astañeda et al. 2015) updates core calibrations, such as the PSF model, and improves the source to observation cross-matching.

Subsequently it repeats all higher level functions of IDT (in particular the estimation of astrometric image parameters) on the (unchanging) raw astrometric and photometric observations, using better geometric calibrations, attitude and astrometric source parameters from AGIS, and source colours from the photometric pipeline.

The results of the updated crossmatch form the basis of the source list used by all the DPAC processing systems, including the daily systems described above.

Astrometric Global Iterative Solution (AGIS) The astrometry for each source is derived within this system, which is described in Lindegren et al. (2012), with the specifics for the processing for Gaia Data Release 1 (Gaia DR1) described in Lindegren et al. (2016).

AGIS also produces the attitude model for Gaia, the geometric calibration of the SM and AF parts of the focal plane, and the calibration of a number of global parameters, such as the value and time evolution of the basic angle (for the first data release, the basic angle variations are obtained from the BAM measurements; Lindegren et al. 2016).

Global Sphere Reconstruction (AVU-GSR) The astrometric verification unit provides an independent method, the global sphere reconstruction, for solving for the astrometry from the raw image locations.

The GSR system will produce astrometry for the so-called primary sources in the AGIS solution (cf. Lindegren et al. 2012).

These results will then be compared to the AGIS astrometry as a strong form of quality control on the main DPAC astrometric outputs that are derived from AGIS.

More details on the GSR can be found in Vecchiato et al. (2012).

Photometric pipeline This system processes the photometric data from the SM, AF, BP, and RP parts of the focal plane.

The source fluxes in the G band, derived from the AF images by the IDU (or for the most recently received data, the IDT) process, are turned into calibrated epoch photometry in the G band.

The integrated fluxes measured from the BP- and RPprism spectra are also turned into calibrated epoch photometry (GBP and GRP; Sect. 8.2), while the spectra themselves are wavelength and flux calibrated.

All photometric data are calibrated against standard stars for which high-quality, groundbased spectro-photometry is available (Pancino et al. 2012).

The calibration process delivers the actual photometric passbands and the physical flux and wavelength scales.

The photometric processing for Gaia DR1 is described in Carrasco et al. (2016); Riello et al. (2016); Evans et al. (2016); van Leeuwen et al. (2016).

RVS pipeline The processing of the data from the RVS instrument is carried out within the RVS pipeline.

The pipeline takes care of the basic spectroscopic calibrations, such as the wavelength scale, geometric calibration for the RVS focal plane, and the treatment of straylight and charge-transferinefficiency effects.

The calibrations are subsequently used to stack the noise-dominated transit spectra of faint objects and derive mission-average radial velocities through crosscorrelation techniques (Sect. 8.3; David et al. 2014).

For the brightest subset, epoch spectra and epoch radial velocities will be available.

The iterations between calibrations and spectra and source parameters is performed entirely within the RVS pipeline (Katz et al. 2011).

The above processing steps provide the basic data needed for further analysis and improvement of the astrometric, photometric, and spectroscopic results from Gaia.

For example, AGIS treats all sources as point sources and will thus produce suboptimal astrometric solutions for astrometric binaries.

Likewise, the alignment of the Gaia reference frame to the ICRF relies on a high-quality selection of QSOs from the Gaia data itself, which will include many previously unknown QSOs from poorly surveyed areas of the sky.

AGIS itself does not have the means to decide whether or not a source is a QSO.

Such a selection requires further analysis of the Gaia astrometry and photometry combined.

The DPAC therefore also carries out a number of data analysis tasks that, on the one hand, provide higher level scientific data products (such as source astrophysical parameters or variable star characterisation) and, on the other hand, serve to refine the astrometric, photometric, and spectroscopic processing (e.g. by properly treating binaries or providing a clean selection of QSOs for reference-frame alignment).