Vocabulary for Linked Data Visualization Model - Dateso 2015
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There is already a vast amount of Linked Data on the web. What is missing is a convenient way of analyzing and visualizing the data that would benefit from the Linked Data principles. In our previous work we introduced the Linked Data Visualization Model (LDVM). It is a formal base that exploits the principles to ensure interoperability and compatibility of compliant components. In this paper we introduce a vocabulary for description of the components and an analytic and visualization pipeline composed of them. We demonstrate its viability on an example from the Czech Linked Open Data cloud.
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Vocabulary for Linked Data Visualization Model - Dateso 2015
- 1. Vocabulary for Linked Data Visualization Model Jakub Klímek Jiří Helmich http://xrg.cz | helmich@ksi.mff.cuni.cz XML and Web Engineering Research Group Faculty of Mathematics and Physics Charles University, Prague Czech Republic klimek@fit.cvut.cz Faculty of Information Technology Czech Technical University in Prague
- 2. Linked Data ❑ Use URIs to denote things. ❑ Use HTTP URIs so that these things can be dereferenced by people and user agents. ❑ Provide useful information about the thing when its URI is dereferenced (RDF, SPARQL). ❑ Include links to other related things when publishing data on the Web. 2 LDVM vocabulary
- 3. LOD Cloud 3
- 4. LDVM vocabulary CzLOD cloud ❑ OpenData.cz since 2012 ❑ 600M triples ❑ RUIAN 600M triples ❑ Virtuoso 7 instance http://linked.opendata.cz/sparql 4
- 5. Motivation ❑ bring Linked Data back to lay users ❑ use well-‐know presentation means ❑ 3 basic use cases ❑ What can I see in the given data? ❑ “Google-‐like approach” ❑ What can I combine my data with to see more? ❑ What data can I visualize like this? 5
- 9. LDVM ❑ Abstract process ▪ 4 stages ▪ 3 transformation types ▪ 3 operator types ❑ Adapted for RDF ▪ Input transformed to RDF ▪ Internally works with RDF ▪ Existing visualizers accept proprietary formats 9 LDVM vocabulary
- 10. LDVM stages ❑ Source RDF and non-‐RDF data ▪ Data transformation 10 LDVM vocabulary
- 11. LDVM stages ❑ Analytical abstraction ▪ Relevant data extraction using SPARQL operators ▪ Analyzers ▪ Reusability 11 LDVM vocabulary
- 12. LDVM stages ❑ Visualization abstraction ▪ Transformers ▪ Reusing concepts ▪ e.g. skos:broader 12 LDVM vocabulary
- 13. LDVM stages ❑ View ▪ Visualizers • User configuration (rotate, scale, zoom, etc.) ▪ End-‐users 13 LDVM vocabulary
- 14. LDVM instance 14 OVM entities with links to RUIAN entities with coordinates towns with coordinates OVM entities with coordinates LDVM vocabulary
- 15. LDVM implementation ❑ compatibility checks for existing pipelines ❑ pipeline discovery algorithm based on compatibility checks 15 LDVM vocabulary
- 16. LDVM components compatibility 16 LDVM vocabulary
- 17. LDVM compatibility ❑ Mandatory visualizer feature ❑ ASK { ?something s:geo ?g . ?g a s:GeoCoordinates ; s:latitude ?lat ; s:longitude ?lng . } 17
- 18. LDVM compatibility ❑ Optional visualizer feature ❑ ASK { ?something s:geo ?g ; s:title ?title . ?g a s:GeoCoordinates ; s:latitude ?lat ; s:longitude ?lng . } 18
- 19. LDVM compatibility ❑ Optional visualizer feature ❑ ASK { ?something s:geo ?g ; s:description ?desc . ?g a s:GeoCoordinates ; s:latitude ?lat ; s:longitude ?lng . } 19
- 20. LDVM Vocabulary ❑ based on LDVM architecture ❑ RDF definitions ❑ components, instances, pipelines ❑ clear specification ❑ anyone can define his own ❑ easy to share ❑ Linked Data processing described using Linked Data technologies (RDF, SPARQL) 20 LDVM vocabulary
- 22. Nested pipelines ❑ reusing components ❑ building complicated pipelines based on simple ones ❑ sharing 22 LDVM vocabulary
- 23. Links ❑ http://opendata.cz ❑ http://ldvm.opendata.cz ❑ http://linked.opendata.cz/sparql ❑ http://lov.okfn.org/dataset/lov/vocabs/ldvm ❑ https://github.com/payola/ldvm ❑ https://github.com/payola/LDVMi 23 LDVM vocabulary
- 24. Thank you for your attention Jakub Klímek Jiří Helmich http://xrg.cz | helmich@ksi.mff.cuni.cz XML and Web Engineering Research Group Faculty of Mathematics and Physics Charles University, Prague Czech Republic klimek@fit.cvut.cz Faculty of Information Technology Czech Technical University in Prague