Wikidata:Wikimedian in Residence Summit Part 3

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Grandiose name, but so deserving. The third WMUK sponsored meeting of Wikimedians in Residence to skillshare and develop the role of WiRs.

This is a page to record everything.

Datasets

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Slides

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Referring back to things we can't remember

Common issues, questions, needs & possibly answers

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The pig of presentation
  • Fixing duplicate items in Sparql - Example
  • Tools, their maintenance and access
  • Building case studies and showcases with which to advocate internally
  • Database copyright in practice
  • How to set up a Wikidata project? Is there a format to follow?
  • Matching subject expertise with data uploads and management
  • How can institutions get mutual benefit from their engagement with WD? (ie enriching catalogues with crowdsourced info from WD or tools like Monumental, for example)
  • SPARQL line for excluding fictional people from a person query:
MINUS{ ?person wdt:P31/wdt:P279? wd:Q15632617 }
  • We are importing data without subject matter expertise
  • No easy way to do metrics for partners sharing data
  • To import data into Wikidata you need to be really good at spreadsheets
  • Lots of people are creating documentation for their project but hardly anyone is creating general documentation
  • A lot of missing basic documentation
  • Missing Wikidata tours
  • Missing documentation on how to make cool graphs and other visualisations
  • Don't know where all the useful case studies are to show Wikidata is useful to potential partners
  • Database rights and copyright is confusing and unclear
  • Lots of tools break quite a lot and are often reliant on one person, Magnus
  • Wikidata:Data donation is not a very good name
  • How to keep data in sync with updates in the original source
  • Subject matter experts find it really hard to contribute
  • How to track changes in the data that has been imported into Wikidata
  • How to know what to do with with Wikidata as a WiR, so many options, hard to know what is posible and valuable to the host organisation
  • Don't know where all the case studies are
  • Query service instructions hurt my brain
  • How to convince people in organisations Wikidata is good
  • Property proposals are hard to do and the instructions aren't very good



Opportunities

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Existing Tools

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Existing resources

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THOSE ALL IMPORTANT CASE STUDIES

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  • please add more here

Wishlist?

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  • Bot for recognising additions without references. - I think PyWikiBot could do this. Learn Python!
You could do something like this. Just change the query to include references.
  • What is the gas function?
The Gather Apply Scatter (GAS) model was developed in a series of papers on the GraphLab and GraphChi platforms.Part of the evolution of this API has been learning about the constraints that allow for scalable, multi-machine, and (with MapGraph), massively parallel graph algorithms.
Bigdata implements a version of the GAS abstraction that is designed to work efficiently with RDF, including efficient link attributes. This implementation is exposed to SPARQL end points as a SERVICE.

Attendees

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  • sign in here....
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