Crowdsourced data projects turn contributions from volunteers, observers, editors, and local users into large public information resources. The figures below show the scale of that work across encyclopedic knowledge, mapping, air-quality monitoring, biodiversity observation, and crisis reporting. Measurement periods vary by source, so each statistic is identified by its date or reporting period.
Contents
- Wikipedia: volunteer knowledge at global scale
- OpenStreetMap: mapping through recurring edits
- OpenAQ: shared air-quality information
- iNaturalist: observations and identification
- City Nature Challenge participation
- Ushahidi and crowdsourced reporting
Wikipedia: volunteer knowledge at global scale
Wikipedia illustrates how a distributed editor community can create and maintain a multilingual reference work. The [Wikipedia year in review 2024] reports nearly 260,000 editors worldwide. During 2024, those contributors made 98,222,407 changes, equivalent to 342 edits per minute globally in the same review. The review also records 4,104,852,969 bytes added to English Wikipedia during 2024.
The audience is similarly international. English Wikipedia reached 989 million unique devices per month, according to the [Wikipedia year in review 2024]. Readers spent 2.9 billion hours reading English Wikipedia, while reading across all languages totaled 5.8 billion hours. The same source describes Wikipedia as covering more than 300 languages and counting. These are different measures: devices, hours, and language coverage should not be treated as interchangeable indicators of audience size.
The [Wikimedia Foundation 2024–2025 Annual Report] gives a closely related snapshot. It reports 15 billion Wikipedia views every month, 66 million Wikipedia articles, 324 edits every minute, and 250,000 volunteer editors around the world. It also identifies 185 Wikimedia affiliates. The two Wikipedia sources use different reporting contexts and slightly different figures for editors and edits, so the values are best read as source-specific snapshots rather than combined totals.
| Wikipedia measure | Reported figure | Period or context | Source label |
|---|---|---|---|
| Worldwide editors | Nearly 260,000 | 2024 review | Wikipedia year in review 2024 |
| Changes made | 98,222,407 | 2024 | Wikipedia year in review 2024 |
| English Wikipedia devices | 989 million unique devices per month | 2024 review | Wikipedia year in review 2024 |
| Wikipedia views | 15 billion per month | 2024–2025 annual report | Wikimedia Foundation 2024–2025 Annual Report |
| Wikipedia articles | 66 million | 2024–2025 annual report | Wikimedia Foundation 2024–2025 Annual Report |
Together, these measures show several layers of crowdsourced data: people contributing changes, the accumulated information being maintained, and the public using that information. They also show why a single headline number cannot describe the whole system.
OpenStreetMap: mapping through recurring edits
OpenStreetMap provides a long-running record of collaborative geographic data creation. [OpenStreetMap Stats] reports more than ten million registered users, including 10 million registered users in 2025-Q2. In that quarter, the project had 2.25 million different user contributors. The distinction matters: registered users represent the account base, while different contributors represent participation during the stated quarter.
The database reached 10 billion nodes on 2025-08-12, according to [OpenStreetMap Stats]. The same source reports approximately 4 million map changes per day in 2021-Q4. A later [OpenStreetMap relation page] reports more than 14 million relations in January 2026. Nodes, changes, and relations describe different parts of the mapping system and should not be added together.
OpenStreetMap’s changeset history shows how activity developed over time:
| Year | Changesets |
|---|---|
| 2005 | 1,413 |
| 2006 | 16,706 |
| 2007 | 138,132 |
| 2008 | 505,200 |
| 2009 | 2,842,911 |
| 2010 | 3,319,313 |
| 2011 | 3,433,765 |
| 2012 | 4,223,843 |
| 2013 | 5,254,565 |
| 2014 | 8,079,024 |
| 2015 | 8,454,489 |
| 2016 | 8,522,134 |
| 2017 | 10,248,363 |
| 2018 | 10,855,892 |
| 2019 | 13,146,959 |
| 2020 | 17,682,667 |
| 2021 | 18,870,506 |
| 2022 | 15,110,467 |
| 2023 | 15,013,279 |
| 2024 | 15,101,460 |
The [OpenStreetMap changeset history] records a rise from 1,413 changesets in 2005 to 18,870,506 in 2021. It then records 15,110,467 in 2022, 15,013,279 in 2023, and 15,101,460 in 2024. Those annual counts document changing activity levels; they do not by themselves measure the accuracy, geographic balance, or usefulness of individual map features.
OpenAQ: shared air-quality information
OpenAQ shows how crowdsourced and shared environmental data can support scientific and public uses. As of September 2025, [OpenAQ Ten Years] reported more than 2 billion data points, 20,700 total locations, and coverage in 134 countries. The same source reported an average of 14 new scientific and media uses each month.
The research footprint included 553 scientific and technical publications and proceedings citing OpenAQ as of September 2025. OpenAQ also counted 2,043 locations in low- and middle-income countries. Eight companies were then facilitating data sharing with OpenAQ. These figures describe the network’s scale, reach, and reuse; they do not establish that every location has the same monitoring frequency or data quality.
The [OpenAQ Publications] assessment for 2024 provides a different view of global coverage. It found that 36% of countries were not currently monitoring air quality. Nearly one billion people lived in those countries. The same assessment found that barely over one-quarter of countries provided full and easy public access to maximally useful air-quality data.
The contrast is informative. A shared platform can contain more than 2 billion data points and still exist within a world where monitoring and public access remain incomplete. The OpenAQ figures therefore help separate platform capacity from universal coverage: a large dataset does not mean that every country, population, or pollutant is represented equally.
iNaturalist: observations and identification
iNaturalist records crowdsourced biodiversity observations through several kinds of participation. In the [iNaturalist 2024 City Nature Challenge snapshot], there were 4,128 observations, 1,015 species, 297 observers, 33 project members, and 305 identifiers. The 2023 City Nature Challenge figures were 2,976 observations, 811 species, 223 observers, 44 project members, and 259 identifiers.
The roles are not identical. Observers submit records, identifiers help determine what those records show, and project members are counted separately. Comparing the categories without preserving those definitions would blur different forms of contribution.
The [iNaturalist Personal Bioblitz 2024] recorded 53,985 observations, 9,291 species seen, and 11,550 scientific names, or taxa, seen. It had 99 participants. The top observer contributed 9,308 observations, followed by 4,866 for the second-ranked observer, 4,479 for the third, 3,873 for the fourth, and 3,428 for the fifth.
The same Personal Bioblitz source reports species totals for its top five species observers: 1,780, 1,579, 1,341, 1,232, and 1,174 species, respectively. It also reports that 54 observers saw a species not reported by anyone else. There were 5,329 unique observations, described as about 10% of all observations, and about 46% of species were seen only once by a single observer.
These figures show both concentration and discovery. A small group of highly active participants contributed thousands of observations, while one-time or single-observer records added distinct species information. The percentages are reported descriptions from the source and are not recalculated here.
City Nature Challenge participation
The [iNaturalist 2024 global City Nature Challenge figures] show a worldwide event with 2,436,000 observations, more than 65,600 species, more than 3,940 rare, endangered, or threatened species, 83,500 participants, and 690 participating cities. These measures cover observations, biological variety, participation, and geographic participation at the global event level.
A local snapshot from the same iNaturalist reporting gives a more focused view. The 2024 Chicagoland City Nature Challenge included 11,100 observations and 1,670 species. The global totals and Chicagoland totals should remain separate: one describes the event worldwide, while the other describes a regional contribution.
The year-to-year City Nature Challenge snapshots also show why dates matter. The 2024 snapshot listed 4,128 observations, 1,015 species, and 297 observers, while the 2023 snapshot listed 2,976 observations, 811 species, and 223 observers. Because these figures are tied to the stated snapshots, they should not be generalized into a universal annual trend for every participating place.
Ushahidi and crowdsourced reporting
Ushahidi applies crowdsourced reporting to events and public-interest situations. The [Ushahidi Election Toolkit] states that Ushahidi has been used more than 200,000 times, in over 160 countries, and has crowdsourced more than 50 million reports.
These three figures describe reach, geography, and report volume. “Used more than 200,000 times” is a platform-use measure, while “more than 50 million reports” is a contribution measure. Neither figure specifies a single year in the supplied source, so they should be treated as cumulative source-reported totals rather than as a 2024, 2025, or 2026 annual count.
Across the examples, crowdsourced data is measured in several ways: edits and changesets for collaborative knowledge and maps; nodes, relations, and locations for structured geographic or environmental resources; observations and species for biodiversity; and reports and countries for civic response. Keeping each unit, source label, geography, and measurement period attached to its statistic is essential when comparing projects with different purposes.