Networks

From transactions to meetings, every event happens at a point or duration in time. Successful investigations need to understand how those events unfold, and how they’re linked.

KronoGraph is the first toolkit for scalable timeline visualizations that reveal patterns in time data.

Our search needs, and in turn our browser history, are not being met with single query anymore. We move through a variety of sources with every new piece of information giving us new ideas and directions to follow. Without us ever knowing it, our search queries are constantly fluctuating.

...Our browser’s history should reflect our behavior on the internet and help us understand the process behind it. It is crucial to actually understand and question the way we use the internet, and without the suitable tools, it is not possible.

I find answers in maps.

Since writing [On Motivation] two years ago, I’ve thought a lot about this idea of nodal points. And just to be clear, what I’m calling a “nodal point” is just any “thing” in the world that has changed your trajectory. The easiest examples are the ones that I gave, but a nodal point could also be a person, it could be a friend, or a place, or just an idea. Anything that has a hand in shaping how you see the world.

I’m interested in this idea because I think on some level, the sum total of all of a person’s nodal points could be some kind of proxy for a personal identity. At the very least, it’s an indication of an individual perspective. Since writing this essay, I’ve thought a lot about this kind of personal intuition towards things: the radar that any person has that leads them to different points in their life.

In an ideal world, one’s own personal intuition or radar is the same thing as the force that motivates them.

The existing personal knowledge management tools are insufficient to help us process information, especially during web-based research.

The tree structure and unique file path inherited from analog metaphors encourage collection, not connection, of ideas.

They make it harder to reuse and cross-reference ideas, and easier to hoard information.

...Can building associations be more intuitive?
...Is playfulness possible?
...Can web discovery be an organic extension of the existing knowledge base?

Semilattice is a collection of system and interaction concepts for personal knowledge management tools.

Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.

In Obsidian, making and following [[connections]] is frictionless. Tend to your notes like a gardener; at the end of the day, sit back and marvel at your own knowledge graph.

When I design a piece of software, I start out by doing the obvious thing: sitting down and making a list of features I think it should have.

But in my mind, great software is not defined by its feature list so much as its feature matrix.

Software starts to become really useful not just when it hits a certain number of features, but when there gets to be a dense web of connections between features, that is, when each feature complements other features in the program.

...A great piece of software will have a dense feature matrix; that is, most features will interact somehow with most other features, and you’ll see a lot of check marks in the matrix.

Andrew Trousdale is a researcher and designer. His initiatives and projects bridge positive psychology, human-computer interaction, and the creative arts.

A work in process of mapping the creative coding community around the world.

The world’s emails, TikToks, classified memos, bank transfers, satellite surveillance, and FaceTime calls travel on cables that are about as thin as a garden hose. There are about 800,000 miles of these skinny tubes crisscrossing the Earth’s oceans, representing nearly 600 different systems, according to the industry tracking organization TeleGeography. The cables are buried near shore, but for the vast majority of their length, they just sit amid the gray ooze and alien creatures of the ocean floor, the hair-thin strands of glass at their center glowing with lasers encoding the world’s data.

I have reason to believe, which for brevity’s sake I will treat elsewhere, that the most complex class of processes and structures we humans can consciously prescribe, reduces mathematically to a tree. A tree has a top, bottom, left and right. Its branches fan out from the trunk and they don’t intersect with one another. They are discrete, contiguous, identifiable objects which persist across time. Trees are Things.

Software and websites, however, reduce to arbitrarily more complex structures: they are graphs. A graph has no meaningful orientation whatsoever. No sequence, no obvious start or end—at least none that we can intuit. It is better considered not as one Thing, but as a federation of Things, like the brain or a fungus network, or perhaps a composite artifact left behind from an ongoing process, like an ant colony or human city.

Here’s the scenario: I’m looking at a big system with several micro services, several data stores, a pub-sub queue, and integrations with several APIs. I have some questions I need to answer, ranging from “how much work would it take to replace one of the external APIs with a similar service from a different vendor?” to “which parts of this system are actually necessary to do some subset of its operations” to “what does this subset of services even do?” I don’t have access to anyone who designed or worked on the system. I do have some architecture documentation, but it’s for an older version of the system — I don’t actually know how accurate that documentation is.

In order to answer these questions, I want to make a map of the major components and how they call each other. My weapon of choice here is Obsidian, because of the way its visualization tools work.

...I’ll start with a list of the components I want to map...[Then] I turn that list into a set of notes, one for each service...[And finally,] once I’ve made that set of interlinked notes, I can switch over to graph view and see what’s basically a directed graph of the system.

This paper introduces a novel representation, called the InfoCrystal, that can be used as a visualization tool as well as a visual query language to help users search for information. The InfoCrystal visualizes all the possible relationships among N concepts.

My hunch is that digital Luhmann-ism really only provides dividends for a small population of academics and writers of non-fiction who need to cite references or make connections across disparate texts.

For the rest of us, just writing down notes is all that really matters. Any tool that allows you to compose and save text will do. It is the act of writing, not the act of linking or reading or revisiting, that clarifies thought and leads to insight. The rest is all superfluous.

If I had to guess where this is all going, I’d say that what an internet platform is actually has already permanently shifted. Instead of apps trying to dominate specific features — a platform for video, a platform for expiring content, a platform for connecting social networking, a platform for livestreaming, a platform for resumes — we’ve already entered a new era of online networks where they all will essentially offer the same services and instead, focus increasingly on specific demographics.

A Code Graph is a visual representation of a codebase as a Knowledge Graph that helps one explore entities in code (functions, variables, classes) and their relationships. By mapping out these connections, it becomes easier to understand the structure and flow of the code, identify potential issues, and improve overall code quality.

The concept of representing code as a graph data structure has its roots in the early days of software engineering when researchers explored ways to model and analyze program structure and behavior using graph-based techniques. Modern Code Graphs, incorporating Knowledge Graphs and Large Language Models (LLMs), are a recent development.

• Improved Understanding: Helps trace the flow of data through functions and identify interconnected components.
• Impact Analysis: Assesses the ripple effects of code changes, predicting potential issues before they arise.
• Autocompletion: Suggests relevant functions, variables, and types based on the current context.
• Code Search: Searches for functionalities not just by keywords, but by understanding the relationships between code elements.

Seamless connects familiar objects from everyday life into a three-dimensional network

Sze incorporates objects designed for human scale, such as tools for installing sculpture such as a ladder and a spirit level. Other components, like the tiny wooden bridges, could imply a miniature scale. The sculpture sweeps across the space in delicate curves, connecting the objects into a single larger construction. The spiralling structures suggest the double helix shape of DNA – molecules that determine the growth and reproduction of all living things.

Although titled Seamless, the work draws attention to the ‘seams’ of the museum’s architecture. Several rectangles are cut into the walls where the sculpture penetrates. They reveal the construction of the museum building and the functional spaces behind its pristine ‘white cube’ galleries.

Adopting a new app is the only way for most people to get new interfaces and features into their personal computing environments. This presents users with a funny challenge: surveying pre-made apps for the ones that, hopefully, match the way they think and work. But this is a surprisingly arduous process because apps often operate on their own silo of data, and they present a new, separate environment which must be learned and adopted. When that doesn’t work, people are stuck trying to use software that doesn’t think or work the way they do.

Alexander has been exploring the concept of an “itemized” OS, one that allows users to construct their own environment. In such an OS all of your digital things — emails, todos, notes, reminders, webpages, podcast episodes, and so forth — are “items” that sit in one, local graph. Users are then able to create new interfaces with the items that matter in their lives and work, or introduce items that bring new functionality to their overall environment (such as having a reminder item which can be added to any other item).

Nowadays, seemingly everyone seems to admit online life is getting worse, both in quality and how dynamic the web used to be. At the same time, we’ve seen big tech platforms and governments be more proactive about making the internet “safer” and more “truthful.” Yet, the problem practically remains the same, if not worse.

A City Is Not a Tree can provide us with some answers. As Alexander argued almost 60 years ago, our minds are inclined to categorize the world as a tree, but an organic society and city actually resembles a semilattice. And just like with a city, organizing the internet like a tree stifles it completely.

In my puzzle collection, there are many games in which you have to connect points together by edges, making a graph, and the puzzle rules say you must avoid making any loop in the graph. Examples are Net, Slant, and some configurations of Bridges (although not the default one). Loopy and Pearl also care about whether there’s a loop in a graph, although those two are more subtle: your aim is to make a loop, and only wrong loops must be rejected.

Therefore, those puzzle programs need to be able to check whether a graph has a loop in it, in order to decide whether the puzzle solution is correct. If there is a loop, they also have to identify the edges that make up the loop, in order to point out to the player why their solution hasn’t been accepted.

Over the years I’ve been developing these puzzles, I’ve gone through an amazing number of algorithms for doing that job. Each one was unsatisfactory for some reason, and I threw it away, and moved on to the next.

I might by now have collected all the ways to do this job wrong! So I thought I’d write up all my mistakes, as a case study in all the ways you can solve this particular problem wrongly – and also in how much effort you can waste by not managing to find the existing solution in the literature.

Welcome to the Recycle Bin Project.

This is an initiative to keep files in flight.

We simulate over 2.4 billion trips across every urban area in the world to measure street network vulnerability to disasters, then measure the relationships between street network design and these vulnerability indicators.

...All else equal, networks with higher connectivity, fewer chokepoints, and less circuity are less vulnerable to disruption. But (for example) even the otherwise dense, connected Amsterdam is easy to disconnect by targeting its chokepoints (like canal bridges).

Historical facts, knowledge, or thinking are not isolated atoms in a formless cloud of information, as digitalized bits; on the contrary, they form a dense network of causalities and interactions. This endless interaction and intertwining is crucial in all creative thoughts, and it makes knowledge even seemingly far from one's discipline useful in one's own work.

I wish to create a kind of forest of thought in which the reader can become happily lost. The side note references are not given to show the extensiveness of my library; my numerous quotes are only intended to leave traces that the readers may follow beyond the contents of these condensed texts.

I’ve been using Obsidian to write a story, partly for fun, partly as a de-stresser, but also to try my hand at a different form of writing. And one feature that I adore is the graph view which shows the relationships between your documents.

...Each character should have some connection to every other in some form and this is a quick way to notice storytelling gaps. But this view is also helpful for me to not just write the story from start to finish, get mad, then bail. I feel like this story is now more like a codebase, where I can pop open one section of it and tinker and tweak it. Poke it until it’s connected to the rest of the code. I can refactor this one page, this scene, this weapon, this location—without having to worry about writing everything sequentially in chapters and without having to worry about writing high fiction where everything has to be beautiful.

Intelligent note-taking. Non-linear file management. Ideas and relationships visualized.

A note-taking tool for networked thought.

Scientific papers straddle two worlds. They’re thoughtfully crafted prose documents, but they’re also computational documents containing data analyses and visualizations. Today, the prose and computational parts of a paper often live in different environments and tools, which causes friction for teams of scientists.

...We wondered: what if one collaboration environment could host both the text of the paper and the data visualization code, making it seamless to edit them together?

The demo shows a web-based collaboration environment with provenance — information about how computed artifacts were generated from source material. By keeping track of provenance, we know when an output file needs to be rebuilt, and we know how to do it. We can also use provenance to create a map of the project.

I evaluate the importance of informal social interactions for invention by exploiting a massive involuntary disruption of informal networks from U.S. history: alcohol prohibition...After prohibition, previously wet counties had 13-35% fewer patents per year relative to consistently dry counties. The drop was largest 2-3 years after the imposition of prohibition and then rebounded as individuals reconstructed their informal social networks. I conduct several additional analyses that suggest the observed drop in patenting was driven by the disruption of informal social networks. Using data on inventors' identities and collaborations, I show that individuals who were successful inventors before prohibition became relatively more likely to struggle to invent in the social network that evolved in response to prohibition, and that the new social network led to a change in the direction of inventive activity.

Build ideas mindfully.

Save content, create collections, and connect ideas with other people.

I love the way the web still works without any social media influence. Here's the internet rabbit trail that led me to creating this post:

1. I was adding a link to omg.lol, a blog and email hosting service that's cute AND easy AND (relatively) cheap, to my newsletter.
2. While browsing their help and info page, I saw that they offer a /now/ feature that lets you update the world on what you're working on, reading, watching, etc... now. Old school internet at it's best.
3. I clicked through to the omg.lol /now garden which has examples of how people are using /now to update the world.
4. I randomly picked Rebecca Owen's /now page.
5. Then I clicked back through to her omg.lol page to see how she was using it.
6. I saw she had a blog, so I checked that out.
7. The most recent post on Rebecca's blog was one called Default Apps 2023. That's clickbait-up-arrow.gif material for me.
8. She had included a link to an episode a podcast called Hemispheric Views, and this defaults page.

Which is how I got around to posting a list of my defaults. No Meta / Twitter / TikTok needed.

HyperCard is a programming environment that can create applications as diverse as utilities and games by linking “cards” arranged into “stacks.” Commands are executed through a natural-language scripting language called HyperTalk.

The software has been phenomenally successful and highly influential. But Atkinson feels that if only he’d realized separate cards and stacks could be linked on different people’s machines through the Net — instead of cards and stacks on a particular machine — he would have created the first Internet browser.

I have realized over time that I missed the mark with HyperCard. I grew up in a box-centric culture at Apple. If I’d grown up in a network-centric culture, like Sun, HyperCard might have been the first Web browser. My blind spot at Apple prevented me from making HyperCard the first Web browser.

...I thought everyone connected was a pipe dream. Boy was I wrong.

I sometimes like to use the term "weave the web" to describe people who publish on their personal website. While web-themed, "weave the web" speaks only to one aspect of the web: its interconnectivity. Internet gardening evokes thoughts of the other side of the web: where you are on your own land, cultivating the thoughts on your mind. Letting ideas grow.

We would need a system that enables people to:

• Publish a list of books they would be willing to discuss with other people to the open web. Antilibraries – collections of books you haven't read yet but would like to read – are particularly well suited to this proposition.
• See which books people in their social network want to discuss, and/or subscribe to other people's lists
• Be notified when 4+ people in their network have the same book on their discussion list – possibly via an email thread?
• Coordinate and schedule a time to read and discuss the book with that group.

Can we use GPT-3 (or its coming descendants) to relieve people of the burden of communicating their ideas, so that they can invest more energy in producing them?

...What I am doing right now, writing this essay, is, technically, a linear walk through the network of my ideas.

That is what writing is: turning a net into a line. But it is also very concretely what I do, since I have externalized my ideas in a note-taking system where the thoughts are linked with hyperlinks. My notes are a knowledge graph, a net of notes. When I sit down to write, I simply choose a thought that strikes me as interesting and use that as my starting point. Then I click my way, linearly, from one note to the next until I have reached the logical endpoint of the thought-line I want to communicate.

...A reader-generated essay is what you get when you can go into someone else’s knowledge graph and make a linear journey through the network, while GPT-5 generates a just-in-time essay that is human-readable. It would be like going on a Wikipedia spree, except that the posts are written the moment you read them, based on facts encoded in a knowledge graph, and the user interface makes it look like you are reading a single, very long, and meandering essay.

I started thinking about all the other important “nodal points” (I don’t know what else to call this) of people, places, books, albums, websites, etc. that all played a part in shaping who I am as a person and what I think is important. These points are a combination of seeking things out myself and getting a recommendation that felt like it was actually for me. A mixture of both passive and active knowledge acquisition.

ultimately, it's the totality of those “nodal points” that indicate one’s own unique perspective. It doesn’t matter if you specifically sought out the nodal point or not, it’s the recognition that counts. When you encounter a piece of life-changing information (no matter how large the change part is), you are simultaneously discovering and creating “yourself,” becoming incrementally more complete. Your perspective (where your gaze is directed) is made up of a meandering line through these points. Learning (or maybe some precursor to learning) is a lot about developing the intuition to recognize when something you find in the world is going to be a nodal point for you.

Some of the most rewarding features to add to products are ones that don’t increase surface area, but increase depth.

This is how you continue to make a product a whole lot better without it feeling like it got a whole lot bigger.

Basecamp’s new References feature is a great example of this.

Barely any surface area — just a subtle tab down by the comments section. It’s almost not even there. Easy to ignore if you aren’t interested, but click that tab and a whole world of connections opens up. That’s the depth.

All [of a] sudden you can see how this is related to that, who’s referenced it across the entire system, how recently it’s been discussed (is it “alive” or “dead”), and where the energy is around the topic.

Surface area vs. Depth. An important thing to internalize when designing products.

I think LinkedIn has a unique opportunity - a cultural moment around work, coupled with a unique proposition: real networks and real utility.

What if LinkedIn positioned itself not as a professional network or social network but as a learning network. A personal learning network for every user - centered on their personal development.

Knowledge is not an accumulation of facts, nor is it even a set of facts and their relations. Facts are only rendered meaningful within narratives, and the single-page document is a format very conducive to narrative structure. The hypertext books that have gained popularity (I’m thinking here of Meaningness.com) have largely conformed to this in two ways: 1) there is an intended reading order, and 2) the longer essays within the project do most of the heavy lifting in terms of imparting the author’s perspective to readers.

On the other hand, the notion of the “document” that is intrinsic to web development today is overdetermined by the legacy of print media. The web document is a static, finished artifact that does not bring in dynamic data. This is strange because it lives on a medium that is alive, networked, and dynamic, a medium which we increasingly understand more as a space than a thing.

To boil it down to its core, there exists a massive collection of documents, distributed over millions of nodes, through which a separate collection of billions of people wish to conduct a guided search.

A significant portion of these nodes cannot be trusted to deliver suitable content, as such the rest of this note will assume we are working within a malicious risk model.

The current front runner solution for this problem is a collection of centralized services that actively crawl some subset of nodes, index the content, and permit searches over that index - usually in exchange for both search history data and the opportunity to substitute paid advertisements for
search results.

This state of affairs has resulted in a large scale privacy and incentives problem for search, and an interest in alternatives that bring about both better privacy and better search results.

What is this obsession with tracking down the source of things, anyway?

...Maybe it’s about the journey: tracking the original source means following a breadcrumb of links. Every stop along the way is also a fork in the road, except in this case the fork is really a node connected to, potentially, hundreds of hundreds of other nodes. And sure, you can keep on the path to the destination, but you can also take a detour, or two, or a hundred.

...And then, maybe you write about what you saw and the connections you made, and add another dot to that ever expanding knowledge graph.

Effective writing stems from intelligently connecting the dots between the concepts you understand and can articulate. It stands to reason, then, that in order to generate more creativity you must not only add to a knowledge base, but deepen and expand the number of connections within the totality of the network. By establishing and explicitly mapping your knowledge, you allow yourself the freedom to remix information. You will often find that solutions come from previously unsuspected fields or topics—proving to be analogous in some shape or form.

The importance of diversity is not so much the number of elements in a system; rather it is the number of functional connections between these elements. It is not the number of things, but the number of ways in which things work.

Each pattern depends both on the smaller patterns it contains, and on the larger patterns within which is is contained. Each pattern sits at the center of a network of connections which connect it to certain other patterns that help to complete it. It is the network of these connections between patterns which creates the language.

Do I need to know the precise polygonal geometries of Los Angeles and the University of Southern California to assert that the latter is within the former? No. My mind contains no such precise geometric model of points and lines, yet I know that USC is in Los Angeles. When humans reason with the real world, they focus on its objects, relations, and processes—rather than starting with geometry—because these are the keys to understanding and explaining the real world. Our GIS tools, however, usually do the opposite. Built from the geometry-up around the legacy logic of traditional cartography (geometries and layers), most GIS tools today are restricted by that legacy’s limited ability to model objects, relations, and processes. A representational tension thus exists in GIScience between being a geometric information science versus an ontological, relational, and processual information science.