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ThinkMind // ICCGI 2020, The Fifteenth International Multi-Conference on Computing in the Global Information Technology // View article iccgi_2020_1_30_10023
Quasi-physical Model of Knowledge
 Authors:
Maxim Polyakov
Igor Khanin
Nikolai Bormatenko Keywords: infosphere; noosphere; model of knowledge; conscious phenomena; quasi-physical effects; innovation development; sign ontology; data ontology; organization ontology; noosphere ontology; convergence of knowledge Abstract:
The domain of research is the process of understanding the field of information phenomena, including its practical level, in solving problems such as fragmentation of data, which is due to their diversity and variability. The solution to such problems requires immersion in the ontology (essence) of information phenomena and a relevant cognitive model. The problem of creating such a model is interesting, in particular, in that reducing the fragmentation of data will make data, including Big Data, and then programs and organizations, more unified in form, more diverse in content,in general - more useful. To solve the problem, the following conditions had to mature: an empirical base, formed by digitizing information practices; principles of convergence of heterogeneous fundamental ideas; reconstruction of understanding how cognition occurs in various fields of phenomena. The presence of conditions made it possible to develop a Quasi-Physical Model of Cognition (QPMC), where the object of cognition is the result of the convergence of the physiosphere, biosphere and infosphere (Vernadsky’s noosphere); the method of cognition is the embodiment of forms of consciousness in artifacts; the ontology of the bodies of knowledge and innovation is signs constructions (programs, databases and knowledge, organizations. The QPMC model is addressed to those who in the field of information phenomena solve practical and theoretical problems of information and communication technology, cognition, semiotics, economics,knowledge management, which, unlike, for example,“digitization” or modeling, require reflection as a better understanding of the innovator’s own actions. Pages: 13 to 23 Copyright: Copyright (c) IARIA, 2020 Publication date: October 18, 2020 Published in: conference ISSN: 2308-4529 ISBN: 978-1-61208-793-1 Location: Porto, Portugal Dates: from October 18, 2020 to October 22, 2020
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