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We surveyed all 336 OONI Run v2 links, and three of them drive 72% of all measurements

OONI Run v2 usage census

Worldwide, OONI Run v2 has produced 14.17 million measurements, and just three lists account for 72% of them. The highest-volume lists all work the same way: each one targets a single censorship or blocking phenomenon, and a continuously-running measurement backend executes it on a schedule, accumulating data over time. We surveyed every Run v2 link to measure how concentrated this is, and to draw out what the pattern offers communities that want to run their own local connectivity observation.

OONI (the Open Observatory of Network Interference) is a global censorship-measurement project. Its mobile app, OONI Probe, runs through a list of websites and reports whether each one is reachable from where you are. OONI Run v2 lets anyone compose their own list of sites to watch, generate a link, and have others run that list with one tap in OONI Probe, with every result flowing into OONI's public dataset. You can define your own measurement targets without writing code, yet few people know the feature exists or have used it, which is exactly why we wanted to see how it is actually used.

What we did

We took a snapshot on 2026-06-01 and went through every live OONI Run v2 link, 336 of them, pulling each link's lifetime measurement count from OONI's public aggregation API1 and grouping them by list topic. Every figure below is based on that snapshot; the data source and caveats are at the end.

From the first link on 2024-04-24 to now, about 26 months, the whole world has created only 337 Run v2 links (one has been deleted; 336 remain). Creation spiked between October and December 2024 and has since held steady at 10 to 19 per month. 157 distinct authors took part, and 332 of the 336 use Web Connectivity, almost all of them testing website reachability.

  • New Run v2 links created per month {"description":"OONI Run v2 links created per month","data":{"values":[{"m":"2024-04","n":4},{"m":"2024-06","n":1},{"m":"2024-07","n":1},{"m":"2024-09","n":3},{"m":"2024-10","n":23},{"m":"2024-11","n":54},{"m":"2024-12","n":28},{"m":"2025-01","n":14},{"m":"2025-02","n":9},{"m":"2025-03","n":19},{"m":"2025-04","n":16},{"m":"2025-05","n":11},{"m":"2025-06","n":9},{"m":"2025-07","n":18},{"m":"2025-08","n":14},{"m":"2025-09","n":17},{"m":"2025-10","n":8},{"m":"2025-11","n":8},{"m":"2025-12","n":19},{"m":"2026-01","n":10},{"m":"2026-02","n":12},{"m":"2026-03","n":14},{"m":"2026-04","n":10},{"m":"2026-05","n":14}]},"mark":{"type":"bar","tooltip":true,"color":"#00aeff"},"encoding":{"x":{"field":"m","type":"ordinal","title":"Month","axis":{"labelAngle":-45}},"y":{"field":"n","type":"quantitative","title":"New links created"}}}

For a global censorship-observation tool, 337 links in two years is a small number. Going by creation count alone, it is easy to conclude that almost nobody uses Run v2. The usage data in the next section overturns that.

Usage is extremely concentrated, Gini 0.981

Adding up the lifetime measurements of all 336 links gives 14,171,627. The total is not small; the problem is how unevenly it is distributed. The Gini coefficient by measurement count is 0.981, almost at the 1.0 of complete inequality.

Why the Gini coefficient

The Gini coefficient was originally used to measure income inequality. It ranges from 0 to 1 and compresses the concentration of a whole distribution into a single number. 0 means perfectly even, with every link producing the same number of measurements. 1 means fully concentrated, with all measurements coming from a single link.

It fits here well, because each link's measurement count is a non-negative quantity and the question is exactly how concentrated all measurements are among a few links. Mathematically the Gini coefficient equals the area between the Lorenz curve and the diagonal (divided by the total area below the diagonal), so the closer the Lorenz curve below hugs the bottom edge, the closer the Gini coefficient is to 1. A value of 0.981 means the distribution is very close to the extreme where a handful of links take almost everything.

A single number does not show which links these are or what the long tail looks like, so we include both the Lorenz curve and a bucketed distribution to lay out the shape of the concentration.

  • Lorenz curve of measurement volume (the dashed line is perfect equality) {"description":"Lorenz curve of measurement volume across Run v2 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The Lorenz curve runs almost flat along the bottom and only shoots up at the very end. The 90% of links with the fewest measurements add up to just 0.93% of the total, and even the bottom 99% account for only 20.45%. The top 4 links take about 79.5%, and the single largest (DW's Global media, id 10006) is 46.5% on its own.

  • Which bucket each link's lifetime measurement count falls into {"description":"Distribution of lifetime measurement counts per link","data":{"values":[{"bucket":"= 0","links":112,"share":0.0,"order":0},{"bucket":"1–99","links":81,"share":0.0,"order":1},{"bucket":"100–999","links":73,"share":0.2,"order":2},{"bucket":"1k–9999","links":41,"share":1.0,"order":3},{"bucket":"10k–99k","links":15,"share":2.4,"order":4},{"bucket":"100k–999k","links":12,"share":28.0,"order":5},{"bucket":"1M+","links":2,"share":68.3,"order":6}]},"mark":{"type":"bar","tooltip":true,"color":"#0089bf"},"encoding":{"x":{"field":"bucket","type":"ordinal","sort":{"field":"order"},"title":"Lifetime measurements (bucket)","axis":{"labelAngle":-30}},"y":{"field":"links","type":"quantitative","title":"Links"},"tooltip":[{"field":"bucket","title":"Bucket"},{"field":"links","title":"Links"},{"field":"share","title":"% of all measurements"}]}}

At the other end of the tail, 112 of the 336 links (33%) have zero lifetime measurements, built and then barely run. 193 (57%) have fewer than 100, and the overall median is just 27. Most Run v2 links get created, run a few times, and stop.

Where the measurements concentrate

The concentration above only describes the shape of the distribution, not what the data is actually used for. Once the links are grouped by list topic, the most heavily-observed cohorts show a common way of working.

  • Share of all measurements by use case (orange is the anoni.net community) {"description":"Share of all measurements by use-case cohort","data":{"values":[{"group":"DW (international media)","share":72.4,"links":3,"measurements":10265315},{"group":"Spain / LaLiga blocking","share":10.8,"links":13,"measurements":1529544},{"group":"Venezuela / VeSinFiltro","share":6.5,"links":4,"measurements":925351},{"group":"Uruguay / UCU research","share":6.1,"links":49,"measurements":863016},{"group":"Long tail (other)","share":2.1,"links":199,"measurements":300815},{"group":"Thailand gov sites","share":1.7,"links":2,"measurements":239430},{"group":"OONI official","share":0.3,"links":59,"measurements":43385},{"group":"anoni.net (Taiwan)","share":0.0,"links":7,"measurements":4771}]},"mark":{"type":"bar","tooltip":true},"encoding":{"y":{"field":"group","type":"nominal","sort":"-x","title":null},"x":{"field":"share","type":"quantitative","title":"% of all measurements"},"color":{"condition":{"test":"datum.group == 'anoni.net (Taiwan)'","value":"#ef6c00"},"value":"#00aeff"},"tooltip":[{"field":"group","title":"Use case"},{"field":"links","title":"Links"},{"field":"measurements","title":"Measurements"},{"field":"share","title":"Share %"}]}}

Deutsche Welle (DW) uses 3 lists to continuously monitor the reachability of international media across many places, taking 72.4%. Spain's conexionsegura uses 13 lists to watch the piracy blocks ordered by the LaLiga football league, at 10.8%. Venezuela's vesinfiltro uses 4 lists to track local blocking, at 6.5%. Add Uruguay's UCU research team and an observer who has long tested Thai government websites. The most heavily-observed cohorts share a clear common thread: each list targets one specific censorship or blocking phenomenon, paired with a continuously-running measurement backend that watches it day after day. That is the underestimated way to use it.

Listing the top 15 links by measurement count makes the same pattern concrete.

link id Lifetime measurements List size Created Author List name
10006 6,589,070 223 2024-07-03 dw.com Global media
10005 3,093,765 91 2024-06-13 dw.com Selected (inter)national media
10236 856,036 167 2026-05-14 conexionsegura La Liga bloqueos.es
10158 734,627 4635 2025-04-03 ucu (UY) lista global final
10004 582,480 15 2024-12-11 dw.com Trusted International Media
10154 418,978 131 2025-03-26 vesinfiltro MagisTV y FlujoTV
10135 344,268 819 2025-04-16 conexionsegura Test Bloqueos LaLiga
10153 259,331 102 2025-03-24 vesinfiltro PriorityList
10143 210,078 134 2025-03-05 vesinfiltro VSF News y otros
10298 133,991 72 2026-05-04 Thailand observer Test Thai gov websites
10226 118,509 170 2025-09-15 conexionsegura Bloqueos LaLiga - Dominios
10235 109,276 293 2025-09-20 conexionsegura VE media http+https check
10214 105,439 67 2025-10-04 Thailand observer Test Thai gov websites
10114 102,096 256 2026-05-05 jiyul.org revi
10118 56,541 3044 2025-03-26 ucu (UY) LISTA GLOBAL

Long-term observation comes from a continuously-running backend, list size barely matters

An intuitive guess is that the more sites a list collects, the more data it produces. The data does not support that guess. Plotting each link's list size (number of inputs) against its lifetime measurements shows almost no relationship.

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The two extremes are clearest. UCU's id 10158 packed in 4,635 inputs (the largest on the network) for 734,627 lifetime measurements. DW's id 10004 has only 15 inputs yet 582,480. No matter how big a list gets, without a continuously-running backend to execute it the measurement count stays near 0, which means no observation is happening. What actually lets observation accumulate is whether there is a measurement infrastructure that runs the list every day; how many sites it collects matters far less.

anoni.net's own coordinates: the community is its own controlled experiment

The anoni.net community has built two Run v2 links, which happen to demonstrate the two patterns above. We lay both out, not just the better-performing one.

The first, id 10238, was built on 2025-09-15 with 7 inputs (anoni.net plus our own services: im, matrix, form, pad, search, cinny) and has run only 14 measurements in its lifetime. It sits with the majority: built but not run continuously. The second, id 10328, was built on 2026-05-15, expanded to 10 inputs, and this time paired with a self-operated vantage point that runs continuously. In half a month it accumulated 4,659 measurements, ranking 39th of 336, inside the top 12%.

Same community, same draft list of anoni.net's own services; the only difference between the two links is whether a continuously-running backend stands behind it. We do not dodge the other side either: 10328's share of the whole network is still near 0%. In such a long-tailed distribution, just running continuously for half a month already beats 297 links, which shows how many people miss the "run it continuously" threshold. The move from 10238 to 10328 is the record of the community crossing that threshold itself.

What it means for communities and OONI

For communities that want to run local connectivity observation, the census points in a clear direction. Run v2's value comes from a curated list aimed at a specific phenomenon plus a continuously-running measurement backend; missing either one drops you into the long tail. Opening more links by itself brings no data.

The same pattern applies to many topics. The DW, conexionsegura, and vesinfiltro cases above are three already-running examples: international media reachability, sports-piracy blocking, and local blocking. If you want to start, here are a few directions to consider.

  • Election observation: from before to after an election, continuously track the reachability of news media, candidate, and election-authority websites in a given region, recording any blocking or interference during the voting period, giving election observers and researchers an evidentiary time series.
  • Real-time observation of major events: during protests, strikes, disasters, or shutdowns, continuously test independent media, messaging services (Signal, Telegram), and help-and-information sites, to see in real time which are blocked and when.
  • Specific communities and issues: sites that are often blocked in some regions, such as LGBTQ+, religious minorities, women's rights, and human-rights organizations, observed longitudinally to accumulate evidence that research can cite.
  • Circumvention-tool availability: track the official sites and download endpoints of VPNs, Tor, bridges, and other circumvention tools, whether they are still reachable in a given place and when blocking begins, which is especially useful for groups helping local people stay connected.
  • Cross-border media and diaspora communities: the overseas media that diaspora communities rely on (for Chinese-language readers, for example RFA or Initium Media), observed for reachability differences across ASNs and changes over time.
  • Platform-level blocking events: when an app or service is suddenly blocked in a country, quickly build a list and observe across ASNs, measuring the scope and the start and end times of the block, turning a single event into analyzable data.

Pick a topic you care about most, list a dozen or so relevant sites, and have one vantage point run it every day; within a few weeks you will have your own reachability time series to analyze. For OONI and data-analysis partners: the aggregation API supports filtering by ooni_run_link_id, which makes a meta-analysis of the Run v2 ecosystem itself feasible. This report was produced exactly that way. The anoni.net community has written up this approach as a measurement-model proposal in issue #78; the call for feedback is still open, and we welcome discussion from the community and the OONI team.

Summary of the issue #78 measurement model

Issue #78 proposes a civic-internet-watch measurement model that splits the system into two layers.

  • List governance: the community maintains its own list of civil-society websites, with the single source of truth in the community's git repo. Inclusion criteria, consultation status, and sensitivity tiers are all decided by the community according to local context, and the git history is itself the record of list governance.
  • Measurement and data: using the standard Web Connectivity test, a Run v2 link generated from the list does the measuring. Volunteer phones and self-operated vantage points consume the same link and carry the same Run Link ID, and all results flow into OONI's public dataset, queryable via the OONI API and Explorer, citable by researchers, with no data lock-in.

List governance does not churn the shared Citizen Lab tw.csv, avoiding the breaks in long-term measurement time series that repeated edits to a shared list would cause. tw.csv is demoted from a required path to optional, additive feedback: only mature, non-sensitive organizations are fed back additively in exchange for the cross-platform baseline, while sensitive organizations stay in the community-managed list and Run v2 and never enter a public PR.

Data and caveats

This report's data is a snapshot taken on 2026-06-01, pulled link by link from OONI's public aggregation API1 (filtered by ooni_run_link_id). Measurement counts keep growing over time, so re-querying later yields slightly higher numbers, while the shape of the concentration stays stable. A few caveats before reading the figures.

  • Measurement counts come from the aggregation API's measurement_count, a point-in-time query as of 2026-06-01 that keeps growing.
  • The lifetime query spans 2024-01-01 to 2026-06-30, covering the whole history of Run v2.
  • A link with 0 measurements may be a test or draft, and does not necessarily mean "failure".
  • A link can be run by probes in any country; the use-case cohorts are inferred from list topic, not an official OONI label.
  • Full disclosure: the community's own two links (10238, 10328) are both included in the analysis and discussion; we did not cherry-pick the better-performing 10328.

  1. OONI API (aggregation endpoint) - OONI ↩↩