Humaniki/FAQ

Welcome to Humaniki! You might be confused about what Humaniki is, but this page hopes to explain the answer to some common questions.

What is humaniki?
Humaniki provides statistics about the gender gap in the content of all Wikimedia projects based on data available on Wikidata. The data is available under the creative commons license and is free for anyone to use!

Why humaniki doesn’t reflect editing I did yesterday?
Although it would be useful the queries that WHGI runs are too large for community SQL/SPARQL services. Instead to compute the statistics WHGI downloads the entire Wikidata dump and parses it with Wikidata Toolkit. That is, say for instance a dump file that is created by Wikidata on March 5th, it might only be reflecting the latest data up to March 4th. WHGI runs every day midnight, so it's actually getting a Wikidata Dump that's maybe a day-or-two out of date. So even if you did something on March 5th and WHGI runs on March 5th, because of the dump latency it's possible it won't show up in time. We bet if you check back after 24 hrs you might see the results you were expecting.

I am new to humaniki, What all can I do with this tool?
Link to Demo Video: https://www.youtube.com/watch?v=0cbPWeJ8PiQ

How can I contribute?
1. Adding data labels for missing fields in Wikidata. 2.You can help with the project code and make extensions [ADD - provide leads for such users]

What data it uses?
Humaniki uses Wikidata, the centralized knowledge base of Wikimedia projects, to generate statistics. It only imports data that has properties associated with humans and not otherwise.

How is gender structured in Wikidata
Wikidata is a free, collaborative, multilingual, secondary database, collecting structured data to provide support for Wikipedia, Wikimedia Commons, the other wikis of the Wikimedia movement, and to anyone in the world (Read more).

The Wikidata repository consists mainly of items, each one having a label, a description and any number of aliases. Items are uniquely identified by a Q followed by a number, such as Kamala Harris (Q10853588).



For a person (human), you can add a property to specify to their gender identity, by specifying a value for their sex or gender. As of February 2021, Wikidata has has one property to represent both gender and sex of a human, P21 - sex or gender.

What is its history?
‘Humaniki’ is the merging of two previous Wikimedia data tools for diversity-focused editors - Wikidata Human Gender Indicators (WHGI) and Denelezh. Both of these previous projects enabled statistics about the biography gender gap in Wikimedia projects, but needed extra work to make those insights actionable for editors. This WMF-grant-funded project does that work by making available features identified from a participatory co-designing activities conducted with the editor community.

Do similar tools exist?
Several tools providing statistics about the content of Wikimedia projects exist (sorted here by year of release): gender gap by Wikimedia project gender gap by occupation gender gap by North-South divide
 * 2018 — WDCM Biases Dashboard, tracks the usage of Wikidata items (in how many pages each item is used in Wikimedia projects, not the number of sitelinks):

Who are the authors and what are the licenses of the images and logos used on humaniki?
Images and logos used on Humaniki have various authors and licenses. The full list is available on the Miscellaneous Credits File on the git repository of the project.

What is the roadmap?
(The project is open source. You can help us build this tool by working on any of the open tasks listed below)


 * 1) Alpha stage (completed)
 * 2) Merge capabilities of WHGI and Denelezh
 * 3) Customizable Visualizations by enabling filter search
 * 4) Provide screenshot ready visualizations with the meta data information listed in the view that makes the tool presentation ready
 * 5) Beta stage:
 * 6) Provide data completeness information, e.g. number of articles about humans missing gender, and other demographics labels T275330
 * 7) Internationalization to adapt software to different languages T274079
 * 8) Gender gap evolution trends T275332
 * 9) Generate occupation metrics T270046
 * 10) Beyond:
 * 11) Support list-making T274085
 * 12) Enabling third party applications via data API T275328
 * 13) Anomaly detection T274088
 * 14) Maximizing the scope of currently collected gender gap data T275331
 * 15) Collecting other attributes of gender gap data (article quality, media files, others) T275339

How to use the API?
https://humaniki.wmcloud.org/api/v1/gender/gap/latest/gte_one_sitelink/properties?countries=all&label_lang=en