Cohesion Forces and Tools

This article is part of the series on Autonomy and Cohesion. It is the second part of the basic overview of the balance. If you haven’t read the previous part, I’d recommend doing so before reading further.

Cohesion forces

Liquids and solids are in those states because there are cohesion forces bonding the molecules together. The main cohesion forces currently studied in physics are the van der Waals forces, dipole-dipole interactions, hydrogen bonding, and ionic bonding. In socio-technical systems, there are cohesion forces too. Those forces are way more complex and less studied. Cohesion in socio-technical systems is not only due to natural forces. Tools, technologies, and artifacts can significantly contribute too. They bring direct and also systemic effects. We’ll go to the cohesion tools and technologies after we briefly review some cohesion forces and factors. Cohesion forces and factors are difficult or impossible to influence, which is what makes them different from cohesion tools and technologies.

There are personal cohesion factors like the need for safety, the need to belong to a social group, to reduce uncertainty, and the need to increase self-esteem. Such needs make us form clubs, tribes, communities, organizations, and networks.

Shared values and beliefs are strong cohesion forces, and those can include the shared value of autonomy.

There are also social identity cohesion forces. We tend to identify, sometimes strongly, with sports clubs, ethnic groups, communities, professions, organizations, or religions. In some situations, compassion, loyalty, and empathy play a bigger role. In others, completely different forces. For example, typical personal cohesion forces in social networks are the need for self-expression, validation, and recognition, as well as the fear of missing out.

In every socio-technical system, there are internal and external cohesion factors and forces. The personal cohesion forces work both within organizations and networks, although they have different subsets and strengths. Typical internal organizational cohesion forces are organizational identity, internal operational dependencies, shared resources, synergy, and efficiency. In networks, cohesion forces and factors are proximity, transitivity, and preferential attachment, and in social networks, there are many additional ones, such as shared interest and shared aversion.

Which brings us to the external cohesion factors.
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Autonomy and Cohesion

The viability and welfare of socio-technical systems depend on their ability to balance autonomy and cohesion.

Is that true for other systems? Yes, it is remarkably universal. It works for biological systems like bacteria or elephants and social systems like packs of wolves, termites or beehives. However, this series focuses on socio-technical systems such as organizations, governments, and networks.

Autonomy brings adaptability and short-term effectiveness.

Cohesion brings efficiency and long-term effectiveness.

In viable systems, the balance between autonomy and cohesion is well maintained at all levels. And they have a way to restore it when it is disturbed.

Thinking in terms of dynamics of essential balances, one of which is that between autonomy and cohesion, has benefits over the usual dilemmas such as centralized/decentralized, hierarchical/flat, waterfall/agile and suchlike. If you are curious, you may watch this webinar for a bit more details or check out the book for an in-depth exploration. In the following series of articles, I’ll expand on topics only briefly mentioned in the book, such as the way the balance works outside organizations, how different systems differ by the way in which cohesion is achieved, and how some cohesion technologies achieve cohesion without reducing autonomy. Then, I’ll move on to decentralization and other topics. But we need to cover the basics first, which is what this and the next article will do.

What is meant by the balance between autonomy and cohesion, and how does it work?
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Requisite Hypocrisy

The city is charged with tension and a sense of urgency. After years of oppression, people’s frustration has reached its boiling point. The streets are flooded with bodies, united in their demand for equality. As you navigate through the crowd, you are just one among the countless anonymous faces. Only those next to you can see you and hear you.

The air is thick with determination and rhythmic chants. Every step brings you closer to the center square, where a stage stands as a symbol of hope and a platform for change.

You ascend the stage. A hush falls over the crowd. All eyes are fixed on the figure that has emerged from their midst. Now everybody can see you. You are given a mike. Now everybody can hear you. You are no longer equal, but only this way you can make the case for equality and help it happen.

Means rarely share values with goals. It can be temporary, just a learning stage, a Wittgenstanian ladder you can throw away after you climb up. Or, an ostensibly necessary compromise, like the oikonomia (same word as economy) in the Orthodox church, where you can deviate from the letter of the law to adhere to the spirit of the law. But in many cases, it is a necessity. A requisite hypocrisy.

You need a platform from which to talk against platforms.
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Link & Think

This blog started in January 2011. That was 13 years ago. Many readers assured me the content was valuable and has aged well. To help new readers find their way, today I published a short Reader Guide to the blog.

It’s time to experiment with new forms of publishing. I’m now launching Link&Think.

PKM (Part 2): Landscape

If you look to the east, you’ll see the Outliners Forest. It is a magical place where branches and leaves can talk to each other. Trees can do that, too, using the fungal network that entangles their roots. You can hear various bird songs, but what grabs the attention is the screech of the spaced parrots.

The Outliners Forest covers part of the Markdown Valley, yet the valley stretches over a much bigger area. The soil is very fertile there. If you walk around, you can find all kinds of plants. A few knowledge streams go through the forest. The bark of some trees around the streams is chewed out by beavers who build dams further down to keep as much water area to themselves as possible before the streams flow into the river down the Markdown valley.

The river flows fast at first, but it slows down when it leaves the Markdown Valley and enters the Canvas Canyon. Intricate drawings cover the walls of the canyon. If you come closer, you’ll see that the drawings are made by the slime mould. It is a bit like the fungal networks of the Outliner Forest, but the legend has it that the slime mould is so intelligent that it can solve any problem.

White clouds cover the sky above. They resemble fluffy thought bubbles, float gently, and seem deceivingly light. Yet, everybody knows they can carry a lot and expand to cover the sky from end to end.

Weary travelers usually enter the Landscape of Personal Knowledge Management from the south, from the Lonely Elephant Savanna. It is a place where one can reflect and prepare for the wondrous adventure that awaits them in the Outliners Forest, the Markdown Valley, and the Canvas Canyon.

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PKM (Part 1): The Explosion

When the virus hit the planet, it induced other parallel pandemics. They did not spread through the air and did not require physical proximity. They spread online. Some were conspiracy theories, of which a good part related to the virus itself. Others were political propaganda, already successful but now more than ever, seizing the opportunity that people got more susceptible and spent more time online.

A less-known yet undeniably astonishing parallel pandemic was the explosion of Personal Knowledge Management tools. There were a dozen PKM tools by the end of 2019. Then suddenly, something happened. In the second half of 2020, there were already more than 50. New ones kept popping up almost every month in the following two years. What makes it even more bizarre is that unlike viruses, which take hours and days to spread, the development of a software tool is a combination of entrepreneurial, engineering and design activities that need much more time to produce usable output. When we add to this the time for users to learn about a tool, be attracted to it, try it, adopt it, and contribute with their feedback, this quick spread looks even more incredible.

So why the sudden interest? Was that a dormant demand? Or could it be that this breed of tools redefined themselves after a series of innovations and created an entirely new market? Was it the rise of interest in Zettelkasten that caused the rise of PKM tools, or was it the other way around?

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What’s wrong with…?

We see patterns, create patterns, and think in patterns. Looking back at what I’ve written through the years in this blog, I see a macro pattern I can call, for the lack of a better name, the “What’s wrong with…” pattern.

The object is usually some common practice or a discipline that has established certain norms and stabilized them through training, certification, and tool design. It could also be a mainstream way of thinking about or doing something. Its object is usually taken for granted, rarely questioned if at all. If I find it harmless or slightly problematic, I don’t bother writing about it, but when it’s more fundamental and detrimental, then there is motivation.

So, this will not be a normal post but rather a signpost, a collection of pointers to posts with that pattern.

“What’s wrong with” is actually in the name of one article, What’s wrong with best practices. It could’ve been in titles of many more. Yet, it’s good to be careful here because the context is important as Tim Minchin convincingly reminded us with his song Cont.

The non-exhaustive list will look like this:

What’s wrong with…

And the last post about requirements may sound in praise of principles, so I should probably write about what’s wrong with principles. Spoiler: nothing if they a descriptive, but almost always they are prescriptive.

The above list is not the full “What’s wrong with” list, but just that part that made it to the blog. Otherwise, my “what’s wrong with” list is longer. It includes platitudes such as “you cannot manage what you cannot measure,” “culture eats strategy for breakfast,” influential averages like “per capita GDP” in economics or “personas” in design thinking, “Agile” and “SAFe,” “mental models” and many more. Some of them I have covered in Essential Balances, but only briefly, not to distract from the main focus of the book.

Data-centric project requirements?

Several times last week, in different circumstances, I was asked a question containing these three words or their synonyms. That’s not new. It happened previously. But this concentration triggered the write-up that follows. Nothing original and neither is the reason to write it:

Everything that needs to be said has already been said. But since no one was listening, everything must be said again.

— André Gide

Let’s first clarify what is data-centric and then see why it doesn’t go well with project and even less so with requirements.


What is data-centric?

The short answer is in these three1Check out all five principles data-centric principles. principles:

  1. Data is self-describing and does not rely on an application for interpretation and meaning.
  2. Data is expressed in open, non-proprietary formats.
  3. Applications are allowed to visit the data, perform their magic and express the results of their process back into the data layer.

I find these three are the most important data-centric principles, but another reason for selecting them is that they are context-independent. The data-centric manifesto they are taken from is currently with an enterprise-only focus2 After the publication of this article, the scope of the manifesto was adapted, and now it includes the other two scales. . Yes, the problem they address is most severely felt – or rather not felt because of ignoring or misattributing the symptoms – in large organizations. Yet, what is behind these principles is equally important for personal information management and on the open web. Let’s go quickly through all three levels then, from big to small, and see what data-centric means for the world wide web, for corporate IT, and then for personal information management.

The web was designed to be a decentralized system where the agreement on a few standards, basically HTTP and HTML, enabled free choice on just about anything else. People were finally free to express themselves and to choose from where and how to get information. They got free to innovate on building new browsers, websites, and whatever web applications and services they can think of. A system like this, with a self-maintained organization, can work well and have a natural tendency for virtuous cycles. In other words, it can amplify goodness and develop its own immune system for whatever threatens its viability. All it needs is to have the right kind of enabling constraints, for example, the standards I mentioned above, and to allow autonomy of all subsystems. This is the balance between autonomy and cohesion. It works for animals, people, tribes, organizations, society, and a socio-technical system like the web.

So the web flourished as a decentralized system, where people were free to choose and create more choices. And then one day the platforms appeared. They offered good and free services. Or at least they looked good and free at first. In reality, they were (and are) neither good nor free. The platforms are not nearly as good information providers as it was the decentralized web before them. What we see is not what we are looking for, but what their algorithms decide to show us. And the services of these platforms are not free. Quite the contrary. We pay with our data, and we pay twice. Once by being their content providers and a second time by giving them our personal data. Importantly, we don’t give them only our current personal data but also future ones, by allowing them to track our online behaviour. Who’s them? I’m talking of course about IT giants like Google, but the best example of extreme centralization and lock-in is Facebook3This has many facets. Facebook can be looked at as a very successful aggregator or as a prime example of a new form of capitalism.. In this way, the web, a decentralized system, shaped by the users, turned into a hyper-centralized system, shaped by a few powerful corporations4The centralization of the web is not only about the content but also about the infrastructure. The convenience of the cloud increased the dependency of both individual users and companies on the strategy and fate of a few powerful providers, namely Amazon, Microsoft, and Google.. It also formed users’ expectations. In 2019 Facebook and Google announced that it was now possible to copy images from Facebook to Google Photos. That’s the new norm for innovation. Only a few people noted the absurdity. As Ruben Verbourgh pointed out, 50 years after being able to send video signals over a distance of 380,000km, we celebrate that we can finally move a photo by 11km (the distance between Facebook and Google headquarters). A bit dystopian, isn’t it?

Yet, the problems with this centralization are not widely understood. For example, very few people realize how platform-based political propaganda works, and that’s why it works so well. Even fewer relate it to the hyper-centralization of the web. Same with fake news and so on. Maybe the least understood of the damages is how it suffocates innovation. It’s easy to illustrate. Even when you use Google for product search, where it should excel after so many years of work, huge investments, massive feedback, and the use of language models with trillion parameters, it’s really lame. Try searching for a bike below a certain price and certain weight. You’ll get results for bikes above that, but okay, then you can fix that using the shopping filter. Currently, that will not allow you to specify the weight even though it’s available in most technical specifications published online. But even if they add it at some point, the final selection will still exclude the majority of the offerings by smaller companies. As a result, you can’t get an answer to this simple question.

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  • 2
    After the publication of this article, the scope of the manifesto was adapted, and now it includes the other two scales.
  • 3
    This has many facets. Facebook can be looked at as a very successful aggregator or as a prime example of a new form of capitalism.
  • 4
    The centralization of the web is not only about the content but also about the infrastructure. The convenience of the cloud increased the dependency of both individual users and companies on the strategy and fate of a few powerful providers, namely Amazon, Microsoft, and Google.

Roaming through contexts with Roam: How I use it

This is the last, 5th instalment on Roam. Here I’ll share how I use it. This part will be easier to write than some of the previous ones. What won’t be easy is to keep it short.

Here are the links to the previous post in the series: Part 1: what is it, Part 2: Distinction, Part 3:Self-reference, and Part 4: Organization.

Migrating from Evernote to Roam felt like going backwards and forward at the same time. Before Everone, I used to use Zim. In Zim creating a new note from within a note and backlinks were standard features from the first release1Evernote is lacking them to this date, 17 years after its launch. That’s why it felt like going backwards. And it felt also like a big leap forward because Roam changed the game not only on note-taking but on personal knowledge management in general.

The main difference is that conceptually Roam treats the data as a graph. I’m not referring to the graph visualizing how pages are linked by references. This view shows only a small part of the graph, hiding the main element, the block. Blocks in Roam are basically paragraphs and other content chunks with unique identifiers. Blocks are not something RoamResearch came up with. Many content management tools, for example, WordPress, refer to the content components as blocks. But Roam pushed that idea a few steps further by allowing blocks to quickly be nested, referred to, embedded, created from a piece of text in a block, appear in the sidebar, being searched and queried. Block capabilities can be extended and it has been, beyond what I thought was possible. Yet, for me, the most important thing is that blocks, along with the special kind of block called “page”, are the nodes of my graph.



To get the most of my graph, I follow certain conventions and practices. As I explained in detail in Part 2, creating a page reference is making a distinction. It is followed by further distinctions. For example, I may create a reference to a named entity such as Paris, Athens, and Alice. In the context of a block, I know if I mean Paris the city, or Paris the street, or Paris the square, or Paris the cafe. I also know if I mean Athens the city or Athens Research, the open-source tool, inspired by Roam. I know that Alice is a person, and I know that I meant Paris the city, and Athens the tool but I want to let my graph know that as well. To query my graph, just like when querying Wikidata or DBpedia, it becomes very important to know the type of a thing. That’s one of the reasons to have a knowledge model, an ontology. Continue reading

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    Evernote is lacking them to this date, 17 years after its launch

Roaming through contexts with Roam: Organization

There are such kinds of tools which, when you interact with them, an organization emerges that modulates the interaction. That organization takes on a life of its own. The design and affordances of some tools for thought enable the emergence, persistence and adaptability of such an organization.

This is the fourth out of five posts of the series on Roam. The first part was about what is Roam likeThe second was about the powerful concept of distinction, and the fourth built on that to explain self-reference in Roam and why it is important. The current one is on organization. The series started in April 2020 with the intention to be published within a couple of months. That wasn’t to be as my workload tripled1pun not intended but is welcome once I realized it: it wasn’t just the volume that was three times more than before but also it was mostly work with triples  by that time. And although the productivity boost coming from Roam made it possible, cutting things was unavoidable and writing blog posts was one of the first things to go. Not go forever though, just wait patiently in the backlog.

Three things happened in the meantime. One, I gathered more experience working with Roam and more observations on how that structural coupling works. Second, my book on what makes organizations work was published in November last year. This means the current essay will be shorter than intended and the curious readers are invited to dive into more supporting arguments and details there. And third, the ecosystem changed. Now, apart from Roam, there are personal knowledge graph tools like Logseq, Athens, Obsidian, Kanopi, Codex, Foam, and Dendron, among others. They all have, in both similar and different ways, systemic properties that enable the interaction with the tool to be like with a living being.


Roam is a tool for organizing. You can use it to organize your day, project, research, knowledge, life. But there is also another organization, emerging from the interaction it2That doesn’t apply only to Roam, but also to some other PKG tools as those mentioned above.. This organization behaves as if it cares about its viability. It belongs to a class self-sustained systems, where the most typical organizations such as companies, government agencies, and NGOs belong to. Not surprisingly families, clubs, music bands, teams are also self-sustained systems of this kind. But it may seem strange to you if I put habits3Egbert, M., & Cañamero, L. (2014). Habit-based Regulation of Essential Variables. Artificial Life Conference Proceedings 14. MIT Press. and emotions4Colombetti, G. (2014). The feeling body: Affective science meets the enactive mind. The MIT Press. in the same class. There are good reasons to do so. Some say hurricanes are something like that too. A friend of mine also sees some dishes as self-sustained systems.

Self-sustained organizations emerge also in simple situations when we are trying to pass each other in a narrow corridor, but that lasts only seconds. Or during meetings. We tend to see meetings only as events. But they are social species, having a mind of their own, emerging from the complex dynamic of intentions, preferences, agendas, personalities, emotions, egos, and tribes, acting within the constraints of norms, rituals, and rules. This interplay between enabling conditing and constraints is always present in self-sustained organizations.

Do you need to interact with a software application for personal knowledge management to enable a self-sustained organization to emerge? No. Luhmann saw his Zettelkasten – not a software, just indexed cards in boxes – as his thinking partner:

As a result of extensive work with this technique, a kind of secondary memory will arise, an alter ego with who we can constantly communicate. It proves to be similar to our own memory in that it does not have a thoroughly constructed order of its entirety, not hierarchy, and most certainly no linear structure like a book. Just because of this, it gets its own life, independent of its author.


Does it happen only when you interact with tools for thought like Roam? Certainly not. It will be a matter of future research to find out when this happens, how, and when interacting with what sort of applications. A type of application that most likely belong to this class are videogames.

[G]ameplay is argued as being the achievement of dyadic and reciprocal coupling between a player and the game. In this reciprocity, gameplay arises as autonomous organization that is both self-sustaining and precarious. Coordination and exploration are offered as constitutive principles of videogame gameplay.

The viability of all these autonomous organizations, habits, emotions, teams, companies, and the one emerging when we interact with interconnected notes, depends on three essential balances. Continue reading

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    pun not intended but is welcome once I realized it: it wasn’t just the volume that was three times more than before but also it was mostly work with triples 
  • 2
    That doesn’t apply only to Roam, but also to some other PKG tools as those mentioned above.
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    Egbert, M., & Cañamero, L. (2014). Habit-based Regulation of Essential Variables. Artificial Life Conference Proceedings 14. MIT Press.
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    Colombetti, G. (2014). The feeling body: Affective science meets the enactive mind. The MIT Press.

SASSY Architecture 2

I shared previously a short description of what is SASSY Architecture and a more detailed deck here. This is a shorter but more recent deck from my talk at the IRMUK EA Conference in 2019.

(if the slidedeck doesn’t appear, you may need to refresh)

Linked Data uptake

Linked Data is a universal approach for naming, shaping, and giving meaning to data using open standards. It was meant to be the second big information revolution after the World Wide Web. It was supposed to complement the web of documents with the web of data so that humans and machines can use the Internet as if it is a single database while enjoying the benefits of decentralisation1This is the balance between autonomy and cohesion – essential for any socio-technical system..

Today, we have 1495 linked open datasets on the web, according to the LOD cloud collection. Some among them, like Uniprot and Wikidata, are really big in volume, usage, and impact. But that number also means that today, 15 years after the advent of Linked Data, LOD datasets are less than 0.005% of all publicly known datasets. And even if we add to that the growing amount of structured data encoded as JSON-LD and RDFa in the HTML, most published data is still unavailable in a self-descriptive format and is not linked.

That’s in the open web. Inside enterprises, we keep wasting billions attempting to integrate data and pay the accumulated technical debt, only to find ourselves with new creditors. We bridge silos with bridges that turn into new silos, ever more expensive. The use of new technologies makes the new solutions appear different, which helps us forget that similar approaches in the past failed to bring lasting improvement. We keep developing information systems that are not open to changes. Now, we build digital twins, still using hyper-local identifiers, so they are more like lifeless dolls.

Linked Enterprise Data can reduce that waste and dissolve many of the problems of the mainstream (and new-stream!) approaches by simply creating self-descriptive enterprise knowledge graphs, decoupled from the applications, not relying on them to interpret the data, not having a rigid structure based on historical requirements but open to accommodate whatever comes next.

Yet, Linked Enterprise Data, just like Linked Open Data, is still marginal.

Why is that so? And what can be done about it?

I believe there are five reasons for that. I explained them in my talk at the ENDORSE conference, the recording of which you’ll find near the end of this article. I was curious how Linked Data professionals would rate them and also what I have missed out on. So I made a small survey. My aim wasn’t to gather a huge sample but rather to have the opinion of the qualified minority. And indeed, most respondents had over seven years of experience with Linked Data and semantic technologies. Here’s how my findings got ranked from one to five:

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    This is the balance between autonomy and cohesion – essential for any socio-technical system.

Roaming through contexts with Roam: Self-reference

It was early November 2020. I escaped for a long weekend to Tenerife, where I played tennis for the last time of what turned out to be a 5-month ban back in Belgium. It was over 20°C and sunny, two more things I was going to miss in the long winter of the second lockdown.

I’d been working since dawn on a big terrace overlooking the ocean.

It was a magical moment to see how the ocean emerged out of nothing, made all the more special by its synchronicity with my thoughts. I was writing a chapter note on George Spencer-Brown (GSB) for Essential Balances, which was to be published a few weeks later, for it was GSB who showed mathematically how everything could come into being out of nothing.

All I teach is the consequences of there being nothing. The perennial mistake of western philosophers has been to suppose, with no justification whatever, that nothing cannot have any consequences. On the contrary: not only it can: it must. And one of the consequences of there being nothing is the inevitable appearance of “all this”.

Now, a few hours later, I was immersed in work when I got interrupted by some birds’ cries. I lifted my eyes from the screen of my laptop and saw a couple of colourful parakeets that had just alighted in the palm tree in front of the terrace. But they did not hold my attention long. What did was not an exotic island bird but a boring city one that landed on the corner cap of the railing and posed in a way making the flat cap look like a pedestal. It was then that I remembered I started writing a series of posts about Roam, and published two of them, the next one to write being about self-reference. I took a photo of the bird, noted in Roam what it looked like to me, and posted this tweet:

Indeed it’s high time for another Roamantic entry. This is the third installment in a series of five. The first part was about what is Roam likeThe second was about the powerful concept of distinction, based on George Spencer-Brown’s Laws of Form. And it was the rigorous study of distinction that led George-Spencer brown embrace what was treated as an error by the western1That wasn’t the case in the East. See, for example, the logical system Catuṣkoṭi. philosophers and mathematicians before him − self-reference. Continue reading

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    That wasn’t the case in the East. See, for example, the logical system Catuṣkoṭi.