Gaia Data Release 1: Catalogue validation

TL;DR

The paper details the validation process of Gaia Data Release 1, assessing its accuracy, coverage, and limitations through various tests to ensure data quality for scientific use.

Contribution

It introduces dedicated validation methods for Gaia DR1, analyzing its content and quality, and identifies limitations for optimal scientific exploitation.

Findings

Gaia DR1 is the most precise all-sky astrometric catalogue to date.

Validation confirms high data quality but reveals limitations in completeness and accuracy.

Multiple tests assess properties of different stellar populations and data reliability.

Abstract

Before the publication of the Gaia Catalogue, the contents of the first data release have undergone multiple dedicated validation tests. These tests aim at analysing in-depth the Catalogue content to detect anomalies, individual problems in specific objects or in overall statistical properties, either to filter them before the public release, or to describe the different caveats of the release for an optimal exploitation of the data. Dedicated methods using either Gaia internal data, external catalogues or models have been developed for the validation processes. They are testing normal stars as well as various populations like open or globular clusters, double stars, variable stars, quasars. Properties of coverage, accuracy and precision of the data are provided by the numerous tests presented here and jointly analysed to assess the data release content. This independent validation confirms the quality of the published data, Gaia DR1 being the most precise all-sky astrometric and photometric catalogue to-date. However, several limitations in terms of completeness, astrometric and photometric quality are identified and described. Figures describing the relevant properties of the release are shown and the testing activities carried out validating the user interfaces are also described. A particular emphasis is made on the statistical use of the data in scientific exploitation.