I do get what you’re saying. The immersion between input and output works breathtakingly fluidly in Logseq, because it makes it so cheap to create, as fast as you create on the command-line and emacs, in fact, which are platforms with good track record of attracting the types of people that build sophisticated structures. Take XML authoring practice that evolved into YAML for instance. Well, Logseq could (also) be a Yaml editor and in a way, it almost is. One could argue that Markdown was also a response to difficulty authoring XML and JSON. I would personally favour RDF/XML or something like that as the backend language, or some serialisation strategy that stays loyal to Logseq’s simplicity, yet is capable of taking full advantage of the vast capabilities provided by OWL2.
When you put it in social context, well my belief is that platforms such as Logseq can serve as a way for independent organisms to converse effectively, at a level that has not yet been seen. What you’re after though, is what Elon Musk is trying to do with Twitter. So in all honesty, you may want to put your efforts in guiding that work. Twitter already gives you something super big, which is the global commoditisation of humans voting. Millions can systematically vote on a clearly-defined topic. Of course, the big issue there is fraud/duplicate detection and false identities, robots and what not. Getting rid of those is the big chuck of the work. The interesting fact about this is that one of the first tech companies that actually had to deal with this issue of fraud detection was, none other than PayPal led by Elon himself. I’m not an Elon fan or anything, merely trying to explain his way of thinking and stuff he may have planned for us. But mainly, how his work is close to what you are stating in your comment. Since you’re an artist by the way, thanks for sharing that info, you could start thinking about ways in which you can connect the power of Wikipedia/DBpedia to Twitter. There might be Logseq in between or not. But that’s the kind of thinking that allows to create order out of chaos, to create waves like cryptos do. Anyway, too deep for a Monday morning. But I’m here to help if you want to explore and I see that you have already created a thread. I’ll try to look into it further, too.
UPDATE: I wish Logseq’s core contributors also participated in this topic. I don’t know them unfortunately, but I’d like nothing more than to pick their mind on some of the adjacent markets they are exploring. At the end of the day, they are open source with investment from respected VCs, so I’m sure they might consider opinions of their community members. At the same time, I wonder where the strategic conversations take place, which to a degree, for me, also determines the level of openness they plan to implement in the mid term. And Discord cannot be the answer, I’m sorry. Synchronous communication for such deep convos are counterproductive to say the least.
UPDATE (completely off topic but since the thought arose from this thread, I decided to share it but it is not directly related to Logseq, per se, so apologies for being off topic):
One strategy that could help with fraud detection is to embrace the concept of a robot and start defining their status on something like Twitter. I mean, we’re starting to have people going around risking their well-paid jobs to say that a certain robot is sentient. Some things ought to be changing as a response to that. And recognising robots and being able to tell their lineage for the purposes of bookkeeping. Their lineage is key, this way we can count them appropriately. Some semantic work on reasoning about data. It’s been my job, only for the past 12 years.