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TimeNet: Open-source data infrastructure for Temporal Foundation Models

·2026.11.11 02:16

Key point

The pre-release project provides a unified TimeF format and API to standardize the discovery, building, and loading of time-series datasets for AI models.

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Details

  • TimeNet is an open-source, MIT-licensed data infrastructure project designed to solve the incompatibility of time-series dataset layouts by introducing the TimeF storage format.
  • The system separates the data layer from model training, allowing developers to use a single API to find, build, download, and load datasets while keeping inference and evaluation in their preferred frameworks.
  • TimeF versions consist of a manifest.json for identification, a control.duckdb for hierarchy and relationships, and a Parquet or Zarr values plane for signal data.
  • The project is currently in pre-release status, meaning its public API and the TimeF format are subject to change before the 1.0 release.
  • An online hackathon is active, encouraging users to onboard datasets into TimeNet format and train or fine-tune Temporal AI Models like OpenTSLM for forecasting, classification, and reasoning tasks.
open-sourcetime-seriesdata-infrastructuretemporal-aidataset-management
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