Practical Cross-Dataset Queries with SPARQL (Introduction)
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Practical Cross-Dataset Queries on the Web of Data
Tutorial @ WWW2012, Lyon, FranceRichard Cyganiak, Knud Möller, Anja
Jentzsch, Andreas Schultz, Robert Isele, Pablo Mendes
The Web is becoming a platform for data exchange.
• Microdata, Schema.org, web APIs, Linked Data Cloud, Open Data movement, …
• Often need to combine local and remote data from several heterogeneous sources
• Scripting and mash-ups. This works, but can we do better?
SPARQL as a query languagefor the Web
• Data from all of these data sources can be converted to RDF using off-the-shelf tools, or the sources are already RDF.
• SPARQL is W3C's standard query language for RDF
• SPARQL 1.1 just out, great new features for working with heterogeneous data
Caveats
• We will focus on ad-hoc queries.• This is not just about what works, but also
about what doesn't work.
How to get data into RDF format
• Relational: R2RML standard; D2RQ, Virtuoso RDF Views, Revelytix Spyder
• Excel, CSV: RDF Extension for Google Refine, XLWrap
• XML: XSPARQL• JSON: JSON-LD• Microformats, Microdata: Apache Any23• Collect data from many web pages: LDSpider
SPARQL: The big picture
SPARQL client
SPARQL engine
RDFStore
SPARQL Protocol
Scenario: Remote SPARQL endpoint
SPARQL client SPARQL engine
RDFStore
Scenario: Local SPARQL store
SPARQL client
SPARQL engine
Scenario: Local SPARQL engine, load data from files on the fly, no store
LocalRDFfile
RemoteRDFfile
Non-RDFfile
Conversion
SPARQL engine
RDFStore
Scenario: CONSTRUCT the input data
SPARQL client
SPARQL engineLocalRDFfile
SPARQLCONSTRUCT
query
SPARQL engine
RDFStore
LocalRDFfile
SPARQLCONSTRUCT
query
SPARQL engine
RDFStore
Scenario: Federated Query
SPARQL client
SPARQL engine
Basic Federated Query
LocalRDFfile
… or any combination of these.
Agenda – Morning
• Linked Data Basics• SPARQL Basics• 10:30–11:00 Coffee• Federated queries with SPARQL• Hands-on session 1• 12:30–13:30 Lunch
Agenda – Afternoon
• 12:30–13:30 Lunch• Schema mapping with SPARQL CONSTRUCT• Instance matching with Silk• Finding RDF datasets• 15:00–15:30 Coffee• Visualizing SPARQL query results• Hands-on session 2• 17:00 Adjourn
Hands-on sessions
• USB sticks with data, queries, and instructions• Install Apache Jena command line tools• Need a browser with a JavaScript console
(recommended: Firefox+Firebug or Chrome)
Music
Presenters
• Richard Cyganiak, DERI• Knud Möller, Talis• Anja Jentzsch, FU Berlin• Andreas Schultz, FU Berlin• Robert Isele, FU Berlin• Pablo Mendes, FU Berlin• (Christophe Guéret, VUA)• (Michael Hausenblas, DERI)
Please interrupt and ask questions!