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EKAW - Linked Data Publishing

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Slides for the presentation on Linked Data Publishing in the Modeling, Generating and Publishing knowledge as Linked Data tutorial at EKAW 2016.

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EKAW - Linked Data Publishing

  1. 1. Linked Data Publishing Ruben Taelman - @rubensworks imec - Ghent University 1
  2. 2. Publishing as part of any Linked Data life cycle 2 Publish Query... ...
  3. 3. Linked Data Publishing Linked Data Interfaces Storage Non-technical tasks 3
  4. 4. Linked Data Publishing Linked Data Interfaces Storage Non-technical tasks 4
  5. 5. Linked Data provides machine-accessible data Machines can retrieve and discover data through HTTP interfaces Machines can understand the data 5
  6. 6. Ways for publishing Linked Data on the Web Data dump 1 RDF document Linked Data document RDF document per topic SPARQL endpoint Expressive query interface 6
  7. 7. Data dump Simple for data publisher Data dumps can be large (~gigabytes) Querying only possible after downloading entire dataset 7
  8. 8. Linked Data document Data is available in smaller fragments, according to subject Linked Data principle of dereferencing “3. When someone looks up a URI, provide useful information, using the open Web standards such as RDF, SPARQL” (Hyland 2013) Querying only possible by traversing links 8
  9. 9. SPARQL endpoint Requires higher computational effort from server Single point to get and expose data Easily queryable by clients 9
  10. 10. How do the different interfaces relate to each other? 10
  11. 11. Linked Data Fragments (LDF) A uniform view on Linked Data interfaces high client effort high server effort D ata dum p LD docum ent SPAR Q L result 11 (Verborgh 2016)
  12. 12. A big unexplored area on the LDF axis high client effort high server effort D ata dum p LD docum ent SPAR Q L result ? 12 (Verborgh 2016)
  13. 13. Triple Pattern Fragments (TPF), a trade-off between server and client effort high client effort high server effort D ata dum p LD docum ent SPAR Q L result TPF 13 (Verborgh 2016)
  14. 14. Triple Pattern Fragments Low-cost server interface Fragmentation of a dataset by triple patterns Client-side SPARQL query evaluation using a TPF interface 14
  15. 15. Choosing an LD interface as trade-off between server and client effort 15
  16. 16. URI policies for interfaces Linked Data uses URI’s as a global identification system URI design principles also apply to interface URI’s: Persistent URI’s and redirection Domain authority (e.g. government domain) Machine and human-readable representations through content negotiation ... 16
  17. 17. Linked Data Publishing Linked Data Interfaces Storage Non-technical tasks 17
  18. 18. Interface and storage solution influence each other 18
  19. 19. Start with most restrictive element Storage is fixed → storage, interface Machine limitations → interface, storage 19
  20. 20. Storage solutions for Linked Data interfaces Data dump Linked Data document Triple Pattern Fragments SPARQL endpoint RDF file, HDT, ... Static or dynamic RDF files RDF file, HDT, SPARQL engine, ... SPARQL engine 20
  21. 21. Linked Data Publishing Linked Data Interfaces Storage Non-technical tasks Licensing Publication announcement Maintenance 21
  22. 22. Linked Open Data requires an open license All published data should have a connected license Features of openness: (Open Knowledge Foundation) Availability and access Reuse and redistribution Universal participation Popular open license: CC0 Mention license in dataset listings and in metadata Confidential data might require restrictive license and security 22
  23. 23. Announcing to the public Communication channels: mailing lists, blogs, newsletters, … Feedback channel: form or contact address for any issues Centralized repositories (e.g. https://datahub.io) Automated discovery with metadata (e.g. DCAT, VOID) 23
  24. 24. Linked Data Publication is a continuous process Social contract with data consumers Avoid dataset / interface removal Data can change Movement of dataset to new location → URI persistence! Responsible entity behind feedback channel 24
  25. 25. Linked Data Publishing Linked Data Interfaces Storage Non-technical tasks 25
  26. 26. Conclusions Different Linked Data interfaces exist for publishing Linked Data Trade-off between server and client effort Interface and storage solution influence each other Properly license, announce and maintain your data 26
  27. 27. Sources R Verborgh “Linked Data Publishing” http://rubenverborgh.github.io/WebFundamentals/linked-data-publishing/ Hyland B, Atemezing G, Villazón-Terrazas B. “Best Practises for Publishing Linked Data” https://www.w3.org/TR/ld-bp/ Berners-Lee, Tim. "Linked data, 2006." (2006). https://www.w3.org/DesignIssues/LinkedData.html Villazón-Terrazas, Boris, et al. "Methodological guidelines for publishing government Linked Data." Linking government data. Springer New York, 2011. 27-49. 27

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