Transdisciplinary fundamentals of information-analytical activity

Abstract

The information and analytical activities of experts have one of the main problems which are the unstructured information resources usage to be displayed in various network documents and represent a passive distributed system of knowledge in fact. This research considers transdisciplinary of such information resources as a metacategory that takes into account the hyperproperties of Big Data (Big Data), namely: a) reflection which implements the principles of integration, the consistency and their behavior integrity and guarantee; b) recursion which implements the recurrence category of their operational transformation forms during activation; c) reduction on the basis of which these forms decomposition principle is realized. Their interpretation in the case of Big Data processing is implemented in the following areas: i) the information resources structural analysis; ii) forms of interaction with information resources; iii) definition of the mechanisms for identifying criteria for selecting appropriate contexts that needed for the expert analysis. The actuality of the such procedures implementation is based on the need to create the conditions for supporting the effective a large number of diverse information arrays processing for the information and analytical activities of experts. This understanding for solving the Big Data processing problem is supported by the implementation of component architecture of the services to support the analytical processes of the experts from various thematic sphere of activity.