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Superordinate Knowledge Based Comprehensive Subset of Conceptual Knowledge for Practical Geo-spatial Application Scenarios

Authors:
Claus-Peter Rückemann

Keywords: Comprehensive Conceptual Knowledge; Geo-spatial Application Scenarios; Superordinate Knowledge Methodology; UDC; Advanced Data-centric Computing

Abstract:
The results presented in this paper are based on the research conducted during the last years. Many multi-disciplinary and practical geo-spatial data and application solutions require to exploit holistically complex scenarios. In many cases, data and algorithms as well as workflows have to be created and tackled individually. The goal of this research is to create an innovative, comprehensive tool base of conceptual knowledge in geo-spatial application scenarios for arbitrary knowledge context in any media. The solution should be complementary to the commonly available geo-spatial features and should fulfill a range of further criteria, especially for a coherent system of knowledge, multi- disciplinary, and data-centric. The result should allow to create and refer to facetted knowledge focussed on geo-spatial scenarios. The paper presents the results of an implementation based on the fundamental methodology of superordinate knowledge. The solution is targeting geo-spatial application scenarios and has been used for many practical implementations over more than three decades. The resulting comprehensive subset of conceptual knowledge reference divisions, which was created from this long- term research, is available and first published with this paper.

Pages: 52 to 58

Copyright: Copyright (c) IARIA, 2019

Publication date: February 24, 2019

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-687-3

Location: Athens, Greece

Dates: from February 24, 2019 to February 28, 2019