A must-read for those interested in (conceptual) modelling!

The book “The What and How of Modelling Information and Knowledge”, written by C. Maria Keet, caught my attention right in its preface: “One may wonder why even bother with a book about modelling when there are the large language models with apps like ChatGPT that are claimed to be taking over the world by storm. Among others, they don’t make you understand stuff. Modelling does.” Indeed, before writing this commentary, I decided to use the knowledge from the book itself and create a mind map (discussed in Chapter 2) to structure my thoughts. Notably, I managed to write this text much faster and easier after investing just a few minutes of my time. Let me say: it really works! Modelling does make you understand stuff.

Reading this book reminded me of one of my favourite cartoons once presented to me by my supervisor. The cartoon describes four stages of the learning trajectory. The first stage is unconscious incompetence, which is when you do not know what you do not know. The second is conscious incompetence, which is when you know what you do not know - also known as the “AHA!” or awareness part, where the learner realises the possibilities opened up by the new learning subject. Third and fourth are conscious and unconscious competence, which occur when you know what you know, and when you have so much practice with a skill that it has become “second nature”, respectively. Even though I have been involved in the world of modelling and ontologies since my Bachelor’s around 2016, this book surprised me with several “AHA!” moments. Therefore, the book is a testament to an enduring truth: there is always something new to learn, no matter your background.

I appreciate how the author establishes the book’s scope clearly from the beginning. Maria dives right into the topic from the first chapter, clearly outlining the goals and motivation of the book. This clarity is particularly welcome at a time when the term ‘model’ is used to describe so many things, both scientifically and non-scientifically. Maria takes the sensible step of defining the specific type of models she explores and the kind of content the reader can expect: “This book is about a different type of modelling, an activity that is not an end in itself merely to creativity, but one that has a model as concrete output emanating from the act of modelling. […] What is a model in the sense we’ll use it in this book? It’s an abstraction, idealisation, approximation or simplification of reality […], or of our best understanding of reality we can attain.”

Following the introductory chapter, the author essentially takes the reader by the hand and leads them through a structured learning journey, which “covers five principal declarative modelling approaches to model information and knowledge for different, yet related, purposes. [She] starts with entry-level mind mapping, proceeds 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.” This journey is taken with a very realistic and unbiased perspective, where the benefits of each approach are contrasted with their downsides and limitations. Maria employs clear and simple language to describe modelling procedures and methods, all accompanied by clear illustrations. She also includes some interesting tips for modelling (some rarely found in academic papers). I found these tips to be very useful, especially for beginners.

One aspect I found lacking in the book is a more substantial focus on evaluation. While Maria offers valuable insights into the evaluation of the artefacts produced, I believe that a deeper exploration of evaluation methods would have greatly enriched the text. I am pretty sure Maria has a lot to say about the evaluation of models as well, and she probably had good reasons not to include this topic in this book.

Most importantly, the book is very enjoyable to read. The examples throughout the text are fun and thought-provoking. It was interesting and engaging to read about Maria’s own experience, and also more about the broader history of modelling and ontologies. 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. As Maria says in Chapter 8: “more and better modelling […] may get you ahead of those who don’t, thanks to the focus and more systematic domain analysis to structure content, ideas, and theories.” If you are an expert in modelling, then I hope that this book will allow you to revisit the basics, learn something new from the fun examples and interesting use cases and, perhaps, inspire new insights for future research.