million things (16.8 million from the English Dbpedia);
★ labels and abstracts for 12.6 million unique things;
★ 24.6 million links to images and 27.6 million links to external web pages;
★ 45.0 million external links into other RDF datasets, 67.0 million links to
Wikipedia categories, and 41.2 million YAGO categories.

The dataset consists of 2.46 billion RDF triples (470 million were extracted from
the English edition of Wikipedia), 1.98 billion from other language editions, and 45
million are links to external datasets.
DBpedia uses the Resource Description Framework (RDF) as a flexible data
model for representing extracted information and for publishing it on the Web. We
use the SPARQL query language to query this data.

What is a Triple?
A Triple is the minimal amount of information expressable in Semantic Web. It is
composed of 3 elements:
1. A subject which is a URI (e.g., a "web address") that represents something.
2. A predicate which is another URI that represents a certain property of the
subject.
3. An object which can be a URI or a literal (a string) that is related to the
subject through the predicate.

John has the email address john@email.com
(subject) (predicate) (object)
Subjects, predicates, and objects are represented with URIs, which can be
abbreviated as prefixed names.
Objects can also be literals: strings, integers, booleans, etc.

Why SPARQL?
SPARQL is a quey language of the Semantic Web that lets us:
1. Extract values from structured and semi-strutured data
2. Explore data by querying unknown relatioships
3. Perform complex join query of various dataset in a unique query
4. Trasform data from a vocabulary in another

Structure of a SPARQL query:
● Prefix declarations, for abbreviating URIs ( PREFIX dbpowl:
<http://dbpedia.org/ontology/Mountain> = dbpowl:Mountain)
● Dataset definition, stating what RDF graph(s) are being queried (DBPedia,
Darwin Core Terms, Yago, FOAF - Friend of a Friend)
● A result clause, identifying what information to return from the query The
query pattern, specifying what to query for in the underlying dataset (Select)
● Query modifiers, slicing, ordering, and otherwise rearranging query results -
ORDER BY, GROUP BY

##EXAMPLE - Give me all cities & towns in Abruzzo with more than 50,000
inhabitants
PREFIX dbpclass: <http://dbpedia.org/class/yago/>
PREFIX dbpprop: <http://dbpedia.org/property/>
SELECT ?resource ?value
WHERE {
?resource a dbpclass:CitiesAndTownsInAbruzzo .
?resource dbpprop:populationTotal ?value .
FILTER ( ?value > 50000 )
}
ORDER BY ?resource ?value

Some PREFIX:
PREFIX owl: <http://www.w3.org/2002/07/owl#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX txn: <http://lod.taxonconcept.org/ontology/txn.owl#>

DBPEDIA
----------------------------------------------------------------------------------
PREFIX dbp: <http://dbpedia.org/>
PREFIX dbpowl: <http://dbpedia.org/ontology/>
PREFIX dbpres: <http://dbpedia.org/resource/>
PREFIX dbpprop: <http://dbpedia.org/property/>
PREFIX dbpclass: <http://dbpedia.org/class/yago/>

Wikipedia articles consist mostly of free text, but also contain different types of
structured information: infobox templates, categorisation information, images,
geo-coordinates, and links to external Web pages. DBpedia transforms into RDF
triples data that are entered in Wikipedia. So creating a page in Wikipedia creates
RDF in DBpedia.

Example:
https://en.wikipedia.org/wiki/Pulp_Fiction describes the movie. DBpedia creates a
URI: http://dbpedia.org/resource/wikipedia_page_name (where
wikipedia_page_name is the name of the regular Wikipedia html page) =
http://dbpedia.org/page/Pulp_Fiction. Underscore characters replace spaces.
DBpedia can be queried via a Web interface at ttp://dbpedia.org/sparql . The
interface uses the Virtuoso SPARQL Query Editor to query the DBpedia endpoint.

Public SPARQL Endpoint - use OpenLink Virtuoso
Wikipedia page: http://en.wikipedia.org/wiki/Pulp_Fiction
DBPedia resource: http://dbpedia.org/page/Pulp_Fiction
InfoBox: dbpedia-owl:abstract; dbpedia-owl:starring; dbpedia-owl:budget;
dbpprop:country; dbpprop:caption ecc.
For instance, the figure below shows the source code and the visualisation of an
infobox template containing structured information about Pulp Fiction.

Big&Wikidata - no lies
PREFIX prop: <http://dbpedia.org/property/>
PREFIX res:<http://dbpedia.org/resource/>
PREFIX owl:<http://dbpedia.org/ontology/>
SELECT DISTINCT ?name ?abstract ?caption ?image ?budget ?director ?cast ?country ?category
WHERE {
res:Pulp_Fiction prop:name ?name ;
owl:abstract ?abstract ;
prop:caption ?caption;
owl:thumbnail ?image;
owl:budget ?budget ;
owl:director ?director ;
owl:starring ?cast ;
prop:country ?country ;
dcterms:subject ?category .
FILTER langMatches( lang(?abstract), 'en').
}

Linked Data is a method of publishing RDF data on the Web and of interlinking
data between different data sources.
Query builder:
➢ http://dbpedia.org/snorql/
➢ http://querybuilder.dbpedia.org/
➢ http://dbpedia.org/isparql/
➢ http://dbpedia.org/fct/
➢ http://it.dbpedia.org/sparql
Prefix variables start with "?"

The current RDF vocabularies are available at the following locations:
➔ W3: http://www.w3.org/TR/vcard-rdf/ vCard Ontology - for describing People
and Organizations
http://www.w3.org/2003/01/geo/ Geo Ontology - for spatially-located things
http://www.w3.org/2004/02/geo/ SKOS Simple Knowledge Organization
System

➔ GEO NAMES: http://www.geonames.org/ geospatial semantic information
(postal code)
➔ DUBLIN CORE: http://www.dublincore.org/ defines general metadata
attributes used in a particular application
➔ FOAF: http://www.foaf-project.org/ Friend of a Friend, vocabulary for
describing people
➔ UNIPROT: http://www.uniprot.org/core/, http://beta.sparql.uniprot.org/uniprot
for science articles

➔ MUSIC ONTOLOGY: http://musicontology.com/, provides terms for
describing artists, albums and tracks.
➔ REVIEW VOCABULARY: http://purl.org/stuff/rev , vocabulary for
representing reviews.
➔ CREATIVE COMMONS (CC): http://creativecommons.org/ns , vocabulary for
describing license terms.
➔ OPEN UNIVERSITY: http://data.open.ac.uk/

➔ Semantically-Interlinked Online Communities (SIOC): www.sioc-
project.org/, vocabulary for representing online communities
➔ Description of a Project (DOAP): http://usefulinc.com/doap/, vocabulary for
describing projects
➔ Simple Knowledge Organization System (SKOS):
http://www.w3.org/2004/02/skos/, vocabulary for representing taxonomies and
loosely structured knowledge

SPARQL queries have two parts (FROM is not indispensable):
1. The query (WHERE) part, which produces a list of variable bindings (although
some variables may be unbound).
2. The part which puts together the results. SELECT, ASK, CONSTRUCT, or
DESCRIBE.
Other keywords:
UNION, OPTIONAL (optional display if data exists), FILTER (conditions), ORDER
BY, GROUP BY

SELECT - is effectively what the query returns (a ResultSet)
ASK - just looks to see if there are any results
COSTRUCT - uses a template to make RDF from the results. For each result row
it binds the variables and adds the statements to the result model. If a template
triple contains an unbound variable it is skipped. Return a new RDF-Graph
DESCRIBE - unusual, since it takes each result node, finds triples associated with
it, and adds them to a result model. Return a new RDF-Graph

What linked data il good for? Don’t search a single thing, but explore a whole
set of related things together!
1) Revolutionize Wikipedia Search
2) Include DBpedia data in our own web page
3) Mobile and Geographic Applications
4) Document Classification, Annotation and Social Bookmarking
5) Multi-Domain Ontology
6) Nucleus for the Web of Data

MOBILE
QRpedia.org - MIT Licence

WIKIPEDIA DUMPS
● Arabic Wikipedia dumps: http://dumps.wikimedia.org/arwiki/
● Dutch Wikipedia dumps: http://dumps.wikimedia.org/nlwiki/
● English Wikipedia dumps: http://dumps.wikimedia.org/enwiki/
● French Wikipedia dumps: http://dumps.wikimedia.org/frwiki/
● German Wikipedia dumps: http://dumps.wikimedia.org/dewiki/
● Italian Wikipedia dumps: http://dumps.wikimedia.org/itwiki/
● Persian Wikipedia dumps: http://dumps.wikimedia.org/fawiki/
● Polish Wikipedia dumps: http://dumps.wikimedia.org/plwiki/

WIKIPEDIA DUMPS
● Portuguese Wikipedia dumps: http://dumps.wikimedia.org/ptwiki/
● Russian Wikipedia dumps: http://dumps.wikimedia.org/ruwiki/
● Serbian Wikipedia dumps: http://dumps.wikimedia.org/srwiki/
● Spanish Wikipedia dumps: http://dumps.wikimedia.org/eswiki/
● Swedish Wikipedia dumps: http://dumps.wikimedia.org/svwiki/
● Ukrainian Wikipedia dumps: http://dumps.wikimedia.org/ukwiki/
● Vietnamese Wikipedia dumps: http://dumps.wikimedia.org/viwiki/

LINK
Codelab’s project code: http://github.com/GDG-L-Ab/SparqlOpendataWS
http://dbpedia.org/sparql & http://it.dbpedia.org/sparql
http://wiki.dbpedia.org/Datasets
http://en.wikipedia.org/ & http://it.wikipedia.org/
http://dbpedia.org/snorql, http://data.semanticweb.org/snorql/ SPARQL Explorer
http://downloads.dbpedia.org/3.9/ & http://wiki.dbpedia.org/Downloads39

Projects that use linked data:
JAVA: Open Learn Linked data: free access to Open University course materials
PHP: Semantic MediaWiki -Lllets you store and query data within the wiki's pages.
PEARL: WikSAR
PYTHON: Braindump - semantic search in Wikipedia
RUBY: SemperWiki

THANK YOU! :-)
I AM
CAMELIA BOBAN
G+ : https://plus.google.com/u/0/+cameliaboban
Twitter : http://twitter.com/GDGRomaLAb
LinkedIn: it.linkedin.com/pub/camelia-boban/22/191/313/
Blog: http://blog.aissatechnologies.com/
Skype: camelia.boban
camelia.boban@gmail.com

GDG Meets U event - Big data & Wikidata - no lies codelab

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (20)

Destaque

Destaque (6)

Semelhante a GDG Meets U event - Big data & Wikidata - no lies codelab

Semelhante a GDG Meets U event - Big data & Wikidata - no lies codelab (20)

Mais de CAMELIA BOBAN

Mais de CAMELIA BOBAN (20)

Último

Último (20)

GDG Meets U event - Big data & Wikidata - no lies codelab