Global Data and Insights/Movement Data/Equity Landscape/Frequently Asked Questions

Frequently Asked Questions

Using the dashboard

How do I sign up to pilot the data and dashboard?

If you are a representative of a Wikimedia group or committee responsible for movement strategy from grants, to affiliates, to movement governance we are looking to consult with you soon! Please reach out on the central talk page.

How do I get started using the dashboard?

Key stakeholders currently piloting the dashboard in advance of its public release can start exploring the data and the visualizations using the “Explore” tab on the header. We also have some specific documentation for answering key use-case questions outlined in the onboarding guide.

How do I report a bug?

If you want to report a potential error or a bug with the data or dashboard, please report on Phabricator (learn more about Phabricator).

How do I share feedback?

You can share your thoughts publicly on the talk pages of the pilot sub-portal or privately, via google form. We ask that pilot participants also share feedback privately so that we can understand your experience with the data and exploration studio better. For this, we have a google form survey available within the pilot experience. Collection of the dashboard experience survey will be expanded more broadly for the full public release. The private feedback form data use and storage and governance follows our privacy statement posted on the Foundation wiki. If you would like to share other feedback more directly, feel free to message the project team. Lead Strategist: JAnstee (WMF), Data Analyst: KCVelega (WMF), Data Engineer: NMaphophe (WMF)

About the data

What is the purpose of the dashboard?

Two of the key recommendations from the Movement Strategy process are to Ensure Equity in Decision-making and Evaluate, Iterate, and Adapt. By 2030, this will enable Wikimedia to become the essential infrastructure of the ecosystem of free knowledge, and anyone who shares our vision will be able to join us. To support these priorities, and to ensure equity in movement- or regional-level decision making, we need to consistently measure, evaluate, and report data that will help us understand not only the inequalities and diversity across the movement, but also the bounds of our movement ecosystem.

Many of our questions about our communities ask who and where our community members are; historically we have only been able to examine data by Wikimedia project or special data collection event. To understand the context of movement organizing, we must understand the “where” geographically as well. Of course, thematic and language areas intersect these geographic spaces where our communities exist and grow.

Some of the questions that the dashboard will enable us to understand are:

Who is part of our movement?
How are people getting involved?
What are our fastest growing communities across various domains?
Which Wikimedia projects and communities are keeping up or falling behind the global infrastructure gains?
How equitable are we in supporting emerging communities?

All of these exploratory questions can be answered with the help of the dashboard, with a geographical lens.

As the dashboard tracks various domains of the Wikimedia ecosystem combined with external social and economic indicators, year over year, it is intended to serve as a tool for decision-making that involves identity opportunities for growth, investments for community development, measuring equity, and also evaluating our progress.

How do I interpret rank scores?

The rank scores are comparative in nature. The numbers presented are average percentage ranks ranging from 0 to 10. A value of 0 indicates a country or region is at the least possible rank, whereas 10 indicates the highest possible rank for a metric.

For example, if a country haves a metric of value of 4, it indicates that the country is at the 40th percentile of the distribution for the metric. This can be interpreted as: the country ranks better than 40% of the countries for the metric, or alternatively, the country ranks lower than 60% (100 - 40) of the countries for the metric.

How are the percentile ranks calculated?

A percentile rank for each metric is based on the average of several input signal measures. For example, for calculating Reader Presence, average monthly pageviews and unique devices are considered. A detailed overview of measures used for each metric is available on the Metrics Schema.

How frequently is the data updated?

The data on the dashboard is within scope of a calendar year (i.e. January 1 to December 31). Each year, the metrics based on the last calendar year, will be updated in January. However, currently as it is the first launch of the dashboard, the 2022 update will be completed by Apr 30, 2023.

How is the dashboard different from Wikistats?

The metrics provided by Wikistats are primarily product-related domains, across reading (pageviews & devices), contributing (editors & edits) and content (bytes & media). The metrics are presented at project level in their absolute form.

The metrics provided by Equity Landscape are measures based on both product-related domains (as described above) and community, movement organizing related domains (such as grants, affiliates, programs) along with social and economic indicators such as (internet population, mobile connectivity, freedom index, and GDP-PPP). The metrics are presented at a geographic level, in a comparative format using percent ranks.

For example, on Wikistats, you would be able to get the data for number pageviews received by Wikidata in a month, and on Equity Landscape, you can explore the presence of editors in Brazil, compared to another country, or an encompassing region such as South America.

Why are some countries missing data?

There might be two reasons for missing data:

Due to legal and security reasons, we don’t publish the data of countries on the data protection list.
As we use a range of sources (both internal and external) to gather data for the input metrics, for certain countries and certain years, the data may not be available at the source. If we are not confident with the supplemental data, there might be a data gap.