Google translation:

The sheer quantity exceeds the possibilities of book publication, the complex, multidimensional structure of a networked information base cannot be reproduced in print, and finally the dynamic of a constantly growing and constantly correcting material does not fit into the rigid rhythm of book production, in which each expanded and corrected new edition is associated with an incalculable amount of effort. A book publication could only offer a snapshot of such a database, reduced to a specific perspective. This too can be very useful from time to time, but it does not solve the problem of publishing the entire material.

While the writing criticism of "dumping out one's zettelkasten" into a paper, journal article, chapter, book, etc. has been reasonably frequent in the 20th century, often as a means of attempting to create a linear book-bound context in a local neighborhood of ideas, are there other more complex networks of ideas which we're not communicating because they don't neatly fit into linear narrative forms? Is it possible that there is a non-linear form(s) based on network theory in which more complex ideas ought to better be embedded for understanding?

Some of Niklas Luhmann's writing may show some of this complexity and local or even regional circularity, but perhaps it's a necessary means of communication to get these ideas across as they can't be placed into linear forms.

One can analogize this to Lie groups and algebras in which our reading and thinking experiences are limited only to local regions which appear on smaller scales to be Euclidean, when, in fact, looking at larger portions of the region become dramatically non-Euclidean. How are we to appropriately relate these more complex ideas?

What are the second and third order effects of this phenomenon?

An example of this sort of non-linear examination can be seen in attempting to translate the complexity inherent in the Wb (Wörterbuch der ägyptischen Sprache) into a simple, linear dictionary of the Egyptian language. While the simplicity can be handy on one level, the complexity of transforming the entirety of the complexity of the network of potential meanings is tremendously difficult.

Use Follow TCP Stream to display HTTP response chunks

I do like the framing of folgezettel as a benefit with respect to user experience.

There is a lot of mention of the idea of trees within the note taking and zettelkasten space, but we really ought to be looking more closely at other living systems models like rhizomes and things which have a network-like structure.

https://en.wikipedia.org/wiki/Actor%E2%80%93network_theory

I ought to dig into some of Bruno Latour's work which keeps popping up in some of my reading....

• This paper is relevant to understanding

  • cumulative cultural evolution
    • https://jonudell.info/h/facet/?user=stopresetgo&max=300&expanded=true&any=cumulative+cultural+evolution&exactTagSearch=true
  • social tipping points
    • https://jonudell.info/h/facet/?user=stopresetgo&max=300&expanded=true&any=social+tipping+points&exactTagSearch=true

• Learning

• it introduces me to a number of new useful concepts
  • cognitive advantage
  • cultural network analysis
  • more detailed understanding of memetics
  • cultural epidemiology

Network ideology as per Pierre Musso.

https://en.wikipedia.org/wiki/Pierre_Musso, French philosopher

Zapatistas and the internet, network of networks.

!- relationship between : Earth Commission and Science-Based Targets Network (SBTN) - Earth Commission results will be used to develop Science-Based targets - for businesses and cities

!- relationship with : Science-Based Targets Network

ngrok

ISO protocols

At one point, the Open Systems Interconnection model (OSI model) was the leading contender for the network standard. It didn't survive in competition with the more nimble TCP/IP stack design.

several key factors of attitude diffusion: 1. multiple, interacting attitudes 2. social influence between individuals 3. media influence

Hypothes.is + Wiki -> Global Knowledge Graph

[[Article: Six types of IoT network protocols]]

t Laurie Voss's crowdsourced set of examples of things that have structure & control in the form of the following: - centralized - hierarchical - federated - distributed - decentralized

Picture below: Link to tweet: https://twitter.com/seldo/status/1486563446099300359?s=20&t=C6z9xUF_YBkOFmfcjfjpUA

Possibly like Holochain (which is distinct from the blockchain architecture). Blockchain only seems helpful if you need all of the following: - a database - immutability - distributed data - decentralized & totally trustless - append only - cryptographically secure assurance

Confer Brandon Enright's provocative talk "Blockchain is Bullshit" for an elaboration of these features. The first 10 or so minutes is mostly uninsightful trolling, so the link takes one to his argument about the key features of blockchain.

AFAICT, Holochain eases the feature of "decentralized", although Laurie Voss suggests that it's better to think of Bitcoin & Ethereum as "distributed" (in both the structure & control).

In Voss' taxonomy, I suspect that Holochain's structure would be "distributed" (ie, "No total point of failure, all nodes work on shared goal") and control would be "federated" (ie, "Limited set of shared rules, multiple overlapping/conflicting rules below")

This might be achievable through Holochain application framework. One promising project built on Holochain is Neighbourhoods. Their "Social-Sensemaker Architecture" across "neighbourhoods" is intriguing

Jaron Lanier once gave a similar example. How weird it is that to have a conversation with a person, a third party has to be involved. Like a social network. Why not just have the conversation on your own domains? This also reaches out to the idea of webmentions and having conversations through your blog or website.

!- defining feature : modern humans - we build distributed networks and we do not solve problems to adapt to our environment individually, but collectively - most creatures solve adaptive problems individually - some species form superorganisms

黑客要学的网络知识

!- definition : citizen action network (CAN) !- question : rapid whole system change at community scale - Can CAN's scale globally for rapid whole system change? If so, how?

Cox, D. A. (n.d.). Social isolation and community disconnection are not spurring conspiracy theories. American Enterprise Institute - AEI. Retrieved March 8, 2021, from https://www.aei.org/research-products/report/social-isolation-and-community-disconnection-are-not-spurring-conspiracy-theories/

Citation: Kirkpatrick, Keith. The Road to 6G. Communications of the ACM, September 2022, Vol. 65 No. 9, Pages 14-16 10.1145/3546959

Although it is early in the commercial rollout of 5G mobile networks, countries, companies and standards bodies are gearing up for what will be in the next version—so called “6G” mobile network. There are already experimental allocation of high frequency radio bands and testing that has occurred at about 100m distances. The high frequency will mean higher bandwidth, but over shorter distances. There are experiments to make passive graphene reflectors on common surfaces to help with propagation. What may come is a convergence of 6G with WiFi 6 to support connectivity from body-area networks to low earth orbit satellites.

5 areas of vulnerabilities

1. Intercept calls and texts
2. Impersonate user identity
3. Track users
4. Conduct fraud
5. DoS users or network

For each of these types of attacks, vulnerabilities were found in RCS to exploit them.

Reenter attack - The DAO. Basically withdrawal calls before the end of initial execution.

indistinguishability problem and premissionless voting

k8s 网络手册

!- claim : examples of a good enough world * Universal Basic Income (UBI) * Blockchain * Offer network

Network effects can describe a broad variety of phenomenon. Is Katamari ball a better descriptor of this specific phenomenon?

How does one prioritize the richer quality Lindy library material that may be even more beneficial than things which are simply new?

Indyweb can increase traceability across the entire network through built in provenance mechanism.

https://designjustice.org/

Instructional Design Working Group - Book Club https://designjustice.org/events-1/2022/id-1stmeet

Scientific research demonstrating the beneficial impacts of being in a state of awe.

The public Indyweb is eminently designed as a public space for holding deep, continuous, asynchronous conversations with provenance. That is, if the partcipant consents to public conversation, ideas can be publicly tracked. Whoever reads your public ideas can be traced.and this paper trail is immutably stored, allowing anyone to see the evolution of ideas in real time.

In theory, this does away with the need for patents and copyrights, as all ideas are traceable to the contributors and each contribution is also known. This allows for the system to embed crowdsourced microfunding, supporting the best (upvoted) ideas to surface.

Participants in the public Indyweb ecosystem are called Indyviduals and each has their own private data hub called an Indyhub. Since Indyweb is interpersonal computing, each person is the center of their indyweb universe. Through the discoverability built into the Indyweb, anything of immediate salience is surfaced to your private hub. No applications can use your data unless you give exact permission on which data to use and how it shall be used. Each user sets the condition for their data usage. Instead of a user's data stored in silos of servers all over the web as is current practice, any data you generate, in conversation, media or data files is immediately accessible on your own Indyhub.

Indyweb supports symmathesy, the exchange of ideas based on an appropriate epistemological model that reflects how human INTERbeings learn as a dynamic interplay between individual and collective learning. Furthermore, all data that participants choose to share is immutably stored on content addressable web3 storage forever. It is not concentrated on any server but the data is stored on the entire IPFS network:

"IPFS works through content adddressibility. It is a peer-to-peer (p2p) storage network. Content is accessible through peers located anywhere in the world, that might relay information, store it, or do both. IPFS knows how to find what you ask for using its content address rather than its location.

There are three fundamental principles to understanding IPFS:

Unique identification via content addressing Content linking via directed acyclic graphs (DAGs) Content discovery via distributed hash tables (DHTs)" (Source: https://docs.ipfs.io/concepts/how-ipfs-works/)

The privacy, scalability, discoverability, public immutability and provenance of the public Indyweb makes it ideal for supporting hyperconversations that emerge tomorrows collectively emergent solutions. It is based on the principles of thought augmentation developed by computer industry pioneers such as Doug Englebart and Ted Nelson who many decades earlier in their prescience foresaw the need for computing tools to augment thought and provide the ability to form Network Improvement Communities (NIC) to solve a new generation of complex human challenges.

Explore this idea....

What does it look like quantitatively?

This is the part that interests me the most. So many workplaces, when they want to share ideas, immediately think of writing articles, delivering presentations, and recording podcasts or videos - we live in a world with so much content already, but we're obsessed with making more. Sometimes it seems to serve the creator more than the audience. But if we look at a 'Strength of Weak Ties' approach, we're probably more likely to share more information more widely if we create connections over content. (I know, I sound like a connectivist now.) If our ultimate aim in learning design is to share knowledge on pedagogy and technology, surely we would want to go with the methods that work best? See Roxå et al. (2011), 'Understanding and influencing teaching and learning cultures at university: a network approach', for the source of my obsession. https://doi.org/10.1007/s10734-010-9368-9

Kai Kupferschmidt. (2021, December 1). If you’re curious how likely #omicron is to have spread from South Africa or Botswana to different places, @DirkBrockmann and colleagues have done some interesting calculations based on the world aviation network from 08/2021 You can see that US seems a very likely destination https://t.co/OSnZ6ZNble [Tweet]. @kakape. https://twitter.com/kakape/status/1466107074585239568

Wulff, D. U., & Mata, R. (2021). On the semantic representation of risk. PsyArXiv. https://doi.org/10.31234/osf.io/eywjk

This is a great question and I ask it frequently with many different answers.

I've not seen specific numbers, but I suspect that the majority of Hypothes.is users are annotating in small private groups/classes using their learning management system (LMS) integrations through their university. As a result, using it and hoping for a big social experience is going to be discouraging for most.

Of course this doesn't mean that no one is out there. After all, here you are following my RSS feed of annotations and asking these questions!

I'd say that 95+% or more of my annotations are ultimately for my own learning and ends. If others stumble upon them and find them interesting, then great! But I'm not really here for them.

As more people have begun using Hypothes.is over the past few years I have slowly but surely run into people hiding in the margins of texts and quietly interacted with them and begun to know some of them. Often they're also on Twitter or have their own websites too which only adds to the social glue. It has been one of the slowest social media experiences I've ever had (even in comparison to old school blogging where discovery is much higher in general use). There has been a small uptick (anecdotally) in Hypothes.is use by some in the note taking application space (Obsidian, Roam Research, Logseq, etc.), so I've seen some of them from time to time.

I can only think of one time in the last five or so years in which I happened to be "in a text" and a total stranger was coincidentally reading and annotating at the same time. There have been a few times I've specifically been in a shared text with a small group annotating simultaneously. Other than this it's all been asynchronous experiences.

There are a few people working at some of the social side of Hypothes.is if you're searching for it, though even their Hypothes.is presences may seem as sparse as your own at present @tonz.

Some examples:

@peterhagen Has built an alternate interface for the main Hypothes.is feed that adds some additional discovery dimensions you might find interesting. It highlights some frequent annotators and provide a more visual feed of what's happening on the public Hypothes.is timeline as well as data from HackerNews.

@flancian maintains anagora.org, which is like a planet of wikis and related applications, where he keeps a list of annotations on Hypothes.is by members of the collective at https://anagora.org/latest

@tomcritchlow has experimented with using Hypothes.is as a "traditional" comments section on his personal website.

@remikalir has a nice little tool https://crowdlaaers.org/ for looking at documents with lots of annotations.

Right now, I'm also in an Obsidian-based book club run by Dan Allosso in which some of us are actively annotating the two books using Hypothes.is and dovetailing some of this with activity in a shared Obsidian vault. see: https://boffosocko.com/2022/03/24/55803196/. While there is a small private group for our annotations a few of us are still annotating the books in public. Perhaps if I had a group of people who were heavily interested in keeping a group going on a regular basis, I might find the value in it, but until then public is better and I'm more likely to come across and see more of what's happening out there.

I've got a collection of odd Hypothes.is related quirks, off label use cases, and experiments: https://boffosocko.com/tag/hypothes.is/ including a list of those I frequently follow: https://boffosocko.com/about/following/#Hypothesis%20Feeds

Like good annotations and notes, you've got to put some work into finding the social portion what's happening in this fun little space. My best recommendation to find your "tribe" is to do some targeted tag searches in their search box to see who's annotating things in which you're interested.

Creating links to one's own personal context can help one to both learn and retain new material.

Personalizing ideas using existing memories is a method of brining new knowledge into one's own personal context and making them easier to remember.

link this to: - the pedagogical idea of context shifting as a means of learning - cards about reframing ideas into one's own words when taking notes

There is a solid group of cards around these areas of learning.

Random thought: Personal learning networks put one into a regular milieu of people who are talking and thinking about topics of interest to the learner. Regular discussions with these people helps one's associative memory by tying the ideas into this context of people with relation to the same topic. Humans are exceedingly good at knowing and responding to social relationships and within a personal learning network, these ties help to create context on an interpersonal level, but also provide scaffolding for the ideas and learning that one hopes to do. These features will tend to reinforce each other over time.

On the flip side of the coin there is anecdotal evidence of friends taking courses together because of their personal relationships rather than their interest in the particular topics.

1. How do you get to the edge quickly?

I think this is where literature mapping tools come in handy. With such a tool, you can see how the literature is connected and which papers are closer to the edge of understanding. Some tools on this point include Connected Papers, Inciteful, Scite, Litmaps, and Open Knowledge Maps.

1. How do you do that across multiple fields?

I think this requires taking an X-disciplinary approach that teeters on multiple disciplines.

1. What do you do if the field seems misdirected, like much of psychology?

Good question. It is hard to re-orient a field unless you can find a good reason (e.g., a crisis) for a paradigm shift. I think Kuhn's writing on [The Structure of Scientific Revolutions(https://www.uky.edu/~eushe2/Pajares/Kuhn.html) may be relevant here.

What is striking about this request and EFF's argument against is how this goes against "common carrier" principles—although this phrase isn't specifically used. In the net neutrality wars, "common carrier" status means that the network pipes are dumb...they neither understand nor promote/demote particular kinds of traffic. Their utility is in passing bits from one location another in the service of broader connectivity. "Common carrier" is a useful phrase for net neutrality in the United States...as a phrase, it may not translate well to other languages.

Horita, Y., & Yamazaki, M. (2022). Generalized and behavioral trust: Correlation with nominating close friends in a social network. PsyArXiv. https://doi.org/10.31234/osf.io/xu8k3

I love that Johannes Klingbiel highlights having his own place on the Internet as a means to learn. While I suspect that part of the idea here is to learn about the web and programming, it's also important to have a place you can more easily look over and review as well as build out on as one learns. This dovetails in part with his third reason to have his own website: "to build". It's much harder to build out a learning space on platforms like Medium and Twitter. It's not as easy to revisit those articles and notes as those platforms aren't custom built for those sorts of learning affordances.

Building your own website for learning makes it by definition a learning management system. The difference between my idea of a learning management system here and the more corporate LMSes (Canvas, Blackboard, Moodle, etc.) is that you can change and modify the playground as you go. While your own personal LMS may also be a container for holding knowledge, it is a container for building and expanding knowledge. Corporate LMSes aren't good at these last two things, but are built toward making it easier for a course facilitator to grade material.

We definitely need more small personal learning management systems. (pLMS, anyone? I like the idea of the small "p" to highlight the value of these being small.) Even better if they have social components like some of the IndieWeb building blocks that make it easier for one to build a personal learning network and interact with others' LMSes on the web. I see some of this happening in the Digital Gardens space and with people learning and sharing in public.

[[Flancian]]'s Anagora.org is a good example of this type of public learning space that is taking the individual efforts of public learners and active thinkers and knitting their efforts together to facilitate a whole that is bigger than the sum of it's pieces.

Vega-Oliveros, D. A., Grande, H. L. C., Iannelli, F., & Vazquez, F. (2021). Bi-layer voter model: Modeling intolerant/tolerant positions and bots in opinion dynamics. The European Physical Journal Special Topics, 230(14–15), 2875–2886. https://doi.org/10.1140/epjs/s11734-021-00151-8

Edge Computing: What It Is and Why It Matters0 https://en.itpedia.nl/2021/12/29/edge-computing-what-it-is-and-why-it-matters/ Edge computing is an emerging new trend in cloud data storage that improves how we access and process data online. Businesses dealing with high-frequency transactions like banks, social media companies, and online gaming operators may benefit from edge computing.

Kan, U., Feng, M., & Porter, M. A. (2021). An Adaptive Bounded-Confidence Model of Opinion Dynamics on Networks. ArXiv:2112.05856 [Physics]. http://arxiv.org/abs/2112.05856

Kumar, A., Chowdhary, S., Capraro, V., & Perc, M. (2021). Evolution of honesty in higher-order social networks. Physical Review E, 104(5), 054308. https://doi.org/10.1103/PhysRevE.104.054308

Kwiek, M. (2021). The Globalization of Science: The Increasing Power of Individual Scientists. MetaArXiv. https://doi.org/10.31222/osf.io/gj4aq

Mazumdar, S., & Thakker, D. (2020). Citizen Science on Twitter: Using Data Analytics to Understand Conversations and Networks. Future Internet, 12(12), 210. https://doi.org/10.3390/fi12120210

https://www.mdpi.com/1999-5903/12/12/210

Mattei, M., Caldarelli, G., Squartini, T., & Saracco, F. (2021). Italian Twitter semantic network during the Covid-19 epidemic. EPJ Data Science, 10(1), 1–27. https://doi.org/10.1140/epjds/s13688-021-00301-x