Creating Visualizations with Linked Open Data
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This document discusses creating visualizations with linked open data using Visualbox. It begins with an overview of linked data and how to query it using SPARQL. Examples are provided of SPARQL queries to retrieve data about London and schools in London from public linked data sets. The document then introduces Visualbox as a tool for applying visualizations to the query results. It describes the components of Visualbox including using a SPARQL query to obtain data, selecting a visualization type and filters, testing the query, and viewing or embedding the final visualization.
Creating Visualizations with Linked Open Data
- 1. CREATING VISUALIZATIONS WITH LINKED OPEN DATA Alvaro Graves @alvarograves [email protected]
- 2. AGENDA • What is Linked Data? • How can I query Linked Data? • How to create visualizations using Visualbox
- 3. WHAT IS LINKED DATA? • Linked Data is a way to publish data in a machine- readable way • Itallows you to describe information about things on the Web and their relationships • Government, NGOs and universities publish Linked Data
- 4. WHAT IS LINKED DATA? • Example: • London is the capital of England. • London’s population is 8 million people • England is a Country.
- 5. WHAT IS LINKED DATA? England is a capital of Country London population 8.000.000 • England is a Country. • England ‘s capital is London. • London’s population is 8 million people
- 6. ON THE WEB... • We create a URI (i.e., “web address”-like identifier) for everything • London → http://dbpedia.org/resource/London • England → http://dbpedia.org/resource/England • Country → http://dbpedia.org/ontology/Country • Same for relations! • capital of → http://dbpedia.org/ontology/capital • is a → http://www.w3.org/1999/02/22-rdf-syntax-ns#type • population → http://dbpedia.org/ontology/populationUrban
- 7. LINKED DATA England is a capital of Country London population 8.000.000 http://dbpedia.org/resource/England http://dbpedia.org/ontology/capital http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/resource/London http://dbpedia.org/ontology/populationUrban http://dbpedia.org/ontology/Country 8.000.000
- 8. HOW CAN I QUERY LINKED DATA? • We can use SPARQL, a query language for Linked Data • People (and governments) publishes Linked Data in SPARQL endpoints that can be queried
- 9. HOW SPARQL LOOKS PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbp: <http://dbpedia.org/resource/> SELECT ?city ?population WHERE{ dbp:England dbo:capital ?city . ?city dbo:populationUrban ?population . }
- 10. RESULTS Executed against http://dbpedia.org/sparql
- 11. SCHOOLS IN THE CITY OF LONDON PREFIX sch-ont: <http://education.data.gov.uk/def/school/> PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> PREFIX district: <http://statistics.data.gov.uk/id/local-authority-district/> SELECT ?school ?name ?lat ?long WHERE { ?school a sch-ont:School; sch-ont:establishmentName ?name; geo:lat ?lat; geo:long ?long; sch-ont:districtAdministrative district:00AA . } ORDER BY ?name
- 12. RESULTS Executed against http://education.data.gov.uk/sparql/education/query school name lat long http://education.data.gov.uk/id/school/581261 Barbican Playgroup 51.51879 -0.09267 Buffer Bear @ Barts & http://education.data.gov.uk/id/school/531003 51.51697 -0.10086 the London Charterhouse Square http://education.data.gov.uk/id/school/590270 51.52038 -0.09886 School
- 14. HOW TO CREATE VISUALIZATIONS • Part 1: Obtain the data ✓ • Part 2: Apply a visualization → Visualbox
- 15. VISUALBOX
- 17. VISUALBOX SPARQL query
- 18. VISUALBOX Visualization (HTML)
- 19. VISUALBOX Visualization Filters
- 20. VISUALBOX
- 21. VISUALBOX Query testing Results
- 22. VISUALBOX View & embed component
- 23. START PLAYING WITH VISUALBOX Edit: Final demos available at http://orion.tw.rpi.edu/~agraves/mozfest/index.html