  The fundamental relationship of the atomic structure (represented by its
atomic property parameters, APPs) and its physical properties of a specific
inorganic substance can be realized in the bottom-up data-centric and the
top-down knowledge physics-centric ways. Nowadays these two approaches compete
and enhance one another qualitatively and quantitatively. We present our own
holistic method and implementation, based on the PAULING FILE peer-reviewed
inorganic substances database, the world largest materials database containing
under one shelter crystallographic structures, phase diagrams and large variety
of physical properties of single-phase inorganic substances. In addition we
present generated machine-learning data, as well as simulated DFT
physics-centered data, which are in close connection and comparison with the
PAULING FILE peer-reviewed reference data.
