My idea is to collate and export the Nigerian election polling units to Wikidata. This would be achieved via a series of volunteer-driven activities
| Wikidata of Nigerian Election Poling Units | |
|---|---|
| A WikiCred 2022 Grant Proposal | |
| Project Type | Event |
| Author | (Yemi festus) |
| Contact | yemifestusfx2@gmail.com |
| Requested amount | USD 9470 |
| Award amount | Unknown |
- What is your idea?
- Why is it important?
According to the Independent National Electoral Commission, INEC, there are more than 187,000 polling units for the Nigerian general election. However, no data relating to these polling units are available on Wikidata.
- Link(s) to your resume or anything else (CV, GitHub, etc.) that may be relevant
https://meta.wikimedia.org/wiki/User:Yemi_festus
- Is your project already in progress?
No. It’s a newly designed project that we hope to implement with funding support from WikiCred
- How is this project relevant to credibility and Wikipedia?
Accurate information about election polling units impacts the credibility of the election and the accuracy of the contents relating to the election on Wikidata, Wikipedia, and other Wikimedia projects. This project is relevant to information credibility and Wikidata and Wikipedia.
- What is the ultimate impact of this project?
- Export more than 187,000 data on polling units to Wikidata
- Train volunteers on how to use important tools such as OpenRefine, and QuickStatement
- Increase the number of contents relating to the Nigeria election on Wikidata
- Increase the accuracy, credibility, and reliability of the information relating to the Nigeria election on Wikidata
- Can your project scale?
- Yes, the project could be scaled and the outputs are measurable
- Why are you the people to do it?
We are the people to do it because we have experience in data gathering, cleanup, and exportation of large data to Wikidata
- What is the impact of your idea on diversity and inclusiveness of the Wikimedia movement?
This idea aligns with the movement strategy recommendation on Innovation in free knowledge and also knowledge equity, inclusion, and diversity.
- What are the challenges associated with this project and how you will overcome them?
- The major challenge associated with this project is data gathering and data refinement. Data gathering would be done by at least 10 volunteers and supervised by experienced data analysts. We have identified OpenRefine as a potential tool to clean or refine our data.
- How will you spend your funds?
How will you spend your funds? The fund would be spent on the items listed below
- Monthly Stipends for volunteers - USD 100 X 10 x 3 months = USD 3000
- Hall for training on Wikidata, OpenRefine, and QuickStatement - USD 200 X 3 Days = USD 600
- Food &Drinks during training - USD 10 X 20 people x 3 days = USD 600
- Internet data for training - USD 100
- Hall for data-a-thon - USD 200 X 3 = USD 600
- Hall for Edit-a-thon to export the data to Wikidata - USD 200 X 3 Days = USD 400
- Food & Drinks for Edit-a-thon - USD 10 X 20 people x 3 days = USD 600
- Internet data for Edit-a-thon - USD 100
Project Management - USD 500 per month x 3 months = USD 1500 Banner at event venue - USD 70 Transport support for volunteers during training and edit-a-thon = USD 30 X 10 people x 6 events = USD 1,800 Contigency - USD 100
Total = 9,470
- How long will your project take?
4 Months ( 3 months for implementation and 1 month for reporting.)
- Have you worked on projects for previous grants before?
Yes, WMF Grants