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Check the metadata reference for a complete list of metadata fields.

One of the main values of our work is the careful documentation that we provide along with our data and articles. In the context of data, we have created a metadata system in ETL that allows us to describe the data that we are working with.

In our data model there are various data objects (snapshots, datasets that contain tables with indicators, etc.), each of them with different types of metadata.

The metadata is ingested into ETL in the form of YAML files, which live next to the scripts. Metadata can be ingested at any ETL step to tweak, change and add new metadata. However, the most standard places to have metadata defined are in Snapshot and in Garden.

Questions about the metadata?

If you have questions about the metadata, you can share these in our discussion. This greatly helps us keep track of the questions and answers, and makes it easier for others to find answers to similar questions.

Additionally, we have added a FAQs section to this entry.


In Snapshot we define metadata attributes for the data source product. We make sure that all the different files, datasets and publications that we ingest to our system are properly documented. This includes making sure that these have licenses, descriptions, titles and other information assigned.


In Garden we focus on the metadata of the finished product. After all necessary ETL steps, the initial source file (or files) has (or have) been transformed into a curated dataset. This dataset may have multiple tables, each of them with various indicators.

In this step we add metadata that describes this dataset, these tables and these indicators. We focuss on the output of ETL (and not the input, i.e. the origin). This means, for instance, adding details on the processing that a specific indicator has undergone (or how it has been created), how do we want these indicators to be called, etc.

Propagation of metadata

We have built a logic into ETL to automatically propagate metadata fields forward (Snapshot → Meadow → Garden → Grapher).

Learn more

Using metadata

Metadata and Data pages

We automatically create data pages from an indicator using its metadata fields. Learn how the metadata fields are mapped to a data page with our demo app.

Try the demo

Other uses

Users can consume the metadata programmatically using the owid-catalog.

Updating metadata using ChatGPT

We have developed a tool, etl metadata-upgrade, that uses OpenAI's GPT model to help us update metadata files. This tool supports two types of metadata files: 'snapshot' and 'grapher'. It reads the metadata file, generates an updated version, and saves it either in the specified output directory or overwrites the original file.