Practical Cross-Dataset Queries with SPARQL (Introduction)
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This document provides an overview of using SPARQL as a query language for querying data across the web of data. It discusses how data from different sources like relational databases, Excel files, XML, JSON, microdata, etc. can be converted to RDF and queried using SPARQL. The tutorial will cover topics like federated querying across local and remote SPARQL endpoints, using SPARQL CONSTRUCT to map schemas, instance matching with Silk, and visualizing SPARQL results. Hands-on sessions will have participants install Jena tools and run queries on sample RDF data and endpoints.
Practical Cross-Dataset Queries with SPARQL (Introduction)
- 1. Practical Cross-Dataset Queries on the Web of Data Tutorial @ WWW2012, Lyon, France Richard Cyganiak, KnudMöller, AnjaJentzsch, An dreas Schultz, Robert Isele, Pablo Mendes
- 2. 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?
- 3. SPARQL as a query language for 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
- 4. Caveats • We will focus on ad-hoc queries. • This is not just about what works, but also about what doesn't work.
- 5. How to get data into RDF format • Relational: R2RML standard; D2RQ, Virtuoso RDF Views, RevelytixSpyder • Excel, CSV: RDF Extension for Google Refine, XLWrap • XML: XSPARQL • JSON: JSON-LD • Microformats, Microdata: Apache Any23 • Collect data from many web pages: LDSpider
- 6. SPARQL: The big picture
- 7. Scenario: Remote SPARQL endpoint SPARQL client SPARQL Protocol SPARQL engine RDF Store
- 8. Scenario: Local SPARQL store SPARQL client SPARQL engine RDF Store
- 9. Scenario: Local SPARQL engine, load data from files on the fly, no store SPARQL client Local SPARQL engine RDF file Conversion Non- RDF file Remote RDF file
- 10. Scenario: CONSTRUCT the input data SPARQL client Local Local RDF SPARQL engine RDF file file SPARQL SPARQL CONSTRUCT CONSTRUCT query query SPARQL engine SPARQL engine RDF RDF Store Store
- 11. Scenario: Federated Query SPARQL client Local RDF SPARQL engine file Basic Federated Query SPARQL engine RDF Store
- 12. … or any combination of these.
- 13. 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
- 14. 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
- 15. 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)
- 16. Music
- 17. Presenters • Richard Cyganiak, DERI • KnudMöller, Talis • AnjaJentzsch, FU Berlin • Andreas Schultz, FU Berlin • Robert Isele, FU Berlin • Pablo Mendes, FU Berlin • (Christophe Guéret, VUA) • (Michael Hausenblas, DERI)
- 18. Please interrupt and ask questions!