{"slug": "timenet-open-source-data-infrastructure-for-temporal-foundation-models", "title": "TimeNet: Open-source data infrastructure for Temporal Foundation Models", "summary": "OpenTSLM released TimeNet, an MIT-licensed, pre-release open-source data infrastructure project that gives time-series datasets a single storage format, TimeF, and one API to find, build, download and load them. TimeNet requires Python 3.11 or newer and ships as two packages — `timenet` (the TimeF model, reader, writer, registries, SDK and consumer CLI) and `timenet-connectors` (dataset connectors and the `timenet-build` producer CLI) — with each TimeF version containing a `manifest.json`, a `control.duckdb` hierarchy store, and a Parquet or Zarr values plane. The project warns its public API and the TimeF format can change before 1.0, and notes its MIT license covers the code but not the datasets connectors fetch, which keep their upstream licenses and access terms.", "body_md": "*Find, build, and load time-series datasets through one shared format.*\n\nNote\n\nTimeNet is a pre-release project. Its public API and the TimeF format can change before 1.0.\n\nTime-series datasets use many incompatible layouts. TimeF gives them one storage format. TimeNet provides one API to find, build, download, and load them.\n\nTimeNet handles the data layer. Model training, inference, and evaluation stay in your chosen framework.\n\n**TimeNet Online Hackathon is live.** Pick a time-series problem, onboard a dataset in TimeNet format, then train or fine-tune a Temporal AI Model (e.g. [OpenTSLM](https://github.com/OpenTSLM/OpenTSLM)) to explore what it can do. Choose any use case, from forecasting and classification to explanation, reasoning and beyond.\n\n**Register here:** [challenge.timenet.ai](https://challenge.timenet.ai/)\n\nTimeNet needs Python 3.11 or newer.\n\n```\nuv add 'timenet[cli]'\nuv tool install timenet-connectors\ntimenet-build build timenet/hello-world\n```\n\nThe build lands in the local registry at `~/.timenet/registry/timenet/hello-world/1.0.0/`. Load it\nwith Python:\n\n``` python\nfrom timenet import TimeNet\n\ndataset = TimeNet().load(\"timenet/hello-world@1.0.0\")\ndataset.describe()\n\nsignal = dataset.records[0].signals[0]\nvalues = signal.to_numpy()\n```\n\n`TimeNet()` reads the local registry first, and the local registry holds this exact version.\nSo the example works without registry credentials or network access.\n\nSee the [Get started guide](https://docs.timenet.ai/get-started.html) for installation options and a\nlonger example.\n\nA connector converts a raw source into a TimeF version. The version contains:\n\n- `manifest.json` , which identifies the dataset and lists its files\n- `control.duckdb` , which stores the hierarchy and relationships\n- a Parquet or Zarr values plane, which stores Signal values\n\nA registry stores immutable TimeF versions. The client reads a version without importing its connector.\n\nThe repository is a [uv](https://docs.astral.sh/uv/) workspace with two packages:\n\n| Package | Purpose | \n|---|---|\n| `timenet` | The TimeF model, reader, writer, registries, SDK, and consumer CLI. | \n| `timenet-connectors` | Dataset connectors and the `timenet-build` producer CLI. | \n\nRead the [architecture guide](https://docs.timenet.ai/architecture.html) for the complete design.\n\nTimeNet uses the [MIT License](https://github.com/OpenTSLM/TimeNet/blob/main/LICENSE).\n\nThis license covers the TimeNet code, not the datasets that connectors fetch. Each dataset keeps\nits upstream license and access terms. Read the\n[dataset licensing guide](https://docs.timenet.ai/catalog/licensing.html) before redistribution.", "url": "https://wpnews.pro/news/timenet-open-source-data-infrastructure-for-temporal-foundation-models", "canonical_source": "https://github.com/OpenTSLM/TimeNet", "published_at": "2026-11-10 17:16:09+00:00", "updated_at": "2026-11-11 18:24:48.059357+00:00", "lang": "en", "topics": ["machine-learning", "ai-research", "developer-tools", "ai-tools"], "entities": ["TimeNet", "TimeF", "OpenTSLM", "timenet-connectors", "timenet-build", "DuckDB", "Parquet", "Zarr"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/timenet-open-source-data-infrastructure-for-temporal-foundation-models", "markdown": "https://wpnews.pro/news/timenet-open-source-data-infrastructure-for-temporal-foundation-models.md", "text": "https://wpnews.pro/news/timenet-open-source-data-infrastructure-for-temporal-foundation-models.txt", "jsonld": "https://wpnews.pro/news/timenet-open-source-data-infrastructure-for-temporal-foundation-models.jsonld"}}