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Informal presentation about RES
The document discusses linked data, its methods, and its applications in the research and education space, highlighting the transition from handling documents to managing data on the web. It emphasizes the importance of using identifiers, creating links, and the role of vocabularies in semantic web practices. Additionally, it outlines how the research and education space assists GLAM organizations in publishing linked open data and indexing for search interfaces.
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Informal presentation about RES
- 1. LD & theresearch and education space Christophe Guéret Archive Development (TV) / TSA (D&E) @cgueret
- 2. disclaimer: will beexperimenting following guidelines from Alice Bartlett and Russell Davies (mostly) @mildlydiverting made the Google Template
- 3. 1. Linked Data 2.Research and Education Space
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- 5. Linked Data Linked OpenData Semantic Web Three different concepts !
- 6. Linked Data Method forpublishing data using HTTP as a storage and communication layer More info on https://en.wikipedia.org/wiki/Linked_data
- 7. Linked Open Data LinkedData applied to Open Data For a definition of Open Data : http://opendefinition.org/
- 8. Semantic Web Using thesemantic capabilities of Linked Data to derive information
- 9. Why Linked Data? Slides derived from http://www.slideshare.net/cgueret/linking-knowledge-spaces
- 10. Dealing with documentsuntil 1989 1. Find a source for the document 2. Find a way to parse the document 3. Create links and index the content 4. Repeat on each update
- 11. Then came theWeb... Standardized, connected, decentralised, easy Document Document Document One server Another server
- 12. Dealing with datauntil, well, now 1. Find a source for the data 2. Find a way to parse the data 3. Create links and index the data 4. Repeat on each update
- 13. We deal withdata the way we dealt with documents 20 years ago
- 14. Many formats, nolinks, ETL
- 15. Okay it’s notthat bad... ● We have Web APIs now ● All the APIs are RESTful ● All the APIs do JSON, or XML
- 16. But what aboutschemas ? and links ?
- 18. Linked Data =doing the Web again but for data instead of documents
- 19. It’s possible because “Factual knowledge isa graph” http://videolectures.net/iswc2011_van_harmelen_universal/
- 20. Concretely “Lille is inFrance and called Rijsel in Dutch” http://dbpedia.org/resource/Lille http://dbpedia.org/resource/France“Rijsel”@nl http://dbpedia.org/ontology/country http://www.w3.org/2000/01/rdf-schema#label
- 21. Not rocket science: ●Use IRIs for identifiers ● Bind identifiers to data about them ● Bind identifiers to other identifiers ● Use IRIs for typing the links
- 22. Vocabularies ● QB :statistics ● PROV-O : provenance ● SIOC : social media ● Schema.org : search engine results ● And many more ...
- 23. Every data setis a graph part of a bigger graph Only need to know the vocabulary used to meaningfully consume it
- 24. Vocabularies are partof the graph too! http://dbpedia.org/ontology/country http://www.w3.org/2000/01/rdf-schema#comment “The country where the thing is located.”@en
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- 28. Two major trapsto avoid ● Using the same IRI for a thing and the document describing it ● Applying a license to a thing instead of applying it to a document
- 29. And the semanticweb then ?
- 30. LOD + Semantics= Semantic Web ● Document vocabularies with logics => New data gets derived ● “Lille is in France” + “All cities in France are in Europe” => “Lille is in Europe”
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- 32. 2. Research andEducation Space
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- 34. The Research andEducation Space
- 35. In practice we ●Help GLAMs to publish LOD ● Crawl and index that LOD ● Provide a search interface over the data crawled
- 36. Our crawler followslinks across data publishers to hunt for (properly licensed) LOD There is a set of rules used to interpret the data in a specific way
- 38. All of thatis open source ! Both what we use and what we code :-)
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