#OpenLineage

Live, measured metrics for the hashtag #OpenLineage from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #openlineage

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$10.85/ year · 11-character #name
Claim #openlineage — $10.85/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
6
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 6
0
Avg reactions / post
Mastodon · last 6

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 00:29 UTC
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27
0
07-28

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 00:29 UTC

No related tags with measured usage found for #openlineage.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 00:29 UTC

Everything below is measured over the latest 6 public posts (spanning ~25223 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (5) · German (1)

Avg boosts / post: 0.8

Top of the latest posts

  • TIL: #OpenLineage, an open framework for data lineage collection and analysis https://openlineage.io/getting-started

    Nicolas Fränkel 🇪🇺🇺🇦🇬🇪@[email protected]♥ 0↻ 12024-06-08 09:05 UTCView post →

  • @davidculley that’s a conundrum I’ve been going through myself lately. Those of us who actually enjoy to solve problems, build solutions and automate things through software would also like to do it for a living, as engineering jobs have be

    Fabio Manganiello@[email protected]♥ 0↻ 02024-04-29 10:11 UTCView post →

  • @Lobrien a good read that outlines some of the challenges towards transparency/explainability of ML models. IMHO these problems can be fit into three categories: What data the model was trained on. Why a certain model with a certain archite

    Fabio Manganiello@[email protected]♥ 0↻ 02024-03-29 23:02 UTCView post →

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/openlineage