  Model-free data-driven computational mechanics, first proposed by
Kirchdoerfer and Ortiz, replaces phenomenological models with numerical
simulations based on sample data sets in strain-stress space. Recent literature
extended the approach to inelastic problems using structured data sets, tangent
space information, and transition rules. From an application perspective, the
coverage of qualified data states and calculating the corresponding tangent
space is crucial. In this respect, material symmetry significantly helps to
reduce the amount of necessary data. This study applies the data-driven
paradigm to elasto-plasticity with isotropic hardening. We formulate our
approach employing Haigh-Westergaard coordinates, providing information on the
underlying material yield surface. Based on this, we use a combined
tension-torsion test to cover the knowledge of the yield surface and a single
tensile test to calculate the corresponding tangent space. The resulting
data-driven method minimizes the distance over the Haigh-Westergaard space
augmented with directions in the tangent space subject to compatibility and
equilibrium constraints.
