A Review of the Semantic Web Field
cacm.acm.org
A Review of the Semantic Web Field
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Re: A Review of the Semantic Web Field
#2The reason why tools like Protégé have not been sufficiently developed is because of infighting in the academic ontology community in addition to the reasons listed by the author. It has set the whole community back at least 5 years.
Re: A Review of the Semantic Web Field
#3The 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 results of engineering, not research. Alas, json-ld has also taken a turn towards hypercomplexities.
Re: A Review of the Semantic Web Field
#4Maybe 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.
Re: A Review of the Semantic Web Field
#5The reason why tools like Protégé have not been sufficiently developed is because of infighting in the academic ontology community in addition to the reasons listed by the author. It has set the whole community back at least 5 years.
I think that's a symptom, not the cause.
The complexity of web standards in general smother it with it's own weight. The common web has enough raw financial and person backing to grind through that. The semantic web does not.
CURIEs and the depending standards alone are well over 100 pages. Language tags alone has 90.
RDF has like 100, Sparql has a combined of more than 300, and OWL has more than 500, even though it assumes that the reader is generally familiar with Description logics, so it's probably a couple thousand if you take the required academic literature into account.
Nobody is going to read all of that, let alone build that.
Especially not a bunch of academics who don't care about the implementation as long as it's good enough to get the next paper out the door.
So everybody pools on these few projects, because they're the only thing that's kinda working. OWLAPI, Protege, ... uh that's it.
Because everything else, is broken and unfinished.
Here's a thought experiment, name one production ready RDF libray for every major programming language (C, Java, Python, Js), that doesn't have major, stale, unresolved issues in their issue tracker. It's all broken, and there is simply too much work required to fix things.
It's only natural that people start to infight when there is only few hospitable oasis.
What we need is a simpler ecosystem, where people can stake their claim on their niche, where they have the ability and power to experiment and explore.
Re: A Review of the Semantic Web Field
#6The 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…
Yeah, this is an unfortunate consequence of having the whole ecosystem mostly within academia, including the lack of tutorials and proper documentation (e.g. not a 500 page standard).
IMO the most interesting place right now for semantic web development is Wikidata. It's still pretty difficult for newcomers to contribute (as is the case for all Wikimedia projects) but at least it has many eyeballs and a very active community / ecosystem.
Re: A Review of the Semantic Web Field
#7The 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…
Maybe a good indicator that there is only minor (industry) need/benefit. The "biggest" Knowledge Graph is Google, but it is unclear, how much there is actually Semantic Web and how much search, ML, NLP etc..
They are all nice ideas, but the practical usecases are rare. I am skeptical of the often touted usecase in Medicine/Drug Interactions. The only time i saw it in the industry, it was not really used by the lab technicians. Because all questions the system could answer, were trivial. The promise of "the system can inference new combinations/interactions" was never fulfilled.
Re: A Review of the Semantic Web Field
#8This seems to me to be an insightful and comprehensive overview of the Semantic Web, both current status and how we got here. People like me, who have long been wanting to better understand the (obviously sprawling) concepts involved will be able to use the article as a good entry point.
That said, the expressed hope of consolidation in the field is likely still some way off. AI has taken over a lot of the promise that the Semantic Web originally held. But AFAICS there are two drivers (also mentioned in the article) that potentially could provide the required impetus for a reignited interest in the Semantic Web:
Firstly the need for explainable AI, and secondly the probable(?) coming breakthrough in natural language processing and automatic knowledge graph or ontologies from text.
All in all, it seems way too early to write off the Semantic Web field at this point.
Re: A Review of the Semantic Web Field
#9As always should look at metacrap (http://www.well.com/~doctorow/metacrap.htm) when discussing the semantic web
- Certain kinds of implicit metadata is awfully useful, in fact. Google exploits metadata about the structure of the World Wide Web: by examining the number of links pointing at a page (and the number of links pointing at each linker), Google can derive statistics about the number of Web-authors who believe that that page is important enough to link to, and hence make extremely reliable guesses about how reputable the information on that page is.
This sort of observational metadata is far more reliable than the stuff that human beings create for the purposes of having their documents found. It cuts through the marketing bullshit, the self-delusion, and the vocabulary collisions.
in short, engineering triumphs over data entry.
Re: A Review of the Semantic Web Field
#10Maybe 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.
The comparisons to NLP presents a good view on the problems.
Its "easy" to write some logic rules to parse input text for a 50% demo. But then you want to improve & scale, and suddenly all the nuances, bites you. The rules get bigger, nested and complicated. Traditional NLP tried that avenue for a while, with decent success in small usecases, but for larger problems without success. (Compared to stuff like BERT & GPT, which still have a lot of problems)
Similar with Knowledge Graphs, you can show some nice properties on inferring knowledge on small problems, but the real world is much more approximate and unclear than some (binary) relationships.
Personally i think we Humans lack the mental capacity to build large models with complex interactions.