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A Review of the Semantic Web Field

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Re: A Review of the Semantic Web Field

#21
post #17
post #14

Earlier quoted context omitted.

> CURIEs and the depending standards alone are well over 100 pages. The curie standard is 10 pages long, and those "dependent standards" includes things like RFC 3986 (Uniform Resource Identifiers (URI): Generic Syntax) and RFC 3987 (Internationalized Resource Identifiers (IRI)) - which are well established technologies that most people should be familiar with. And you really don't need to read all of the referenced…

Familiarity isn't nearly enough if you want to implement something. Talking about RDF is absolutely meaningless without talking about Serialisation (and that includes ...URGH.. XML serialisation), XML Schema data-types, localisations, skolemisation, and the ongoing blank-node war. The semantic web ecosystem is the prime example of "the devils in the detail". Of course you can explain to somebody who knows what a grap…

> Talking about RDF is absolutely meaningless without talking about Serialisation (and that includes ...URGH.. XML serialisation), XML Schema data-types, localisations, skolemisation, and the ongoing blank-node war.

Don't implement XML serialization. The simplest and most widely supported serialization is n-quads (https://www.w3.org/TR/n-quads/). 10 pages, again with exaples, toc, and lots of non-normative content.

You don't need to handle every data type, and you can't even if you wanted to because data types are also not a fixed set. And whatever you need to know about skolemisation, localization, and blank-nodes is in the standards AFAIK.

> C'mon, rdflib is a joke. It has a ridiculous 200 issues / 1 commit a month ratio, buggy as hell, and is for all intents and purposes abandonware.

It works, not all functionality works perfectly but like I said I have used it and it worked just fine.

> rdflib.js is in memory only, so nothing you could use in production for anything beyond simple stuff. Also there's essentially ZERO documentation.

For processing RDF in browser it works pretty well, not sure what you expect but to me RDF support does not imply it should be a fully fledged tripple-store with disk backing. Also not really zero documentation: https://github.com/linkeddata/rdflib.js/#documentation

> > What are the alternatives?

> SIMPLICITY!

> But the great thing about it is that there could be dozens of equally simple systems and standards, and we could actually see which approaches are best, from usage.

Okay, so you roll your own that fits your use case. Not much use to me and it is not a standard. Lets talk again when you standardize it. Otherwise do you mind giving an alternative that I can actually take off the shelf to at least the extent that I can with RDF?

I am not going to roll my own standard, and if all the RDF data sets instead used their own standards instead of RDF it won't really improve anything.

EDIT: If you compare support for RDF to JSON schema, things are really not that bad.

Re: A Review of the Semantic Web Field

#22
My 10,000 ft layperson's view, to which I invite corrections, is broadly:

- The semantic web set off with extraordinarily ambitious goals, which were largely impractical

- The entire field was trumped by Deep Learning, which takes as its premise that you can infer relationships from the exabytes of human rambling on the internet, rather than having to laboriously encode them explicitly

- Deep Learning is not after all a panacea, but more like a very clever parlour trick; put otherwise, intelligence is more than linear algebra, and "real" intelligences aren't completely fooled by one pixel changing colour in an image, etc.

- Hence, we have come back round to point 1 again

?

Re: A Review of the Semantic Web Field

#23
post #17
post #14

Earlier quoted context omitted.

> CURIEs and the depending standards alone are well over 100 pages. The curie standard is 10 pages long, and those "dependent standards" includes things like RFC 3986 (Uniform Resource Identifiers (URI): Generic Syntax) and RFC 3987 (Internationalized Resource Identifiers (IRI)) - which are well established technologies that most people should be familiar with. And you really don't need to read all of the referenced…

Familiarity isn't nearly enough if you want to implement something. Talking about RDF is absolutely meaningless without talking about Serialisation (and that includes ...URGH.. XML serialisation), XML Schema data-types, localisations, skolemisation, and the ongoing blank-node war. The semantic web ecosystem is the prime example of "the devils in the detail". Of course you can explain to somebody who knows what a grap…

I don’t even work with semantic technologies, but I just love the structure and completeness of arguments in the space. I suppose I should not make enemies by being specific, but compare this comment to the average (or even 90th percentile) argument on almost any other topic.

Although it looks like HN now needs to implement a “download the Kindle“ feature :-)

Re: A Review of the Semantic Web Field

#24
post #20

Earlier quoted context omitted.

You're right to emancipate from the grab that SemWeb has had on the field for so long and turn to Prolog/Datalog and practical approaches IMO. Open world semantics and sophisticated theories may have been a vision for the semantic web of heterogenous data, but in reality RDF and co are only used in certain closed-world niches IME. Pascal Hitzler is one of the more prolific authors (especially with the EU-funded ident…

NitNit: I think the term "Datalog" the prolog subset, has been pretty much replaced with "Datalog" the recursive consjunctive query fragment with recursion (and sometimes stratified negation) term. Most papers and textbooks I read these days use it as a complexity class for queries and not as a concrete syntax.

This is the sense in which I was using Datalog - and how others like Datomic, Grakn and Crux use it (there is a growing movement of databases with a 'Datalog' query language) - althou in our case, we can also use in the former sense as TerminusDB is implemented in prolog.

Re: A Review of the Semantic Web Field

#25
post #23
post #17

Earlier quoted context omitted.

Familiarity isn't nearly enough if you want to implement something. Talking about RDF is absolutely meaningless without talking about Serialisation (and that includes ...URGH.. XML serialisation), XML Schema data-types, localisations, skolemisation, and the ongoing blank-node war. The semantic web ecosystem is the prime example of "the devils in the detail". Of course you can explain to somebody who knows what a grap…

I don’t even work with semantic technologies, but I just love the structure and completeness of arguments in the space. I suppose I should not make enemies by being specific, but compare this comment to the average (or even 90th percentile) argument on almost any other topic. Although it looks like HN now needs to implement a “download the Kindle“ feature :-)

I'm flattered <3

Re: A Review of the Semantic Web Field

#26
post #4

Maybe for its time it seemed like a good idea.. Like SOAP or manual features for image classification. Today, it's clear that languages and knowledge don't really work like that, and it's not practical to approach them this way. I've learned about the OWL and SPARQL 12 years ago, and it already felt like a very dated idea. But then who knows... Everybody have given up on NNs once too.

> Today, it's clear that languages and knowledge don't really work like that, and it's not practical to approach them this way.

There are many applications of Semantic Web that has little to do with natural languages. If you have a better option for all the existing RDF data sets (https://lod-cloud.net/, https://www.wikidata.org/) and ontologies (http://www.ontobee.org/, https://schema.org/) it would be good to be explicit about it.

I would prefer to have more data (e.g. data from US federal reserve data, world bank data) as RDF and accessible via SPARQL endpoints than less, because it is much more useful as RDF than as CSV, in my opinion.

Re: A Review of the Semantic Web Field

#27
post #11

We built a new semantic database first in university and then commercial open source (TerminusDB). We use the web ontology language (OWL) as a schema language, but made two important - practical - modifications: 1) we dispense with the open world interpretation; and 2) insist on the unique name assumption. This provides us with a rich modelling language which delivers constraints on the shapes in the graph. Additiona…

> [...] but we must extract the good and remove ideological barriers to participation.

Could you point to some resources that explain the tradeoff between the practical solutions and concepts and the ideologic cruft for an outsider?

Re: A Review of the Semantic Web Field

#29
post #3

The whole field has been dominated by research, i.e. the wish to make simple things complicated (in order to publish papers) as opposed to engineering, i.e. making complicated things simple (in order to produce usable software efficiently). As a result the standards are horrendously - and needlessly - complicated. The few major practical outcomes like the schema.org, json-ld and the google annotation system, are resu…

I agree, the research is overly complicated.

So it's a lot of extra work to sift through, but I've found a lot of gold in there.

If you're looking for a simple, noise-free way to do the semantic web, I'm very confident that Tree Notation will enable it (https://treenotation.org/).

I've played around a bit with turning Schema.org into a Tree Language, and think that would be a fruitful exercise, but plenty more on the plate first.

FWIW I've pitched this concept to W3C for 4 or 5 years to no avail yet. I think though if someone can put together a decent prototype the idea might start clicking.

Imagine a noise free way to encode the semantic web with natural 3-d positional semantics. Could be cool!

Re: A Review of the Semantic Web Field

#30

My 10,000 ft layperson's view, to which I invite corrections, is broadly: - The semantic web set off with extraordinarily ambitious goals, which were largely impractical - The entire field was trumped by Deep Learning, which takes as its premise that you can infer relationships from the exabytes of human rambling on the internet, rather than having to laboriously encode them explicitly - Deep Learning is not after al…

I think you are spot on.

I think what we'll see is Deep Learning/Human Editor "Teams".

DL will do the bulk of the relationship encoding, but human domain experts will do "code reviews" on the commits made by DL agents.

Over time fewer and fewer commits will need to be reviewed, because each one trains the agent a bit more.

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