The What and How of Modelling
The what and how of modelling information and knowledge — from Mind Maps to Ontologies
Published by Springer in 2023. ISBN-10: 3031396944; ISBN-13: 978-3031396946
This book:
1) Introduces models and modelling processes to improve analytical skills and precision;
2) Describes and compares five modelling approaches: mind-maps, models in biology, conceptual data models, ontologies, and ontology;
3) Aims at readers looking for a digestible introduction to information modelling and knowledge representation.
Aims and content
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. It 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?
Intended audience
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.
Where to buy it
Currently, it is available as hardcopy and ebook from various online stores, among others: the publisher Springer or Springer Professional, many national online bookstores, such as bol, booktopia, and indigo, and Amazon .com (or as ebook) and on their country-specific sites, such as .uk, .de etc.
More information, reviews, supplementary material etc., are available from the academic page of the book: http://www.meteck.org/modellingbook/index.html.
Reviews and endorsements
“The book describes – in excellent style and appropriate framing and leveling – five principal declarative modelling approaches to model information and knowledge for different, yet related, purposes.”
“The book is rich on good advice going down a couple of levels, also on the complicated matters. You will learn about how-to as well as why.”
——
Thomas Frisendal
Graph Data Architect, Visual Data Modeler and GQL committee member
Full review posted on LinkedIn as Interesting New Book on Modeling of Data and Information
~~
“a fascinating journey through the art and science of modeling”
——
Teodora Petkova
Content Writer at Ontotext and Philologist with a PhD in Marketing Communications
Short review on Goodreads; see also her long review Lemonade and Lyrebirds For Thought on her website
~~
“This book is highly recommended for people with any level of expertise, from novices (as the book is not too technical to scare you away) to advanced modellers (the book is not oversimplified either). If you are new to the topic of modelling, then the book will help you create your modeller mindset.”
——
César Bernabé
PhD candidate in the Biosemantics group at Leiden University Medical Centre
Full review posted on his blog as A must-read for those interested in (conceptual) modelling!
~~
“The most appealing for me is Maria’s riveting writing and also her deep knowledge being trasnfered through examples and bit by bit, evey step building on the previous one. Maria does have a nack for explaining complex stuff very methodically grounding it in theoretical knowledge without overwhelming the readers. Things are presented in layers do that you can choose how deep you want to go down the rabbit whole. And there are rabbit holes 🙂 But modelled. 🙂 with elaborate care.”
——-
Teodora Petkova
Content writer and semantic medatada specialist with Ontotext
More preliminary review comments posted on LinkedIn
~~
“Trata-se de um bom livro, principalmente se você gosta de receber informação contextualizada, o que é uma preocupação da autora ao londo de toda obra.”
——
Mauricio B. Almeida
Full professor at the Federal University of Minas Gerais
An Amazon review
~~
“The pragmatic and historical approach of this book is of great help in developing a domain modelling framework for the Dutch Public Healthcare.”
——
Holke Visser
Data architect at Visser Data BV, board member of Enterprise Engineering Institute
Posted on LinkedIn
~~
“I like the pragmatic guidance on modelling steps and approaches and the supporting examples, plus what you can and can’t do with different modelling types and how you can enhance readability and understandability of models and make implicit knowledge and inconsistent constructs in models visible, such that you can improve the quality of your models.”
——-
Pieter van Everdingen
Enterprise & Information Architect at OpenInc
Posted on LinkedIn
~~
“I’ve enjoyed reading your book,” “There are many non-IT specialties across an organization that can benefit from a broad understanding of mapping, without having to understand the intricacies of formal modelling languages.”
——-
Barbara Fillip, Ph.D., PMP
Senior Advisor, Knowledge Management at Chemonics International
Posted on LinkedIn