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Christophe Gueret: Publish Web data - an interactive session

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Christophe Gueret (DANS, VU) “Publish Web data - an interactive session"
Presentation at the KnoweScape workshop "Evolution and variation of classification systems" March 4-5, 2015 Amsterdam

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Christophe Gueret: Publish Web data - an interactive session

  1. 1. Data Archiving and Networked Services Publishing data on the Web Christophe Guéret (@cgueret) Evolution and variation of classification systems March 4-5, 2015 Amsterdam
  2. 2. Publishing data on the Web ● Its' easy! Everybody does it! – … in very different ways :-/ ● Several, even not so big, issues : – Several competing standards and formats – Data hard to compare across sources – Lack of documentation – Limited capacities to assess trust – Missing dialog publisher ↔ consumer – etc
  3. 3. htp://www.w3.org/2013/dwbp/ ● W3C working group “Data on the Web best practices” ● Part of the Data Activity – Also in this activity : Working group for CSV on the Web ● Charted until July 2016, running since January 2014 ● Focus on defining best practices for publishing and using open data via the Web – Agnostic to technologies – Scope: government data, research data, cultural heritage data
  4. 4. Goals ● Publish a set of best practices for publishing a consum ing open data – and supporting list of use-cases and requirem ents ● Publish a vocabulary for quality and granularit description ● Publish a vocabulary for data usage descriptio
  5. 5. Feb 24 headlines : frst draf !!!
  6. 6. which means ... Weneed your feedbackon the work done so far ! © DonkeyHotey, Flickr
  7. 7. Plans for the remaining tme ● Go quickly through the best practices ● Split up in groups of 3 or 4 persons ● Each group review the BP and say what is missing, what should be deleted, what should be added, … – Write everything on post-its! ● We collect and cluster the input. This will be reported back to the group on Friday
  8. 8. The 27 best practces © James Perkins, Flickr
  9. 9. htp://www.w3.org/TR/dwbp/
  10. 10. Derived from htp://www.w3.org/TR/dwbp-ucr/
  11. 11. Grouped in topics (1/4) ● Metadata – What kind of metadata should be considered when describing data on the Web? – How can metadata be provided in a machine readable way? ● Data Identification – How can unique re-use be provided for data resources? – How should URIs be designed and managed for persistence? ● Data Formats – What kind of data formats should be considered when publishing data on the Web? (List based on https://www.linkedin.com/pulse/open-data-standards-steven-adler )
  12. 12. Grouped in topics (2/4) ● Data Vocabularies – How can existing vocabularies be used to provide semantic interoperability? – How can a new vocabulary be designed if needed? ● Data Licenses – How can data licenses be made machine readable? – How can license information about data published on the Web be provided/gathered? ● Data Provenance – How can data provenance information about data published on the Web be provided/gathered? (List based on https://www.linkedin.com/pulse/open-data-standards-steven-adler )
  13. 13. Grouped in topics (3/4) ● Data Quality – How can data quality information about data on the Web be provided/gathered? ● Sensitive Data – How can data be published without infringing a person's right to privacy or an organization's security? ● Data Access – What kind of data access should be considered when publishing data on the Web? – What requirements should be taken into account when deciding how to make data available on the Web? (List based on https://www.linkedin.com/pulse/open-data-standards-steven-adler )
  14. 14. Grouped in topics (4/4) ● Data Versions – How can different versions of a dataset be tracked and managed? ● Data Preservation – How can publishers decide when and how data on the Web should be archived? ● Feedback – How can user feedback about data consumed from the Web be gathered? (List based on https://www.linkedin.com/pulse/open-data-standards-steven-adler )
  15. 15. Hands-on ! © Ian Collins, Flickr

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