Home // International Journal On Advances in Software, volume 12, numbers 1 and 2, 2019 // View article

Components and Computational Modules for Knowledge Mapping: A Case of Spatial Knowledge

Authors:
Claus-Peter Rückemann

Keywords: Knowledge Mapping; Spatial Knowledge; Context Creation Algorithms; Universal Decimal Classification; Advanced Data-centric Computing.

Abstract:
This paper presents the research results from an extended case study and implementation for the identification and spatial mapping of arbitrary non-georeferenced input data entities. The implemented components and methods are based on the methodology of knowledge mapping. The methodology enables to implement and realise methods for the creation of new context for objects and entities, e.g., creating support for the tasks of knowledge mining and decision making. The focus of the methodology is the mapping of knowledge and its facilities of creating substantially different practical method implementations for identical input objects while aiming on comparable tasks. The main goal of these case studies and implementations is to demonstrate how to create two different automatable methods for knowledge mapping to be applied on each input object, based on a functional architecture of sustainable long-term multi-disciplinary knowledge resources and components, which provide support for a wide range of flexibility for knowledge mapping and different computational solutions. The implementation cases are based on automated computational cases of spatial visualisation. In addition, the results from any of these realisations are used to further valorise new knowledge and continuously improve the contributing long-term knowledge resources.

Pages: 1 to 10

Copyright: Copyright (c) to authors, 2019. Used with permission.

Publication date: June 30, 2019

Published in: journal

ISSN: 1942-2628