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Computation and Knowledge Mapping for Data Entities

Authors:
Claus-Peter Rückemann

Keywords: Knowledge Mining and Mapping; Computational Procedures; Context Creation; Universal Decimal Classification; Advanced Data-centric Computing.

Abstract:
This paper presents the research and results from developing resources and knowledge based methods for the creation of new context for objects and entities, based on the methodology of knowledge mapping. The results are an architecture allowing advanced knowledge mapping including flexible deployment of computational sequences and an implementation of resources and application components. The knowledge mapping enables to put knowledge objects in new context, which can be used in arbitrary scenarios, e.g., with knowledge mining and decision making. The paper shows the importance of facilities for different implementations and presents a resulting architecture and case studies of two different implementations for a task. The implementation cases are based on a computational case of spatial visualisation. For demonstration, a publicly available central data object was used for data entity analysis. The paper presents practical examples and discusses the high level views of implementations and case study. The main goal of this research is to create a functional architecture based on sustainable long-term multi-disciplinary knowledge resources, which can provide a wide range of flexibility for knowledge mapping and different computational solutions.

Pages: 7 to 12

Copyright: Copyright (c) IARIA, 2018

Publication date: July 22, 2018

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-655-2

Location: Barcelona, Spain

Dates: from July 22, 2018 to July 26, 2018