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Data Hub receives data from data sources — dataloggers, building automation systems, and public APIs. This section has one page per source; this overview explains how sources work in general, what each source’s documentation status means, and how credentials are handled across all of them. Use the sidebar to open the page for a specific source.

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Categories of data source

Environmental & Weather APIs

Public APIs providing air quality, weather, and regional observational data.

Building & Energy Systems

Building automation systems and dataloggers that push metered readings from a facility.

Generic Ingestion

A file-upload endpoint that accepts data from any source able to produce a properly formatted file.

In development

Native IoT integrations still in the draft-spec stage and not yet usable.

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Documentation status

Each data source page is documented at one of four levels, shown in a callout at the top of the page:

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Credential handling, across every data source

Never share upload tokens, API keys, or device login credentials in plain text over email, chat, or support tickets. If you suspect a credential has been exposed, rotate it immediately and notify the Data Hub team.
Credentials are never logged and never displayed again after initial entry. Different sources use different credential models — an upload token, OAuth-style credentials, a bearer token, or a device-side login that Data Hub never sees. See each source’s own page for specifics.

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Troubleshooting

Many device-based sources require the Data Hub team to manually assign your logger’s serial number to your organization before data appears. Confirm you’ve sent your serial number after completing device-side setup.
Check that you’re using your organization’s own subdomain in the upload URL (not a placeholder or another organization’s subdomain), that you’re using the protocol your source’s page specifies, and that any required token or header is current and correctly formatted.

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Next steps

Once a data source is connected and reporting variables:
  • Polling Intervals — whether that source has a configurable pull interval, and how data-reception status is surfaced per variable.
  • Derived Variables — calculate new metrics (e.g. combining two variables from different sources) from a formula rather than a data source.