Secondly, we should pay special attention to the data quality in the subsystems to be integrated, including resolution, unit size (such as pixel size for image data), missingness, structuredness, and fidelity (such as noise level). Many of these problems are not yet formally addressed, thereby motivating further research on a case-by-case basis guided by domain knowledge. For example, data resolution and fidelity affect the choice of integration ordering, i.e., from high to low or in reverse. For experimental data, the unit size is usually not the same as the resolution because of blurring introduced by the instrument response. Thirdly, we should consider the scalability of the model during development, which may be left unnoticed until Illustrations of spatial models of (left) photoemission data in the energy-momentum coordinates using a Markov random field and (right) combinatorial material screening data in the chemical compositional space using a Gaussian process .