The What and How of Modelling Information and

The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies. C. Maria Keet

The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies


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ISBN: 9783031396946 | 177 pages | 5 Mb
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  • The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies
  • C. Maria Keet
  • Page: 177
  • Format: pdf, ePub, fb2, mobi
  • ISBN: 9783031396946
  • Publisher: Springer Nature Switzerland
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The main aim of this book is to introduce a group of models and modelling of information and knowledge comprehensibly. Such models and the processes for how to create them help to improve the skills to analyse and structure thoughts and ideas, to become more precise, to gain a deeper understanding of the matter being modelled, and to assist with specific tasks where modelling helps, such as reading comprehension and summarisation of text. The book draws ideas and transferrable approaches from the plethora of types of models and the methods, techniques, tools, procedures, and methodologies to create them in computer science. This book covers five principal declarative modelling approaches to model information and knowledge for different, yet related, purposes. It starts with entry-level mind mapping, to proceed to biological models and diagrams, onward to conceptual data models in software development, and from there to ontologies in artificial intelligence and all the way to ontology in philosophy. Each successive chapter about a type of model solves limitations of the preceding one and turns up the analytical skills a notch. These what-and-how for each type of model is followed by an integrative chapter that ties them together, comparing their strengths and key characteristics, ethics in modelling, and how to design a modelling language. In so doing, we’ll address key questions such as: what type of models are there? How do you build one? What can you do with a model? Which type of model is best for what purpose? Why do all that modelling? The intended audience for this book is professionals, students, and academics in disciplines where systematic information modelling and knowledge representation is much less common than in computing, such as in commerce, biology, law, and humanities. And if a computer science student or a software developer needs a quick refresher on conceptual data models or a short solid overview of ontologies, then this book will serve them well.

COE ontology map interface. Links to other
It bridges the gap between the informal nature of concept maps and the formal machine-readable Web ontology languages (Hayes et al., 2005) , by making use of a 
Ontological Engineering | Download Scientific Diagram
data specifically using mind maps. Their ontology engineering was used to provide structures and mental models that support information understanding.
From Mind Maps to Ontologies (Paperback)
The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies (Paperback) Her research focuses on ontology engineering, conceptual 
From Mind Maps to Ontologies (Paperback)
The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies (Paperback) Her research focuses on ontology engineering, conceptual 
(PDF) Using Concept Maps For Ontology Development
PDF | Ontologies are a technological key factor regarding the knowledge management domain. This paper presents a graphical-based knowledge.
(PDF) Semantics of Knowledge Map Visualization
A mind map represents the data as a drawing that shows the link between different elements of information and can assist in theory-refining for an 
From Mind Maps to Ontologies: the dance school example
The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies.
The What and How of Modelling Information and Knowledge
The What and How of Modelling Information and Knowledge: From Mind Maps to Ontologies The main aim of this book is to introduce a group of 
ontology mapping - an overview
In practice, ontology mapping is done manually by domain experts and is very time consuming when there are many data sources, or when ontologies are large or 

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