Data from my project the Wikidata Human Gender Indicators has started to be cited in the press (BBC, Bloomberg), which is a large dose of validation. Traffic to the data visualizations increased 500% on the day of the BBC publication to 1,000 views/day, which inspires confidence. Moreover, Wikimedia Foundation's Grants team—who funded WHGI—praised the project in their year-end report, saying:
Grants for research and tools (such as WHGI) - which minimally contribute to the targets of people or articles - have been extremely valuable in improving our understanding of the gender gap and how or why it manifests.
Among the uses I've seen online, the most reported statistic seems to be the progression of the female ratio of biographies in English Wikipedia: increasing to 16.78% by end of 2016 from approximately 15% in the two years we've been measuring. Seeing this interest, in the future I would plan to build better longitudinal visualizations. So we might see exactly how this statistic (and all others) have changed week-on-week throughout WHGI's history. Additionally, using anomaly detection to automatically call out large spikes and drops in Wikidata, would be a good service to the community. I hope in 2017 I'll have some time to roll-out more advanced analytics in store for measuring Wikipedia's systemic biases.