The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties. Its execution requires control over a larger number of parameters, and therefore, its application in high-throughput studies is hindered by the complex and time-consuming convergence process across a multidimensional parameter space. To address these challenges, we develop a fully-automated open-source workflow for G₀W₀ calculations within the AiiDA framework and the projector augmented wave (PAW) method. The workflow is based on an efficient estimation of the errors in the quasi-particle (QP) energies due to basis-set truncation and ultra-soft PAW potentials norm violation, which allows a reduction in the dimensionality of the parameter space and avoids the need for multidimensional convergence searches. Protocol validation is conducted through a systematic comparison against established experimental and state-of-the-art GW data. To demonstrate the effectiveness of the approach, we construct a database of QP energies for a dataset of over 320 bulk structures.

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