Very interesting approach to teaching that sounds surprisingly sound in concept and execution. Students learn skills through playing Starcraft and reflect, discuss, explain etc. Great idea!

Address of the bookmark: http://www.technologyreview.com/blog/mimssbits/25626/

I’ll start with the simple conclusion: no. Oh alright. Yes. Yes and no.

Somewhat fancifully, language is sometimes described as a tool, but that’s not right either. It’s more like a toolset, a massive and interlocking collection of tools that can be disassembled, reassembled, aggregated and combined to create many things, including more tools and more toolsets. The word ‘and’ might be a tool, but it has no meaning until combined with others into assemblies that perform tasks and it is those assemblies that are the technologies, not the language per se. In extreme cases, language does real work in changing the world directly: by making a performative utterance like “I do” the tool has become the technology that performs the action itself. In most cases, however, it is to do with communication and, I think more significantly, sense-making. Words can be used in an indefinitely large, almost certainly infinite number of ways to achieve a probably infinite range of results and effects. Language thus leads to an infinite range of technologies. More than the computer even, language is the universal technology. We can use language to manipulate ideas, create and transform concepts, design, explore, analyse and more in order to achieve some goal or goals. We can use language to manipulate language, and we often do. We can construct things in language and use those constructions to make other constructions. In language, a single word can express the abstraction of a billion ideas. Add a second word and we change that abstraction utterly. This is a mighty powerful toolset.

Like any technology and more than possibly any other, it takes a great deal of time to learn how to use a language at all, let alone well. It is in many ways the fundamental human invention, hugely more important and fundamental than fire, the wheel or the Internet. We can be human without fire, but to be human without language is barely conceivable, at least when viewed in the general sense, There are a few individual humans without language (babies for instance) but, were lack of language to become widespread, we would no longer be human.

Languages don’t have to be verbal, of course: the advantages of verbal (and similarly sign) languages bring are also there to a greater or lesser extent in visual languages, musical languages, architectural languages and more. Words are not the only fruit by any means. However, the language of words is perhaps our oldest, most highly evolved and most flexible technological toolset and the richness of grammar and syntax it has evolved give it some large advantages over other languages we have invented. 

Language provides a toolset that, first and foremost, is not so much about communication as it is about thinking: it is an incredibly powerful, highly evolved technology to amplify and enhance thought. As we put thoughts into language symbols and connections we condense them and formalise them, allowing us to chain thoughts, hold more of them in our minds at once, build them into richer edifices. Just as writing is a thinking tool that lets us offload some of our cognition, allowing us to create longer and more elaborate chains of ideas that feed back and let us create new and enhanced ideas, language itself takes ideas, lets us abstract them and feed those abstractions back so that we can construct more thoughts, richer thoughts, more elaborate ideas. Learning a language might seem to be to do with communication but really, in learning to talk, we are learning to use a set of technologies that enable us to think. And from that ability we derive almost all other technologies. 

But, of course, the more obvious face of language is that of communication and here, too, that ability the technologies it enables give us, to symbolise, abstract and construct, also enables us to amplify and enhance the thinking of others: to act as a kind of hive mind in which the exchange of symbols enables the hive to build richer, deeper, more creative, more diverse thoughts, individually and collectively. Each new language act that we engage in with others is an opportunity to spread technologies, build ideas, learn, create, discover, enhance. It’s a wonderful virtuous circle that leads to an ever expanding explosion of knowledge in our species as a whole even though we, as individuals, are likely getting dumber and are very likely dumber than some of our distant extinct cousins. It is not intelligence that makes us so ‘successful’ as a species: it is how we use technologies to amplify that intelligence.

Benjamin Franklin famously defined our species as man the toolmaker – homo faber as distinct from homo sapiens. It seems to me that our sapience is at least as determined by our toolmaking, most notably in the form of language, as our toolmaking is determined by our sapience. Probably more so. 

I’ve been spending a lot of time over the past couple of years thinking about what we mean when we talk about ‘learning technologies’. Here’s a thought or two to conjure with…

Is an abacus a technology? I’d say no. It’s a tool. It is only when we use it for a purpose, utilising the principles that it embodies that it becomes a technology. We could use it to hit someone on the head and it would not be the same technology as when we use it to perform addition or subtraction, even though it would be the same tool. What makes it the technology we call an abacus is that we can use the tool to exploit ways that numbers work to perform operations on them.

What if we imagine an abacus in our heads? There is no physical tool, just a representation of that tool in our minds. I think I can do that. I can certainly perform mental arithmetic by imagining and remembering the various rows and beads of a simple abacus. I think that means that it is still a technology even though there is no actual tool present. In fact, I can do that without telling anyone that I have done so, so there doesn’t need to be any actual manifestation of the technology in any form save what goes on in my brain, and it actually works, just like a physical abacus. It is a lot harder than using an actual abacus though.

Taking that further, the ways that we are taught to add, subtract, multiple and divide are using pretty much the same underlying abstract principle as that of the abacus. Those methods are therefore technologies and, if I do them in my head, they remain so. Again, using paper is easier, but they remain technologies even if no writing is involved. So, a thinking process can be a technology. Interesting. Especially as it is possible to think of a computer as a glorified abacus in some senses.

Is this a universally applicable rule to all technologies? No.

If I imagine a four-wheeled, petrol-driven road vehicle in my head, is that a technology? Absolutely not. If it were, I would just be able to imagine driving from A to B and I would magically find myself transported to B, along a road, by the power of thought alone. The difference between the cases is in the phenomena I am exploiting in using the technology. For all that I wish it would, my brain is not able to directly exploit internal combustion, friction, momentum and so on. It might handle the rules of the road and driving skills on its own but much of the technological assembly that defines a car is beyond the power of thought to create. It needs metal, rubber, glass, manufacturing machinery, asphalt, amongst other things. The abacus is a technology for improving thinking and it therefore occupies a special position in the world of possible technologies inasmuch as the phenomena that it utilises and the uses to which we put it are all to do with thought and cognition. Which is, of course, quite a bit of what is involved in learning.

There are things that we call learning technologies that are all about thought, but there are also other things that are more car-like inasmuch as they cannot live entirely inside our heads. Foremost among those are technologies of communication (one sense in which a computer is absolutely not just a glorified abacus). If I get some time I’ll be writing more about that soon.

1. When did you begin blogging. What were your reasons?
   It depends what you mean by ‘blog’. I have shared my thoughts via the Web since around mid-1993 (around the time the Cello and Mosaic browsers were released) but until the mid-late 90s only on static web pages. I did it for the same complex of reasons that underpin most sharing I do with the world. I want to make a difference, gain social capital, give something back rather than simply consuming, archive my thoughts, share ideas on an open stage, it reminds me I am part of a bigger community, establishes a social identity (of a sort) etc. My first blog of that name was probably around 2000 – by that time I was using blogs in teaching as they are a great way to create an idea-centric dialogue, share easily, connect disconnected learners and are wonderfully motivating (until the spammers hit) so it seemed churlish not to do the same as my students. Before that I had created and used my own collaborative bookmark system (CoFIND) that was very blog-like in many ways, including comments, RSS feeds, tags etc, and that continued to feed into my blog until a couple of years ago. Part of the motivation for doing that was to use the system to see how it behaved and performed, and to encourage others to use it. I also really like to play with toys and technologies. It’s a curiosity thing.
2. Has your blogging changed over this time? How? (topics, focus, frequency, etc.)
   Very up and down indeed at multiple timescales. My blogspot (formerly blogger) blog has 9 whole posts starting from 2001, an average of one a year. I would post to my various CoFIND systems many times a week in the early 2000s, and have had flurries of activity, latterly on this site and formerly on my old Elgg site at the University of Brighton since around 2006. I still have phases of rabid activity, punctuated by pauses of a month or more. Sometimes the ideas flow and I have the time and/or motivation, sometimes they don’t and/or I don’t. The vast majority of my blogging activities relate to my research and/or teaching, and they nearly always have. 
3. How has blogging helped you with learning?
   Any writing that involves creating, analysing, constructing ideas and knowledge offloads the cognitive process and extends one’s capability to think: we don’t have to hold it all in our heads at the same time and can connect and organise many more ideas than we could without it. I often don’t know what I think until I write it and writing it encourages further thoughts. In that sense, because a blog helps to motivate the writing process without the same strictures of an academic conference or journal paper, it definitely helps me to learn on an ongoing basis.
   Blogs are a long way from being unconstrained in form and content – the simple fact that they are mostly public ensures that – but they offer liberties that more traditional academic forms exclude. They let me think and behave more like a journalist, which is fun as I can explore ideas that I might exclude from an academic paper because of justified fears they would be shot down in flames. The fact that it is for public consumption forces me to be a bit more careful about what I write and to reflect more, analyse more, correct more. That’s a learning process.
   The dialogues that sometimes ensue also help me to co-construct a shifting view of reality with others. Being able to get different perspectives, being encouraged to re-formulate and adapt ideas to explain them better, to argue, to clarify, all helps me to learn. It’s a bit like teaching which, as we all know, is the best way to learn.
   I also like the ability to easily flick through old ideas, comments, sites I have found that easily get forgotten and link them to new thoughts and ideas: it’s a variation on the same theme of cognitive offloading, and of course is an explicitly reflective process that helps both cement ideas and inform metacognitive introspection.
   Blogs also give me permission to sit back and think: it’s a bit like the value of going to a class or a conference, a large part of which relates to the simple fact that you have explicitly put time aside to think about something and engage with it. If we don’t have such formalised ways of making space to learn then we tend not to do it so much.
   And, naturally, I have also learned unbelievably large amounts from other people’s blogs – a major source of inspiration and a good source of information.  
4. What are the main reasons you have persisted in blogging?
   I research social computing systems for learning and use them in my teaching – it’s a recursive motivation amplifier for me with positive feedback loops all the way down the line.
5. How do you think your blogging activity will change in future?
   Greater connection and greater contextualisation. Here on the Landing I often bookmark things that I find interesting in a blog-like way as well as blogging. I also Tweet things that catch my eye pretty regularly, post things to the Wire, update things (rarely) at acadmia.edu, blog at Brighton and much more. Pulling it all together is a challenge, not because it is technically hard, but because of my increasing awareness of the need and want to provide different things for different audiences or the same audiences in different contexts. One of the major tools being developed for the Landing is based on this idea – that we have many different social, academic, work and personal contexts that we need to switch between very regularly and constantly. We already have the ability to choose who sees what: the next step is to allow people to select what is seen, how it is seen, according to context.
6. How has the Landing influenced your blogging?
   I am strongly aware when blogging here that I know some of the people who will read it very well, some quite well, some a little, some not at all. I am more aware than usual of the effects it will have on those I do know. Not that this always makes me sensitive or diplomatic! In some cases it actually gives me wicked pleasure to know that I will irritate some people and stir up hornets’ nests. In fact, I’m sometimes a bit disappointed when people I expect to have a contrary opinion don’t take up the bait. Contrariwise, I am also very aware of how supportive this community can be and both give help and receive it in many ways, academically, practically and emotionally. In both the stirring and the soothing there is an underlying dynamic that makes this very different from other social sites I participate in, and it is down to implicit trust, I think, brought on by explicit membership in this community. This is a shifting community of groups and networks with some shared goals, ideals and purposes and a shared sense of belonging and support, even amongst those we barely know, which binds in a way most social networks of a more general kind fail to manage. It is partly because other social networks are more commonly based on affinity and connection – we choose who we connect with in a very explicit way. That can be true here as well of course, but selected from a subset of the world that is that AU community. We have deliberately set default permissions for posts on this site (logged-in users) that mean we are mostly also connecting with others who we have *not* chosen to connect with but who are part of this closed and trustworthy community. This gives two big gains: the first is that we get diversity of beliefs, opinions, interests and so on that would not happen if we were only deliberately connecting with individuals via a personal network of friends. We would get more diversity if things were entirely public but what we would gain in diversity we would lose in trust (on the Internet, nobody knows you’re a dog). The second big gain is therefore that we know we are sharing with those we can trust and, in sharing, helping to further increase the trust and connection between people: to build trust we need to expose ourselves and our vulnerabilities, foibles, quirks and weaknesses. I think I have displayed quite a few of those aspects of myself on this site!
   I have found it fascinating and delightful to engage in dialogue with people from the AU community that I only slightly know or only know online. It’s tangibly binding and connecting. I feel more a part of a rich academic community than I did before, even though we only have a little over a thousand inhabitants so far. If I didn’t contribute something to that, I don’t think I would feel the same way. Contribution builds connection. And that’s another motivation to blog.

I am very sad that such a useful report as this was intended for military use but this is a very well researched discussion of stigmergy in human systems that provides an excellent grounding for anyone interested in the area. However, it feels a bit like using the results of Nazi eugenics experiments: useful knowledge, immorally obtained.

Address of the bookmark: http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U2&doc=GetTRDoc.pdf&AD=ADA440006

Excellent. One down, a few million to go, it’s time to end this barbaric, anti-learner practice. I exaggerate. Exams per se are not wrong and in some cases may be a very sensible way to accredit people – driving tests, for instance. I can even imagine ways that they might be constructively aligned with the learning intentions (sporting contests, for instance), though very rarely in an academic setting. But, like the lecture, it’s an idea of very limited applicability that has become a plague in our systems and it is high time that we had to provide a real, strong, learner focused justification for using them. And no, not the dumb old argument about knowing it is all their own work (palpable nonsense in most settings in higher education). And not the one about efficiency (whose?).

Address of the bookmark: http://harvardmagazine.com/2010/07/bye-bye-blue-books

I want to love Diaspora, I really do. It is entirely about an open, controllable and free social networking system. It is being created by ‘four talented young programmers’ (their words) who clearly have passion and enthusiasm, and its aspirations are quaint but highly admirable:

“We are 140-character ideas. We are the pictures of your cat. We are blog posts about the economy. We are the collective knowledge that is Wikipedia. The internet is a canvas – of which, we paint broad and fine strokes of our lives with. It is a forward extension of our physical lives; a meta-self comprised of ones and zeros. We are all that is digital: If we weren’t, the internet wouldn’t either.”

Sigh.

I want Diaspora to succeed. I share the ideals. I believe in the right of people to own their own data and data about themselves. I believe that that the only right way forward in this field is in distributed, modular and open technologies. I believe that there are many ways to do this and Diaspora might be able to exploit one or two of them.

And yet, ignoring for the moment the complete absence of anything tangible from the Diaspora team apart from a few chummy videos and vague hints they are working with a few familiar standards and protocols…

Mark Zuckerberg. Apparently he sees younger versions of himself in them and so has funded them. Actually, spooky though that is, I think the explanation is way more sinister than that. If (as I fear it will) it spectacularly fails or runs out of steam, the faithful lose a little more faith and Zuckerberg wins. If, as is also pretty likely, it slowly fragments and Balkanises, the effect is the same – and the opportunity to introduce a little Facebook integration poison to make that even more likely is one Zuckerberg will be unlikely to miss. If it is successful, then he has the ties and leverage to make Facebook an integral part of it all, which will allow him to claim both openness (ha) and revenue.

I think Zuckerberg must know that Facebook in its current form is cruising towards eventual meltdown. The brilliant cold exploitation of Reid’s Law and Metcalfe’s Law that makes it so successful is also what makes it unsustainable in the long term as long as it stays closed and centralised. It may have another half billion users to go before it finally breaks (right now it’s hard to see how without a lot of restructuring, but there are some very smart people working in that company who will probably find ways to forestall the inevitable collapse for some while longer)  but, at some point, if it is to grow further it *has* to move to a more variegated and distributed model, to become part of a broader ecosystem with greater diversity and differentiation. If he can influence or maybe even control that ecosystem at the basic level of its virtual physics, he wins. Even if not, in the best case scenario that Diaspora gains traction and comes to compete or even dominate, the opportunity to study the enemy from the point of inception will put Facebook in a far stronger position to react and counter-attack.

I’d also love to know what they signed away to him when they took that money.  I hope it was nothing.

There is another possible motivation for Zuckerberg’s apparent generosity though that is maybe the simplest: it diverts attention away from other initiatives that actually have good working code, have communities, have backing and have potential to succeed, such as:

• Noserub: http://noserub.com/
• One Social Web: http://onesocialweb.org/
• Appleseed: http://opensource.appleseedproject.org/

and many others (e.g. 6D, Kopal, DiSo). While a few are only a little more advanced than Diaspora (that barely exists outside the hype), many are way further on and some, like OneSocialWeb, have serious backing.

We need the innovative and open ideas like those that drive these four young programmers. We need the ideas they are borrowing and using even more. We need systems that are both open and controlled by their users at every level. But I fear Diaspora may not be the answer. The only thing that really heartens me about the ludicrously overblown hype it is attracting is that it draws more attention to what is wrong with the centralised cloud models, helping to drive people into more diverse and trustworthy spaces over which they can have some confidence in control of their data and trust in the guardians of them.

Address of the bookmark: http://www.joindiaspora.com/2010/08/26/overdue-update.html

In the past I have written about tags to which we attach some value. Once upon a time in the late 1990s I called these qualities – a means of describing the things that we find valuable in a resource that do not fall neatly into yes-no tag categories: funny, good for beginners, complex, helpful and so on. In recent years I’ve been calling them scalar tags, to reflect the fact that they carry a scalar value or weighting.

We need these things for a variety of reasons. In the first place, as it turns out, many of the binary-category, definitional, taxonomic tags that we use on many social systems are really nothing of the kind – they often relate to our opinions and feelings towards the things we tag which, by and large, are not black and white (they are also often about things that are relative to us and our context – such as ‘my family’ but that’s another issue). On some sites as many as 30% of all tags used can be about subjective qualities of things. Secondly, they have a really great practical value: if tags carry a value then they can be used to rate things in multiple dimensions. Instead of the traditional ‘I like this’ or star ratings that simply suggest something is more or less good or bad, we can use scalar tags to describe in what ways we like them. Thus, we create a kind of disembodied user model of the aspects of ourselves that are important in relation to what we are tagging. This, as it happens, is mighty useful in an educational setting because liking a learning object or rating it highly is not really the problem: we want to know why it is liked, in what circumstances, for what purposes. Standard high-low ratings can be useful for things about which we have fairly consistent feelings such as movies, books, music and so on but the thing about learning is that it changes us. This means that what we valued when we were learning something no longer has any value to us because we have already learnt it (at least, that is often the case).

It occurred to me yesterday as I was blogging about sets that there is a much nicer term for this kind of thing than scalar tags: these are actually fuzzy tags. Fuzzy tags are of course ideally suited to being considered in fuzzy sets. Fuzzy tags are not categorisations as such, they are ways of attaching a value to a tag that reflects its degree of membership within a set of such tags. 

Fuzzy tags are not unproblematic. It is fiendishly hard to create an interface for them, they are highly susceptible to the cold start phenomenon, it is difficult to find uses that give people a non-altruistic motive for using them, and it is hard to get the right balance between counting the number of tags and the values attached to them when presenting resources that have been tagged that way. Do you give prime real estate to those with a higher average value and, if so, how do you balance it so that a resource that has been rated highly by one person does not override one that has been rated even higher by some people but lower by others? Not even considering other problems like the fact people rate things relatively differently, issues of tag ambiguity, personalisation factors and much else besides, it’s a wicked problem with many viable solutions. 

If we can crack this problem (I have had a fair number of cracks at it already) then it opens the door to some interesting ways of looking at collectives. At the moment, we think of collectives as being a kind of human-machine cyberorganism that is formed from the actions of the crowd which are then processed to create something that has agency in a social system. What comes in the first page or two of a Google search is an implicit recommendation by the collective, because of the ingenious PageRank algorithm that underpins it. The big tags in tag clouds tell us what the collective finds interesting and suggests to us that we might find it interesting too (and we do – we are about 3-4 times more likely to click a big tag in a tag cloud than a small one).

Apart from in a few experimental systems (I think I’ve built most of them) collectives are a combination of machine intelligence and human intelligence, at least when they work well – they can equally combine mob stupidity and machine ignorance when they work badly. I think they can be a lot more useful when they also capture the affective stuff – human feelings and opinions as well as intelligence. This is about more than just good or bad feelings: it is about things that say what it is that affects us and how we are affected, as well as how much we are affected by them.  Fuzzy tags can give us richer folksonomies that reflect more of the diversity, hopes, interests and intentions of the crowd than simple taxonomic tags. Plus, ‘fuzzy tag’ is a really catchy name 🙂

Orkut is trying to catch up with Elgg – it looks mighty familiar! Elgg has been doing exactly this for several years. We are creating a toolset that will go much further than this in enabling us to project personas. All Orkut (and Elgg) are doing here is filtering content based on access rights, which is a good start in recognizing the importance of the different facades we portray to others in real life, but not going anywhere like far enough. Our new tools will allow you to customise the look and feel as well – in effect, allowing us to have a different home page for every grouping of people we care about. It’s still in development but, if they pass the tests and trials, the tools will be coming to Athabasca Landing before very long.

Address of the bookmark: http://www.readwriteweb.com/archives/new_version_of_googles_orkut_separates_business_fr.php?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+readwriteweb+%28ReadWriteWeb%29

If you are not involved in social computing, social network analysis, sociology or similarly network-focussed disciplines and interest groups, this is going to seem like a pretty odd thing to make a fuss about (surely this is all common sense) so you might want to look away now…

Of late I have been increasingly concerned that the field of social computing is becoming dominated by a single world-view. To an increasing extent, research in the area has become dominated by various forms of network analysis, almost completely excluding the ‘social’ part of the term and anything else that avoids talking about abstract connections. Sometimes it is taken to ludicrous extremes. The other day I reviewed a paper that purported to show a small world network structure in what were described as ‘communities’ of people whose only connection was that they had used the same tags to describe content they had uploaded. They had not tagged anyone else’s uploads, only their own. There was absolutely no interaction between individuals, even in a mediated or artefactual way.  They were as much a network as all the people in the world that like cake.

I think nets are great. Network analysis is incredibly useful: it provides a powerful and flexible tool for understanding interactions between people and objects, lets us gain rich insights into complex interacting and dynamic systems. But nets are only a small part of what makes the field of social computing interesting.

The main part of social computing is, of course, made up of people and all their multifaceted wonderfulness (gotta love em), which should make up the chief object of study in any rational universe but that are generally simply treated as nodes in social computing conferences and journals (which are not rational universes).

However a significant other class of object in a social computing system is made up of sets of things – people, resources, dialogues, groups and so on. Things in sets (interchangeably, collections, aggregations, classes or bags) don’t have a particular order or internal connections between them like networks. They are defined simply by membership (or, in fuzzy sets, degrees of membership). They are just things we lump together for some reason. We could even have sets of nets. Or nets of sets if it makes sense or is useful to do so. Or sets of sets. The point is, sets and nets are useful in different ways and for different purposes.

Sets are powerful tools, especially in an environment (like this one) where people naturally fall into them – classes, research groups, centres, schools and so on. If I am designing a system for learning in an environment like The Landing, it is at least as important to me to know who is in a class as it is to know about the connections between them. It matters that I see myself in a group (set) of people who like to think about online learning. It matters that I can find them, not because they are a network but because they have defined themselves (through tags and profiles) as part of that set. I guess you could, it you wished, see the person-tag-person triad as a second-order net, but why bother when the most natural thing in the world is to call us part of the same set? It’s also computationally way easier and less expensive to do. Of course, once I have found them then first order networks come into play and that’s important too.

Sets are also wonderful for for lumping, averaging, summing, counting, weighting and rating, comparing and sorting.

Sets are perfect when we want to find something and we know what kind of thing it is – in structured data, especially.

Sets are great when we want to model the entities in the world, to find out what kinds of things are out there, how many there are, what they are like, what most interests them as a whole. The vast majority of databases in the world owe their forms to set theory and are composed of sets.

Sets are fabulous tools to filter not just things that are in a set but also the things that are not. 

Sets are just made for harnessing collectives: for instance, tag clouds are based on sets, not nets – typically, we count how many times a tag has been used and weight it in the list by popularity. Similarly, sets are far better than nets for voting: it is mighty interesting that a knows b and b knows c but, in some contexts, it is way more important that there were two votes for x and one vote for y. 

While we could (if we were particularly obsessive) see nets in everything from atoms to galaxies and model almost all sets as nets, we would lose something important in doing so. The fact that we can even use words like ‘atom’ and ‘galaxy’ means that we have already lumped things into categories – i.e. we have put them in sets.  Sets tell us about what matters to us, how we categorise, how we lump things, what the world is like to other people. Sets describe identity. We need sets in order to begin to have nets, as almost every net we are interested in is composed of sets: i.e. things we have no need to analyse as nets and that would have a different meaning and identity if we did.

I am part of the set of people who teach at Athabasca University. I may be part of a similarly named network too, but the fact that I perceive myself as a member, not just joined as a node in a network, matters. Those overlapping sets are as much what defines me as the connections I explicitly or implicitly form.

Nets are cool and most things can be seen in terms of them. But sets are cool, and most things can be seen in terms of them too. Clumping matters as much as connecting.