Evaluation of Quality of a Project Management & Scientific Publications Based On a New Wisdom Framework

This is a theoretical research paper. It presents a proposal for the evaluation of the quality of a project management based on a new and ‘General Cognitive Model of Wisdom’ -GCMW-. For the development of this GCMW, is proposed the conception of an ‘Information Ecosystem’ -IE-, which is composed by the following ‘cognitive units’: Data -D-; Information -I-; Knowledge(tacit, explicit) - K(tacit, explicit) = (Kt,e)- and Wisdom(tacit, explicit) -W(tacit, explicit) = (Wt,e)-, compactly written as DIKt,eWt,e. By aligning this IE with the DIKW hierarchical conception, wehave created a new, no hierarchical, integrated and generalized framework -the GCMW-. This GCMW framework aims -as an insight generator or strategic foresight- to provide a better assessment to different problems in any field of science, from information science, applied researchers or a more general audience as per example, to point out the theoretical and conceptual bases for the interaction between the project manager and this GCMW framework.It is introduced a new set of logical –general-, definitions for the DIKW to instrumentalize the GCMW framework. Finally, based on the GCMW framework, we have proposed a ‘Particular Cognitive Model of Wisdom’ -PCMW- for paper quality evaluation. Aiming at to build a comprehensive and in-depth evaluation of the quality of any scientific production, is derived from the GCMW framework a new no-hierarchical model -the PCMW framework- and a new set of logical –particular-, definitions for the DIKW are introduced to instrumentalize the PCMW towards paper quality assessment. This particular framework should provide –for any paper being written-, a better assessment and insight generator. By last, as we are admitting that any paper published has quality so; the proposal is, the quality of this paper is complete if -and only if-, the paper has also W. Both, the PCMW and the particular DIKW instruments definitions, are necessary and sufficient conditions for guaranteeing -guiding- if the paper -which is in evaluation-, has W

CONA: A novel CONtext-Aware instruction paradigm for communication using large language model

We introduce CONA, a novel context-aware instruction paradigm for effective knowledge dissemination using generative pre-trained transformer (GPT) models. CONA is a flexible framework designed to leverage the capabilities of Large Language Models (LLMs) and incorporate DIKW (Data, Information, Knowledge, Wisdom) hierarchy to automatically instruct and optimise presentation content, anticipate potential audience inquiries, and provide context-aware answers that adaptive to the knowledge level of the audience group. The unique aspect of the CONA paradigm lies in its combination of an independent advisory mechanism and a recursive feedback loop rooted on the DIKW hierarchy. This synergy significantly enhances context-aware contents, ensuring they are accessible and easily comprehended by the audience. This paradigm is an early pioneer to explore new methods for knowledge dissemination and communication in the LLM era, offering effective support for everyday knowledge sharing scenarios. We conduct experiments on a range of audience roles, along with materials from various disciplines using GPT4. Both quantitative and qualitative results demonstrated that the proposed CONA paradigm achieved remarkable performance compared to the outputs guided by conventional prompt engineering

Hybrid modeling to support the smart manufacturing: concepts, theoretic contributions and real-case applications about Hybrid and Wisdom-based Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Swarm Differential Privacy for Purpose Driven Data-Information-Knowledge-Wisdom Architecture

Privacy protection has recently been in the spotlight of attention to both academia and industry. Society protects individual data privacy through complex legal frameworks. The increasing number of applications of data science and artificial intelligence has resulted in a higher demand for the ubiquitous application of the data. The privacy protection of the broad Data-Information-Knowledge-Wisdom (DIKW) landscape, the next generation of information organization, has taken a secondary role. In this paper, we will explore DIKW architecture through the applications of the popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will look at it from a DIKW domain perspective. Swarm Intelligence can effectively optimize and reduce the number of items in DIKW used in differential privacy, thus accelerating both the effectiveness and the efficiency of differential privacy for crossing multiple modals of conceptual DIKW. The proposed approach is demonstrated through the application of personalized data that is based on the open-sourse IRIS dataset. This experiment demonstrates the efficiency of Swarm Intelligence in reducing computing complexity

Diverse perceptions of smart spaces

This is the era of smart technology and of ‘smart’ as a meme, so we have run three workshops to examine the ‘smart’ meme and the exploitation of smart environments. The literature relating to smart spaces focuses primarily on technologies and their capabilities. Our three workshops demonstrated that we require a stronger user focus if we are advantageously to exploit spaces ascribed as smart: we examined the concept of smartness from a variety of perspectives, in collaboration with a broad range of contributors. We have prepared this monograph mainly to report on the third workshop, held at Bournemouth University in April 2012, but do also consider the lessons learned from all three. We conclude with a roadmap for a fourth (and final) workshop, which is intended to emphasise the overarching importance of the humans using the spac

Information support and interactive planning in the digital factory : approach and industry-driven evaluation

In the modern world we are continuously surrounded by information. The human brain has to analyse and interpret this information to transform into useable knowledge that is then used in decision making activities. The advent and implementation of Industry 4.0 will make it a requirement for systems within factories to interact and share large quantities of information with each other. This large volume of information will make it even more difficult for the human resources within the factory to sift through the large amount of information required since there is a limit to the information that our brains can cope with. Just in time information retrieval (JITIR) within the digital factory environment aims to provide support to the human stakeholders in the system by proactively yet non-intrusively providing the required information at the right time based on the users context. This paper will therefore provide an insight into the cognitive difficulties experienced by humans in the digital factory and how JITIR can tackle these challenges. By validating the JITIR concept, several industry scenarios have been evaluated: an exemplary model, concerning the machine tool industry, is presented in the paper. The results of this research are a set of guidelines for the development of a digital factory support tool.peer-reviewe

Three Postulates That Change Knowledge Management Paradigm

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