71–80 of 209 posts
One of the best examples of the semantic web was Daylife[1], and they wound up being "acquired" by two bit players[2] that figured out how to monetize things better.. :-/
[1] https://en.wikipedia.org/wiki/Daylife
[2] https://techcrunch.com/2012/10/17/content-licensing-service-...
Basically any form of structured data, be it in XML or JSON, served through some channel of data, is everything people need. There is no benefit in further standardization. Simple, informal standards work better than monstrous specifications that nobody ever bothers to deal with properly. The most important part is reducing friction, that's why JSON is the most successful format despite its shortcomings.
Serialization is not the hard part.
The semweb community was obsessed with ontologies and OWL and schemas and taxonomies. If we can just break the problem down enough, the logic went, then systems will be able to infer new data about the world. But it never worked out that way.
Eventually you just have to write some code. If you have to write code anyway, all the taxonomies and RDF in the world aren't helpful (indeed, they're almost certainly the least efficient way to model the problem). You just scrape the pieces of knowledge out of whatever JSON, HTML, or whatever else and glue them together with the code. You don't need the all-knowing semantic web, you just need a .csv of whatever tiny piece of it you care about.
I have a distinct memory of trying to sell someone on the startup I was working on, a SPARQL database. I was pitching RDF as a way to model the problem, but eventually the person I was pitching just said "well, we can just outsource the scraping to our eastern european devs and put it all in one big table." I had a kind of "oh my" moment where I realized that the startup was never going to work: in the real world, you just write code and move on. Taking part in the great semantic knowledge base of the world doesn't matter and isn't needed.
The other end of semweb, the "machine-readable web", more or less came to pass. schema.org, opengraph, and that sort of thing did 99% of what the semweb community wanted at 5% of the effort. The fact that all of that data is not in one giant database doesn't really matter to anyone; you rarely care about more than 2 or 3 web pages at once.
Every few months my mind circles around that topic. I think it won’t work if the underlying transport/presentation is „the web“ (i.e as in Web 2.0). Instead of decorating semantics/hints around the actual information mostly for SEO reasons it should work the opposite: using all available semantic hints and information bits there already are to create new information by aggregating and putting things in a new context.…
You will find that:
A) It's probably not that valuable
B) None of the hard problems are technological
Earlier quoted context omitted.
Yeah, semantic web really hacked the brains of academic-facing bureaucrats. It fell into this giant gap between what administrators don't know about business and what they don't know about technology... a gap big enough to shove every utopian idea about "an effortlessly integrated, data driven society" into. There's no such thing as "right" way to represent any given data stream, just ways that are more or less suita…
'There's no such thing as "right" way to represent any given data stream, just ways that are more or less suitable to specific tasks and interests.' My core objection to "the Semantic Web" is the non-existence of "the Semantic". There is no way you can get everyone to agree upon a universal "semantic", and if you can, which you can't, you can't get people to accurately use it, and if you can, which you can't, you can…
It's really too bad that XML+XSLT didn't take off as the "replacement" for HTML. Before you recoil in horror hear me out... Web pages are a giant mess of content and presentation, and CSS doesn't really help much. XML is at least a way of describing data in a meaningful way. , , , etc. XSLT provided a way of formatting XML in the browser . Sure the internet would still be full of inconsistent content structures, but…
I thought Freebase [1] was the most promising "Semantic Web" technology, with a powerful query language (MQL) and an application platform called Acre [2]. I'm biased because I worked at Danny Hillis' adjacent company, Applied Minds, and met with the Freebase folks to talk about graph databases. I went to one of Freebase's Hack Days, and I could feel the energy around building applications on a semantically-aware glob…
First, there is no universal "semantic". The meaning of things is ambiguous, and given a broad enough pool of people and cultural contexts, it becomes nigh impossible to converge on a single consistent model for individual terms and concepts in practice. A weak form of this is very evident in global data interchange systems and implementations, and the Semantic Web took this bug factory and dialed it up to eleven. In short, the idea of the Semantic Web requires semantics to be axiomatic and in the real world they are inductive and deeply contextual. (Hence the data model rule of "store the physics, not the interpretation of the physics.") That said, it is often possible to build an adequate semantic model in sufficiently narrow domains -- you just can't generalize it to everything and everybody.
Second, implementation at scale requires an extremely large graph database, and graph database architectures tend to be extremely slow and non-scalable. They were back then and still are today. This is actually what killed the Semantic Web companies -- their systems became unusable at 10-100B edges but it was clear that you needed to have semantic graphs in the many trillions of edges before the idea even started to become interesting. Without an appropriate data infrastructure technology, the Semantic Web was just a nice idea. Organizations using semantic models today carefully restrict the models to keep the number of edges small enough that performance will be reasonable on the platforms available.
The Semantic Web disappeared because it is an AI-Complete problem in the abstract. This was not well understood by its proponents and the systems they designed to implement it were very, very far from AI-Complete.
As it is now, the one who provides the data is the one who pays for everything (production, storage, compute, bandwidth), while middleman search engines take all the money. What if the middleman was required to pay a fee to index the data ? For example build money transactions into the HTTP protocol, where web sites could automatically ask for a small fee in order to "see more".