Abstract:
Data intensive research (DIR) is being developed in frame of the new paradigm of research study known as the Fourth paradigm, emphasizing an increasing role of observational, experimental, and computer simulated data practically in all research domains. The principal goal of DIR is an extraction (inference) of knowledge from data. The intention of this work is to make an overview of the existing approaches, methods, and infrastructures of the data analysis in DIR accentuating the role of hypotheses in such process and efficient support of hypothesis formation, evaluation, and selection in course of the natural phenomena modeling and experiments carrying out. An introduction into various concepts, methods, and tools intended for effective organization of hypothesis-driven experiments in DIR is presented.