# open data sets

Published articles for open data sets.

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## GHarchive data has become unreliable for measuring GitHub activity

DevFeed: [GHarchive data has become unreliable for measuring GitHub activity](<https://devfeed.tech/articles/how-much-should-you-trust-your-oss-data-34319.md>)

Original publisher: [Read original article](<http://opensource.googleblog.com/2026/09/how-much-should-you-trust-your-oss-data.html>)

Author: KD (noreply@blogger.com)

Published: 2026-09-03T16:00:00Z

Content type: opinion

Language: en

Sources: [Google Open Source Blog](<https://devfeed.tech/sources/google-open-source-blog.md>)

Topics: [data](<https://devfeed.tech/topics/data.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [Crawler](<https://devfeed.tech/topics/crawler.md>), [GitHub API](<https://devfeed.tech/topics/github-api.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [GraphQL](<https://devfeed.tech/topics/graphql.md>)

Tags: [collect](<https://devfeed.tech/tags/collect.md>), [data](<https://devfeed.tech/tags/data.md>), [dataset](<https://devfeed.tech/tags/dataset.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [github](<https://devfeed.tech/tags/github.md>), [google](<https://devfeed.tech/tags/google.md>), [google-open-source](<https://devfeed.tech/tags/google-open-source.md>), [graphql](<https://devfeed.tech/tags/graphql.md>), [open-data-sets](<https://devfeed.tech/tags/open-data-sets.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [oss](<https://devfeed.tech/tags/oss.md>), [pipeline](<https://devfeed.tech/tags/pipeline.md>), [pull-requests](<https://devfeed.tech/tags/pull-requests.md>), [retention](<https://devfeed.tech/tags/retention.md>), [stream](<https://devfeed.tech/tags/stream.md>), [volume](<https://devfeed.tech/tags/volume.md>)

### AI overview

This article examines the reliability of open source data, focusing on GHarchive's coverage of GitHub events. It argues that GHarchive should not be used for real-time or volume-based metrics because event retention has declined and some activity is omitted by the GitHub Event stream and API limitations.

### Source excerpt

by Sophia Vargas, Google Open Source & Andrew Nesbitt, Ecosyste.ms Every second, open source contribution quietly shapes the software we rely on, and yet our view of this open ecosystem is surprisingly opaque. Open source development is performed in public spaces -- we can see the commits, issues and comments, the APIs and endpoints are free to use -- the logs are just sitting there, so why can't we just collect all of the data? ...Said every researcher, everywhere. However in most cases of open source related data, we are only looking at part of the whole. Why am I writing this post? Because many of us (including many business decision-makers) are too comfortable with unsubstantiated data. We've gotten used to it. Our models assume that it's smelly and we adjust the logic and weights to compromise. When it comes to open source, our confidence is even lower, even though our resulting decisions can directly impact individuals whom we collectively depend on. Let's consider one of my favorite datasets: GHarchive. Started as a hobby project in 2011, this crawler has amassed more than 15 years of event data from GitHub. While this source provides a historical record of open source development on GitHub, as a real-time or comprehensive source of metrics, it's unreliable and should not be a source for volume-based metrics. In 2025, GHarchive captured 14% fewer events than in 2024, despite steady growth in platform adoption. Since 2025, we estimate that data retention in GHarchive has fallen to ~50% and in 2026 it may be as low as 20% for some event types (see figure below). Prior to 2025, you could make the general assumption that the majority of events would be represented in this pipeline. Since 2025, we must now assume we may be missing at least half of events and possibly more -- not to mention all of the additional activity that's left out of the event API (see GitHub's GraphQL API.) The crawler logic behind this dataset is simple: give me all the events from the GitHub Ev