Home // International Journal On Advances in Systems and Measurements, volume 8, numbers 1 and 2, 2015 // View article

Contribution of Statistics and Value of Data for the Creation of Result Matrices from Objects of Knowledge Resources

Authors:
Claus-Peter Rückemann

Keywords: Knowledge Resources; Processing and Discovery; n-Probe Parallelised Workflow; Universal Decimal Classification; High End Computing

Abstract:
This article presents and summarises the main research results on computing optimised result matrices from the practical creation of knowledge resources. With this paper we introduce the main implemented long-term multi-disciplinary and multi-lingual knowledge resources' means, fundamentals and application of documentation, structure, universal classification, and statistics and components for computational workflows and result matrix generation. The resources and workflows can benefit from High End Computing (HEC) resources. The paper presents a knowledge processing procedure using long-term knowledge resources and introduces the n-Probe Parallelised Workflow for an exemplary case study and discussion on a practical application. The goal of this research is to extend the applied features used with long-term knowledge resources' objects and context. The extensions are concentrating on structure and content as well as on processing. The focus is the contribution of statistics and the value of data for the creation of complex result matrices. The major outcome within the last years is the impact on long-term resources based on the scientific results regarding the systematics and methodologies for caring for knowledge.

Pages: 30 to 42

Copyright: Copyright (c) to authors, 2015. Used with permission.

Publication date: June 30, 2015

Published in: journal

ISSN: 1942-261x