  The amount of Adaptive Optics (AO) telemetry generated by VIS/NIR
ground-based observatories is ever greater, leading to a growing need for a
standardised data exchange format to support performance analysis and AO
research and development activities that involve large-scale telemetry mining,
processing, and curation. This paper introduces the Adaptive Optics Telemetry
(AOT) data exchange format as a standard for sharing AO telemetry from
visible/infrared ground-based observatories. AOT is based on the Flexible Image
Transport System (FITS) and aims to provide unambiguous and consistent data
access across various systems and configurations, including natural and
single/multiple laser guide-star AO systems. We designed AOT focused on two key
use cases: atmospheric turbulence parameter estimation and point-spread
function reconstruction (PSF-R). We prototyped and tested the design using
existing AO telemetry datasets from multiple systems: single conjugate with
natural and laser guide stars, tomographic systems with multi-channel wavefront
sensors, single and multi wavefront correctors in systems featuring either a
Shack-Hartmann or Pyramid as main wavefront sensors. The AOT file structure has
been thoroughly defined, specifying data fields, descriptions, data types,
units, and expected dimensions. To support this format, we have developed a
Python package that enables data conversion, reading, writing and exploration
of AOT files, which has been made publicly available and compatible with a
general-purpose Python package manager. We demonstrate the flexibility of the
AOT format by packaging data from five different instruments, installed on
different telescopes.
