Data Science and Knowledge Engineering: From Knowledge Engineering to Knowledge Creation

2017 ◽  
pp. 147-155
Author(s):  
Nico Roos
Keyword(s):  
Knowledge Creation ◽  
Data Science ◽  
Knowledge Engineering

ANT and Engineering Education, learning spaces with actors

2020 ◽  
Vol 7 (10) ◽  
pp. 49-59
Author(s):  
Jose Figueiredo
Keyword(s):  
Engineering Education ◽  
Network Theory ◽  
Knowledge Creation ◽  
Knowledge Engineering ◽  
Actor Network Theory ◽  
Learning Spaces ◽  
Actor Network ◽  
Basic Goal

Engineering education is a situated process, enacted by empowerment, motivation and enrolment of actors, using different materials, and framed in exploratory attempts. Inscribing technologic design in the use of artefacts is a basic engineering concern and pushes us to sociotechnical ambiences of value earning and sustainability. We think Actor-Network Theory provides a framework that contributes to our understanding of complexity inscribed in the relations and mutual influences that emerge among actors in learning spaces. Using narrative, and exploring ANT concepts, we circulate in learning spaces, observing and deciding about ways we can explore to enhance knowledge creation and learning. Our results are exploratory but they intend to contribute to a different look into educational fields. Our basic goal is to convince researchers to join us in our reflections and experiments. We believe we are tackling with an innovative perspective, consistent with an extension to this area of knowledge – engineering education.

scholarly journals Data science as knowledge creation a framework for synergies between data analysts and domain professionals

2021 ◽  
Vol 173 ◽  
pp. 121160
Author(s):  
Haiko van der Voort ◽  
Sabine van Bulderen ◽  
Scott Cunningham ◽  
Marijn Janssen
Keyword(s):  
Knowledge Creation ◽  
Data Science

scholarly journals Indigenous frameworks for data-intensive humanities: recalibrating the past through knowledge engineering and generative modelling.

2021 ◽  
Vol HistoInformatics (HistoInformatics) ◽  
Author(s):  
Sydney Shep ◽  
Marcus Frean ◽  
Rhys Owen ◽  
Rere-No-A-Rangi Pope ◽  
Pikihuia Reihana ◽  
...  
Keyword(s):  
Digital Humanities ◽  
Data Science ◽  
Research Collaboration ◽  
Knowledge Engineering ◽  
Data Intensive ◽  
Aotearoa New Zealand ◽  
Social Network Approach ◽  
International Audience ◽  
Indigenous Worldview ◽  
Generative Modelling

International audience Identifying, contacting and engaging missing shareholders constitutes an enormous challenge for Māori incorporations, iwi and hapū across Aotearoa New Zealand. Without accurate data or tools to har-monise existing fragmented or conflicting data sources, issues around land succession, opportunities for economic development, and maintenance of whānau relationships are all negatively impacted. This unique three-way research collaboration between Victoria University of Wellington (VUW), Parininihi ki Waitotara Incorporation (PKW), and University of Auckland funded by the National Science Challenge | Science for Technological Innovation catalyses innovation through new digital humanities-inflected data science modelling and analytics with the kaupapa of reconnecting missing Māori shareholders for a prosperous economic, cultural, and socially revitalised future. This paper provides an overview of VUW's culturally-embedded social network approach to the project, discusses the challenges of working within an indigenous worldview, and emphasises the importance of decolonising digital humanities.

scholarly journals Exploration of Knowledge Engineering Paradigms for Smart Education: Techniques, Tools, Benefits and Challenges

2020 ◽  
Vol 17 ◽  
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Data Science ◽  
Knowledge Engineering ◽  
Case Based Reasoning ◽  
Tutoring Systems ◽  
Smart Systems ◽  
Smart Education ◽  
New Generation ◽  
Application Developers

Knowledge engineering paradigms (KEPs) deal with the development of intelligent systems in which reasoning and knowledge play pivotal role. Recently, KEPs receive increasing attention within the fields of smart education. Researchers have been used the knowledge engineering (KE) techniques, approaches and methodologies to develop a smart tutoring systems (STSs). The main characteristics of such systems are the ability of reasoning, inference and based on static and heuristic knowledge. On the other side, the convergence of artificial intelligence (AI), web science (WS) and data science (DS) is enabling the creation of a new generation of web-based smart systems for all educational and learning tasks. This paper discusses the KEPs techniques and tools for developing the smart educational and learning systems. Four most popular paradigms are discussed and analyzed namely; case-based reasoning, ontological engineering, data mining and intelligent agents. The main objective of this study is to determine and exploration the benefits and advantages of such computational paradigms to increase the effectiveness and enhancing the efficiency of the smart tutoring systems. Moreover, the paper addresses the challenges faced by the application developers and knowledge engineers in developing and deploying such systems. In addition to institutional and organizational aspects of smart educational technologies development and application

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification

KEATS: A System to Support Knowledge Engineering and Training for Decision-Making Skills

1989 ◽  
Author(s):  
Fritz H. Brecke ◽  
Patrick Hays ◽  
Donald Johnston ◽  
Gail Slemon ◽  
Jane McGarvey ◽  
...  
Keyword(s):  
Decision Making ◽  
Knowledge Engineering ◽  
And Training

The Knowledge Creation Organization: The Case of Alphana

2012 ◽  
pp. 78-90
Author(s):  
Thang Nguyen Ngoc
Keyword(s):  
Competitive Advantage ◽  
Knowledge Creation ◽  
Future Research ◽  
Sustainable Competitive Advantage ◽  
Knowledge Based ◽  
The Future

Knowledge and the capability to create and utilize knowledge today are consid- ered to be the most important sources of a firm’s sustainable competitive advantage. This paper aims to advance understanding of the knowledge creation of firm in Vietnam by studying Alphanam Company. The case illustrates how knowledge- based management pursues a vision for the future based on ideals that consider the relationships of people in society. The finding shows that the case succeeded because of their flexibility and mobility to keep meeting to the changing needs of the customers or stakeholders. The paper also provided some suggestions for future research to examine knowledge-based management of the companies in a different industry segments and companies originating in other countries

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