GriddingMachine: A new database and software for sharing global datasets

Read the full story from the Climate Modeling Alliance.

GriddingMachine aims to minimize the effort involved in reusing data by

  • Collecting data from various sources,
  • Processing the data to a uniform format (NetCDF),
  • Storing the reprocessed data on public servers, and
  • Providing APIs to automatically download, manage, and read the data in multiple programming languages.

Each dataset is labeled with a unique tag that describes

  • Type of the dataset (e.g., leaf area index, biomass, etc.),
  • Spatial resolution (e.g., 5X means 0.2° × 0.2° grid),
  • Temporal resolution (e.g., 1Y means 1 year, 1M means 1 month),
  • Year of the data, and
  • Version of the data (from different publications).

Users can look up available dataset tags (and suggest new datasets) through our Github repository.

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