We present new approaches from the aspects of computation, communication, and their integration, to readers including analysts in sciences and businesses, systems managers, and learners desiring to design knowledge to learn. We show clues to explaining causalities in the target world of a black-box AI of which users may seek a predictive performance. For obtaining interpretable knowledge, we show the integration of model- and data-driven approaches, the analysis and perception of signals from data acquired in the cyber or the real word, and creative communication which connects demands to data by visualizing the data market as a place for innovations