Grants:Project/Rapid/Theredproject/WikidataQuickSheets/Report

Report accepted

This report for a Rapid Grant approved in FY 2017-18 has been reviewed and accepted by the Wikimedia Foundation.

• To read the approved grant submission describing the plan for this project, please visit Grants:Project/Rapid/Theredproject/WikidataQuickSheets.
• You may still comment on this report on its discussion page, or visit the discussion page to read the discussion about this report.
• You are welcome to Email rapidgrants at wikimedia dot org at any time if you have questions or concerns about this report.

Goals

Yes, we met most of our goals for this grant. We wrote and improved a set of python scripts called Wikidata QuickSheets that queries the Wikipedia and WIkidata APIs to return QIDs, and then queries Wikidata for P21 (Gender) and P106 (Occupation). Code is available on GitHub here: https://github.com/danaras/wikidata-quicksheets

Outcome

Please report on your original project targets.

In our proposal, we said that what we would have done at the end of our project was:

1. Improved software so it can add sources to Wikidata in a semi-automated process ✅ Yes, we did this.
   1. It would need to be able to work from a list of QIDs (possibly via PagePile?) ✅ Yes, the code handles article names or QIDs
   2. It would need to pull references from the Wikipedia entry, and search for the property values in the text of the reference. ✅ Yes, it pulls references from the wiki page
   3. One challenge here would be searching for all the terms associated with a specific ethnicity; it maybe be possible to do this via Wikidata aliases ✅ Yes, we are working with Wikidata aliases.
   4. It would need to be abstracted so that you could configure it to accept any property input, not just P106 or P172 ✅ Yes, it is abstracted
   5. Because of the potential for complex statements, it should be migrated to output in QuickStatements2 format ❌ No, we decided not to focus on this.
2. Tested said software by adding P172 data to at least 500 items ✅❌ Yes and no: we tested it, but decided not to input the data, as we used the same data set for our trainings, and didn't want to write over that data.
3. Created written and video documentation on how to use the software ✅ Yes, our written documentation is here, and our videos are here.
4. Held an in-person training on how to use the software ✅ Yes, held a training In person, and scheduled one Online (though we called it off, as we couldn't get enough people, despite expressing their interest)

Target outcome	Achieved outcome	Explanation
Improve Software	Done	See above for detail
Tested Software	Done	See above for detail
Drafted documentation	Done	See above for detail
Held Training	Done	See above for detail
Impact of 10 editors trained	We trained 8 editors
Impact of at least 500 Wikidata items	We have improved tens of thousands of Wikidata items with this tool

Learning

Projects do not always go according to plan. Sharing what you learned can help you and others plan similar projects in the future. Help the movement learn from your experience by answering the following questions:

• What worked well?
  • When the underlying data is good, the code works well
• What did not work so well?
  • But the underlying data isn't always so good. And it gets extra tricky crossing languages.
  • Even so, we were able to make it work.
• What would you do differently next time?
  • Skip the online training and just make documentation videos. That was a waste of planning energy, and time waiting.

Finances

Grant funds spent

Please describe how much grant money you spent for approved expenses, and tell us what you spent it on.

• Programmer Labor: $1995

Remaining funds

Do you have any remaining grant funds?

• We have no remaining funds.

Anything else

Anything else you want to share about your project?