Lemonade and Lyrebirds For Thought: Maria Keet’s The What And How Of Modelling Information and Knowledge
What makes an orange orange – is it its spherical shape or its orange-ness? What dance is really? Does reality exist independently of or is constructed through language?
These are only a small part of the body of questions Maria Keet explores in her new (2023) book The What and How of Modelling Information and Knowledge From Mind Maps to Ontologies, seeking to light our way towards better understanding and, most importantly, doing modeling.
In this post I am sharing my fascination with the expedition Maria, a seasoned guide for all of us looking for ways to analyze, describe and clarify what is.
The What and How of Modelling Information and Knowledge at a glance
“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.”
M. Keet, The What and How of Modelling Information and Knowledge From Mind Maps to Ontologies, p. v.
Right from the start of the book Maria presents what’s in for us in a very neat, well-modelled (sic!) and comprehensive description of what to expect. Formally, the book is about “five principal declarative modeling 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.”
I couldn’t have summarized it better. And just like Maria thoughtfully laid the components of the book for the reader in a clear and accessible way, so did she throughout the book, built brick by brick a store full of “the goodies”, as she called them, computing brings to the table of building models, choosing from techniques, tools and procedures and above all linking up information.
Seeing the Woods From Porphyry’s Trees: Into the Modelling Bulls Eye
It is through a thorough look at the very beginnings of philosophers’ attempts to capture and structure the key things that exist, that Maria invites us to begin the journey of understanding modelling.We start with “Illustrious modellers [like] Aristotle (third century BC), Plato (who taught Aristotle), and Porphyry (way later, third century CE), [who] tried to capture and structure the key things that exist, or anyhow were thought to exist according to their understanding of reality.”
The ultimate goal is to teach us how we can deconstruct a certain topic into its elements in the way they relate to each other. And that teaching comes with a historical background of how that was done before, how it can be done better, and even a mapping language between the approaches.
And that goal was reached with a treasure trove of metaphors, in parallel with plenty of curios, facts, and, most importantly, a wonderful interconnected way of presenting complex topics in an easy to grasp way.
For example, did you know that Wikipedia page template for cladograms follows a structure that belongs to another model?
I didn’t either.
I learnt that from the book along with dozens of other curios facts and historical references about the way we have put, sometimes crammed, often times in an unreadable way for machine (and even human ) our precious knowledge in mind-maps, diagrams and models that are not using unified symbols neither concepts or references.
Curious Fact: There is a database that stores data about identifiable lyrebirds, whole video and audio clips at a location at a particular date, annotation terminology, and annotated video and audio fragments. The image is from: https://www.mobilia-gallery.com/exhibits/rie-taniguchi-spotlight-exhibition-2/
Models to Capture Knowledge By
One of the fractals of the wonderful modeling panorama the book offers is the models comparison in one of the chapters. As across the entire book, things are presented in layers do that you can choose how deep you want to go down the rabbit hole. And there are holes. Yet their presentation is carefully modelled. And it is the what-and-how accounts for each model that culminate in an integrative chapter where one can see the characteristic features of each modeling approach.
“A particular type of model should satisfy its own aims and declared function at the
very least. If it meets any of the others, then that is a coincidental bonus. How well
it meets its own aims and how many bonuses a modelling approach and language
has, is a non-trivial matter to figure out.”
Maria also wrote extensively about that in a post based on the book here: On comparing modelling languages https://modeling-languages.com/on-comparing-modelling-languages/
Ontologies – The New Wonder Potion?
If you get your core ontology wrong, errors, misinterpretations and misunderstandings flow ceaselessly from your false model of reality.
Mike Hockney, in Causation and the Principle of Sufficient Reason
This is the citation Chapter 6, one of my favourite parts of the book opens with. The chapter is about ontologies – their philosophical underpinnings and concrete practicalities.
Theory seeds are always waters with plenty of examples from practice and concrete scenarios of certain modeling conundrums.
In it, I learnt what are the best use cases for ontologies, when did they emerge, why people back then thought of them as the “ new wonder potion”.
Moreover I enjoyed reading about approaches to ontology building, accompanied by something that I find precious these days. A set of general guidelines for building an ontology together with a peek into part of the dance ontology development, walking the talk of the guidelines with takeaways for us, readers. Also there is a special section dedicated to “How to Do an Ontological Investigation”. For the curious, the draft of that section partially appears in: https://keet.wordpress.com/2022/09/09/how-does-one-do-an-ontological-investigation/
Lemonade For Thought
Having existed at my own non-trivial intersection of content writing and the Semantic Web, it was refreshing and invigorating to straddle another intersection – that of mind-mapping and ontologies, of deconstructing worlds and building them anew in a machine-readable, standard language.
For example, have you recently thought about what lemonade really is? Is it a sum of water, lemons and sugar? How do we describe it? Does it have parts, or portions? The answers lie in what we read in the section “What’s Lemonade, Really”. A section devoted to mereology – the study of parthood relationships. Here’s a rabbit hole for thought worth (and hard) exploring in this regard: https://www.jstor.org/stable/4147988
One thing that all the time I saw throughout reading the book, at times very slowly, as there are many new concepts and understandings for me, is that my ability to think through a subject and differentiate its dynamics and moving parts grew. And modelling, although still very far away a practice, became clearer, its approaches and varieties more accessible.
That skill of deeply understanding something by looking into its parts, their dynamics, and the internal and external relationships they keep or don’t, is a sine qua non in our world, where communication and systems supporting it increasingly rely on machines processing information. Modelling is a skill to have or at least be aware of. One pleasant way to acquire that skill (and I dare say passion for deconstructing what is and modeling it) is Maria Keet’s book.
Related links:
Book’s website
Maria Keets’s website
Dialogue with Maria Keet: Ontology Engineering and the Love for Modeling and Analysis: A Dialogue with Maria Keet