Knowledge-Grid Modelling for Academic Purposes

Owoc, Mieczysław L.; Hauke, Krzysztof; Weichbroth, Paweł

doi:10.1007/978-3-319-55970-4_1

Cited by 10 publications

(9 citation statements)

References 23 publications

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“…On the contrary, the latter has a verbal or written form (e.g. procedure) and is relatively easy to communicate, codify, store and distribute; usually, explicit representation uses a predefined notation that enables gathered (generated) knowledge to be expressed consistently and completely [3] (e.g. in the form of the association rule: if a customer buys wheat bread then he/she also buys skimmed milk, with support 0,02 and confidence 0,85).…”

Section: A Knowledgementioning

confidence: 99%

“…In this case, "context" is often referred to as environment [7], location [8], or situation [9]. To these three nouns, we can respectively pin the following questions: (1) what resources are you surrounded by?, (2) where are you?, and (3) and if necessary may be identified "manually" by exploiting the expert (or domain knowledge), or "automatically" by using particular types of attributes [10].…”

Section: B Contextmentioning

confidence: 99%

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Towards better understanding of context-aware knowledge transformation

Owoc¹,

Weichbroth²,

Zuralski³

2017

Annals of Computer Science and Information Systems

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Abstract-Considering different aspects of knowledge functioning, context is poorly understood in spite of intuitively identifying this concept with environmental recognition. For dynamic knowledge, context especially seems to be an essential factor of change. Investigation on the impact of context on knowledge dynamics or more generally on the relationship between knowledge and its contextual interpretation is important in order to understand knowledge dynamics. The aim of this paper is to research and examine the nature of knowledge transformation (a specific sort of life-cycle), and to identify contextual factors affecting knowledge dynamics.

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Section: A Knowledgementioning

confidence: 99%

Section: B Contextmentioning

confidence: 99%

Towards better understanding of context-aware knowledge transformation

Owoc¹,

Weichbroth²,

Zuralski³

2017

Annals of Computer Science and Information Systems

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“…In another work [8], we introduced the first multidimensional knowledge space model (including entityrelationship schema), implemented as a part of the developing system, designed to efficiently distribute and manage knowledge resources. We view our model as the foundation of a knowledge grid platform, where two significant aspects are considered: education-and researchdriven.…”

Section: Related Workmentioning

confidence: 99%

The lemniscate knowledge flow model

Weichbroth

Brodnicki

2017

Annals of Computer Science and Information Systems

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Abstract-Knowledge is seen as one of the main resources for organizations providing knowledge-intensive services. Therefore, sharing and reusing are the main goals of the modern knowledge management (KM) approach, driven by information and communication technologies (ICT). However, one must ask for the details in order to provide the means and tools to design and deploy an environment able to fulfil these two goals. We observed that the interactions occurring on knowledge resources can be reduced to a directional flow, and further described by distinguished internal phases. In our research we put forward two research questions: (1)

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“…Knowledge management entails the following functions (Brewster, Ciravegna, & Wilks, 2002;Marwick, 2001;McQueen, 1998;Uren et al, 2006;Zins, 2007): information classification for proper understanding; sharing of ideas; promotion of collaboration among organizations; and standardization of information visà-vis easy retrieval. The works of scholars from a multitude of disciplines have suggested that access to a rich diversity of information encourages organisation existence and maintain growth (Owoc & Weichbroth, 2015;Wang & Ji, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Several techniques have been used in tertiary institutions of learning outside Nigeria to meet up with the challenges and vis-a-vis promotes knowledge-driven economy to ensure good quality, efficiency and ultimately leverage on competitive edge. Examples are: Mauritius (Abbass, 2017), Iran (Yokhaneha & Baghoumian, 2014), Europe (Owoc & Weichbroth, 2015), Asia (Wang & Ji, 2005), Kenya (Murumba & Micheni, 2017), etc. Many studies have also proven that modern knowledge sharing and management system such as knowledge grid (KG) is more effective than traditional ways of sharing and managing knowledge (Sani, 2015;Yokhaneha & Baghoumian, 2014).…”

Section: Introductionmentioning

confidence: 99%

Knowledge Grid: An Intelligent System for Collaboration and Knowledge Management in Nigerian Universities

Akinnuwesi

Odumabo

Aribisala

2020

Data Science Journal

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Nigeria has 169 universities approved by National University Commission (NUC) with 43 Federal Universities, 47 State Universities and 79 Private Universities. The universities are located in different geographical areas and collaboration among these universities is difficult and this makes accessibility to data and information resource of the universities a problem. As a result quite a number of knowledge built from these resources are locally managed within each university private network that is not shared with other universities due to lack of virtual collaboration on a grid computing platform. Knowledge building and management in a country is a function of the information that one could have access to with ease but non-collaboration of the universities in a virtual environment is a hindrance to quality national knowledge building and management. Thus the need arises to embrace grid system as platform for all universities to pool their resources together and hence make their information resources available and accessible for knowledge building and management. This report presents an overview of Nigeria universities' operations as regard their research and innovation policies and vis-à-vis governance and resource management across public and private universities. Also we did a systematic review and analysis of knowledge grid (KG) technology vis-à-vis its use for knowledge management in Nigerian universities. We focused on identifying the strengths and challenges of knowledge grid development and implementation vis-à-vis the technological, economic and social implications involved in the process. Our future work is to develop a robust knowledge grid model that will allow collaboration among universities in Nigerian community and hence facilitates information and knowledge sharing and management among the universities.

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Knowledge-Grid Modelling for Academic Purposes

Cited by 10 publications

References 23 publications

Towards better understanding of context-aware knowledge transformation

Towards better understanding of context-aware knowledge transformation

The lemniscate knowledge flow model

Knowledge Grid: An Intelligent System for Collaboration and Knowledge Management in Nigerian Universities

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