  With Gaia Data Release 2, the astronomical community is entering a new era of
multidimensional surveys of the Milky Way. This new phase-space view of our
Galaxy demands new tools for comparing observations to simulations of
Milky-Way-mass galaxies in a cosmological context, to test the physics of both
dark matter and galaxy formation. We present ananke, a framework for generating
synthetic phase-space surveys from high-resolution baryonic simulations, and
use it to generate a suite of synthetic surveys resembling Gaia DR2 in data
structure, magnitude limits, and observational errors. We use three
cosmological simulations of Milky-Way-mass galaxies from the Latte suite of the
Feedback In Realistic Environments (FIRE) project, which feature
self-consistent clustering of star formation in dense molecular clouds and thin
stellar/gaseous disks in live cosmological halos with satellite dwarf galaxies
and stellar halos. We select three solar viewpoints from each simulation to
generate nine synthetic Gaia-like surveys. We sample synthetic stars by
assuming each star particle (of mass 7070 $M_{\odot}$) represents a single
stellar population. At each viewpoint, we compute dust extinction from the
simulated gas metallicity distribution and apply a simple error model to
produce a synthetic Gaia-like survey that includes both observational
properties and a pointer to the generating star particle. We provide the
complete simulation snapshot at $z = 0$ for each simulated galaxy. We describe
data access points, the data model, and plans for future upgrades. These
synthetic surveys provide a tool for the scientific community to test analysis
methods and interpret Gaia data.
