A Review of the Semantic Web Field

https://cacm.acm.org/magazines/2021/2/250085-a-review-of-the-semantic-web-field/fulltext

by hypomnemata • 5 years ago

126 70 5 years ago

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hyperion2010• 5 years ago

The 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.

j-pb8• 5 years ago

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.

syats• 5 years ago

I agree with this. It is common to hear "Partial SPARQL 1.1 support"... or "Partial OWL compatibility" or "A variant of SKOS is supported". While it is true that full ECMA6/HTTP2/IPv6/SQL is also rarely provided by implementations, this doesn't hinder their use in productive environments. I think it is rare to reach the parts of ECMAscript that aren't implemented, or the corners of SQL that Postgres/MariaDB don't support. In many of the "Semantic Web Stack", however, one quickly reaches a "not implemented" portion of the 500 page owl standard.

cheph5• 5 years ago

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 standards to be able to understand and use CURIE quite proficiently.

RDF has like 100

Normative specifications of RDF is contained in two documents:

- RDF 1.1 Concepts and Abstract Syntax ( https://www.w3.org/TR/rdf11-concepts/ ) = 20 pages

- RDF 1.1 Semantics ( https://www.w3.org/TR/rdf11-mt/ ) = 29 pages

These page counts includes TOC, reference sections, appendices and large swathes of non-normative content also.

And really the RDF 1.1 primer (https://www.w3.org/TR/rdf11-primer/) should be quite sufficient for most people who want to use it, and that is only 14 pages.

RDF and CURIE is simple as dirt really, maybe too simple, but I think I can explain it quite well to someone with some basic background in IT in about 30 minutes.

And while the other aspects (e.g. SPARQL, OWL) are not that simple, there is inherent complexity they are trying to address that you cannot just ignore. And not everybody needs to know OWL, and SPARQL is really not that complicated either and again most people can become quite proficient with this rather quickly if they understand the basics.

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.

What are the alternatives? Proliferation of JSON schemas which is yet to be ratified as a standard and does not address most of the same problems as Semantic Web Technology? I think there are some validity to your concerns, but semantic web technologies are being used widely in production, maybe not all of them, but to suggest it is not usable is not true.

I have used RDF in Java (rdf4j and jena), Python (rdflib) and JS (rdflib.js) without serious problems.

namedgraph11• 5 years ago

OWLAPI, Protege - that's it? RDF libraries broken? Dude what rock are you living under? What about Jena, RDF4J, rdflib, redland, dotNetRDF etc? Most of these libraries have been developed and tested for 20+ years and are active. See for yourself: https://github.com/semantalytics/awesome-semantic-web#progra...

Why are you spreading FUD?

ta9885• 5 years ago

Could you give more details on that? How can it slow down an editor development?

tammet• 5 years ago

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 results of engineering, not research. Alas, json-ld has also taken a turn towards hypercomplexities.

huskyr• 5 years ago

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.

ivan_ah2• 5 years ago

+1 for WIKIDATA

There are lots of useful WIKIDATA links and demos on this page: https://www.wikidata.org/wiki/User:Daniel_Mietchen/FSCI_2017...

krallistic2• 5 years ago

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.

cheph5• 5 years ago

The "biggest" Knowledge Graph is Google, but it is unclear, how much there is actually Semantic Web and how much search, ML, NLP etc..

The second biggest is possibly WikiData, and it is not that small.

As to the practical use cases, there are many, but it is the premier way of encoding metadata for search engines: https://schema.org/docs/about.html

And the amount of datasets and ontologies that exist is quite vast:

- https://lod-cloud.net/dataset

- http://obofoundry.org/

- https://www.mediawiki.org/wiki/Wikidata_Query_Service/User_M...

I would like to understand what other options you would consider better for these datasets, for the metadata and for the ontologies?

I mean if not RDF for web metadata then what? If not semantic web for UK govt data (https://ukparliament.github.io/ontologies/, https://opendatacommunities.org/data_home, https://ckan.publishing.service.gov.uk/dataset?res_format=RD..., https://ckan.publishing.service.gov.uk/dataset?res_format=SP...) then what?

It would be nice to have something even better, but I much prefer RDF to a bunch of CSV files.

namedgraph11• 5 years ago

Explain this Knowledge Graph usage by Fortune 500 companies then: http://sparql.club/

breck3• 5 years ago

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!

ta9885• 5 years ago

It is unclear to me what it would achieve compared to a spog (subject, predicate, object, graph) based representation like it exists in RDF based triplestores.

xkvhs• 5 years ago

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.

krallistic2• 5 years ago

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.

ta9885• 5 years ago

That's true as individuals I do not believe we can. Only as a group and with the help of tools, which is what semweb tried to achieve. We found out the tools weren't the most practical and learned a lot. Now we need the Tensorflow of those approaches, something easy to use not platform centric and with a low barrier of entry.

cheph5• 5 years ago

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.

namedgraph11• 5 years ago

Right... except that Uber, Boeing, JP Morgan Chase, Nike, Electronic Arts etc. etc. are looking for SPARQL developers right now: http://sparql.club/

ta9885• 5 years ago

OWL tools are dated. One large lib OWLAPI that is full of bugs and impractical, available only for one platform (JVM). Reasoners that work or not, and get abandonned once the grant that funded them is finished... Reasoners that use OWLAPI x but never got ported to OWLAPI y so no way to use it on more recent systems...

stareatgoats• 5 years ago

This 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.

bryanrasmussen• 5 years ago

As 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.

sammorrowdrums• 5 years ago

I found that Job Postings are an exception. Google picks up on them, has a special API to submit them direct (due to slow crawling) and close them.

So long as you're a good actor that will get you far. If your data is low quality, wrong, error prone or otherwise you'll not get shown and will likely receive manual actions and end up in the Google proverbial sin bin.

I have found that incentives align for job postings.

That obviously doesn't prove that metadata is not flawed, just that there are areas where it seems to work well.

LukeEF2• 5 years ago

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. Additionally, we don't use SPARQL, which we didn't find practical (composability is important to us) and use a Datalog in its place (like Dataomic and others).

Our feeling on interacting with the semantic web community is that innovation - especially when it conflicts with core ideology - is not welcome. We understand that 'open world' is crucial to the idea of a complete 'semantic web', but it is insanely impractical for data practitioners (we want to know what is in our DB!). Semantic web folk can treat alternative approaches as heresy and that is not a good basis for growth.

As we came from university, I agree with comments that the field is too academic and bends to the strange incentives of paper publishing. Lots of big ideas and everything else is mere 'implementation detail' - when, in truth, the innovation is in the implementation details.

There are great ideas in the semantic web, and they should be more widespread. Data engineers, data scientists, and everybody else can benefit, but we must extract the good and remove ideological barriers to participation.

tannhaeuser• 5 years ago

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 identification of description logic fragments of OWL2 which are some of the better results in the field IMO), but beginning this whole discussion with W3C's RDF is wrong IMO when description logic as more or less variable-free fragments of first-order logic with desirable complexities was a thing in 1991 or earlier already.

Nit: careful with datomic. It's clearly not Datalog, but an ad-hoc syntax whereas Datalog is a proper syntactic subset of Prolog. And while I don't like SPARQL, it still gives quite good compat for querying large graph databases.

j-pb8• 5 years ago

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.

JPKab3• 5 years ago

I met Pascal Hitzler on a few occasions, not long after he ended up relocating from Germany to Ohio to work at Wright State. He was a rare bright spot in always trying to bridge the gap between theory and application in the SemWeb community. He was kind enough to meet up with me and a colleague at a coffee shop in Dayton to discuss our project, all pro-bono. A real good dude.

Communitivity• 5 years ago

Almost every pragmatic implementation of semantic reasoning I've done involved both of the same modifications (closed world and unique names). A couple efforts used SPARQLX, something I created that was a binary form of SPARQL+SPARQLUpdate+StoredProcedures+Macros encoded using Variable Message Format. This was about 18 years ago, before SPARQL and SPARQL update merged, and before FLWOR. One of these days I'll recreate it again. The original work is not available, and I was not allowed to publish.

Oh, and I forgot two things, SPARQLX had triggers, was customized for OWL DLP, and had commands for custom import and export using N3 (I was a big fan of the cwm software).

wuschel4• 5 years ago

[...] 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?

lou1306• 5 years ago

Not the commenter, but I hope to add something to the discussion. Generally, expanding on the current state of the art is paramount in academia. In this case, I guess that defaulting on closed-world and unique names is frowned upon because academic people "know" that SemWeb concepts would be "easy" to implement under such conditions (for some interpretation of "know" and "easy"). A university lab would be reluctant to invest on such a project, because it would likely result in less publications than, say, a bleeding-edge POC.

Of course, practical solutions based on well-understood assumptions are exactly what a commercial operation needs, so it's no wonder that TerminusDB chose that path. They might not publish a ton of papers, but they have something that works and could be used in production.

jerf2• 5 years ago

"Our feeling on interacting with the semantic web community is that innovation - especially when it conflicts with core ideology - is not welcome."

I wasn't a big fan of the "semantic web" community when it first came out, and the years have only deepened my disrespect, if not outright contempt. The entire argument was "Semantic web will do this and that and the other thing!"

"OK, how exactly will it accomplish this?"

"It would be really cool if it did! Think about what it would enable!"

"OK, fine, but how will this actually work!"

"Graph structures! RDF!"

"Yes, that's a data format. What about the algorithms? How are you going to solve the core problem, which is that nobody can agree on what ontology to apply to data at global scale, and there isn't even a hint of how to solve this problem?"

"So many questions. You must be a bad developer! It would be so cool if this worked, so it'll work!"

There has always been this vacuousness in the claims, where they've got a somewhat clear idea of where they want to go, but if you ever try to poke down even one layer deeper into how it's going to be solved, you get either A: insulted B1: claims that it's already solved just go use this solution (even though it is clearly not already solved since the semantic web promises are still promises and not manifested reality) B2: claims it's already solved and the semantic web is already huge (even though the only examples some using this can cite are trivial compared to the grand promises and the "semantic web" components borderline irrelevant, most frequently citing "those google boxes that pop up for sites in search results" just like this article does despite the fact they're wafer-thin compared to the Semantic Web promises and barely use any "Semantic Web" tech at all) or C: a simple reiteration of the top-level promises, almost as if the person making this response simply doesn't fundamentally grasp that the ideals need to manifest in real code and real data to work.

This article does nothing to dispel my beliefs about it. The second sentence says it all. For the rest, while just zooming in to the reality may be momentarily impressive, compared to the promises made it is nothing.

The whole thing was structured backwards anyhow. I'd analogize the "semantic web" effort to creating a programming language syntax definition, but failing to create the compiler, the runtime, the standard library, or the community. Sure, it's non-trivial forward progress, but it wasn't really the hard part. The real problem for semantic web and their community is the shared ontology; solve that and the rest would mostly fall into place. The problem is... that's an unsolvable problem. Unsurprisingly, a community and tech all centered around an unsolvable problem haven't been that productive.

A fun exercise (which I seriously recommend if you think this is solvable, let alone easy) is to just consider how to label a work with its author. Or its primary author and secondary authors... or the author, and the subsequent author of the second edition... or, what exactly is an authored work anyhow? And how exactly do we identify an author... consider two people with identical names/titles, for instance. If we have a "primary author" field, do we always have to declare a primary author? If it's optional, how often can you expect a non-expert bulk adding author information in to get it correct? (How would such a person necessarily even know how to pick the "primary author" out of four alphabetically-ordered citations on a paper?)

(I am aware of the fact there are various official solutions to these problems in various domains... the fact that there are various solutions is exactly my point. Even this simple issue is not agreed upon, context-dependent, it's AI-complete to translate between the various schema, and if you speak to an expert using any of them you could get an earful about their deficiencies.)

olliemath• 5 years ago

Yes. I had pretty much this conversation a while back with some non-technically minded people who had been convinced that by creating an ontology and set of "semantic business rules" - a lot of the writing of actual code could be automated away, leaving the business team to just create rules in a language almost like English and have the machine execute those English-like rules.

I had to explain that they were basically on track to re-implementing COBOL.

namedgraph11• 5 years ago

It's not what you have to do, or how, it's that for the first time we have a common model for data interchange (RDF) with which you can model concepts and things in your domain, or more-importantly across domains, and simply merge the datasets. Try that with the relational model or JSON. Integration is the main value proposal of RDF today, nobody sane is trying to build a single global ontology of the world .

You can despise the fringe academic research, but how do you explain Knowledge Graph use by FAANG (including powering Alexa and Siri) as well as a number of Fortune 500 companies? Here are the companies looking for SPARQL (RDF query language) developers: http://sparql.club

usrusr• 5 years ago

"dispense with the open world interpretation“

That can mean anything from "we have some conventional (e.g. plain old RDBMS) CWA systems but describe their schemas in an OWA DL to ease integration across independent systems" (in particular this means no CWA implications outside those built into the conventional systems with or without a semweb layer on top) to "we do a big bucket of RDF and run it all through a set of rules formulated in OWL syntax but applied in an entirely different way" (CWA everywhere). The former would be semweb as intended, or at least a subset thereof, but the latter could easily end up somewhere between simple brand abuse and almost comical cargo culting.

Well, at least that's how I feel as someone who never had to face the realities of the vast unmapped territories between plain old database applications and fascinating yet entirely impractical academic mind games of DL (old school symbolic AI ivory tower that suddenly happened to find itself in the center of the hottest w3c spec right before w3c specs kind of stopped being a thing, with WHATWG usurping html and Crockford almost accidentally killing XML)

(also, when has "assumption" turned into "interpretation"? Guess I missed a lot)

nut-hatch• 5 years ago

I completed my PhD in the scope of Semantic Web technologies and I can share the same experience that the semantic web community is extremely closed (coming across as feeling "elite"). Having myself no supervisor from the field, it was still possible to publish my ideas (ISWC, WWW etc), but it was impossible to connect to the people and be taken seriously.

I moved on from that field now, and I don't expect to come in touch with any Semantic Web stuff in a open-world context any time soon.

I couldn't agree more with you that the strong ideology that drives this community is one of the main reason that these technologies are not widely adopted. This, and the failure to convince people outside academia that solving the problems it tries to solve is necessary in the first place.

Good luck with TerminusDB, I think I listened to you at KGC.

JPKab3• 5 years ago

I was "stuck" working with a bunch of leading academics and researchers on a SemWeb project using OWL/RDF, in collaboration with DARPA and the US Department of Defense, around 2008-2009.

You are absolutely correct that they are hostile to anything outside of their "ideology".

The awful, horrific performance of the RDF/OWL databases compared to the impure, heretical evil Neo4j that they despised for its practicality..... that was always funny.

Another interesting thing I encountered in the field was the side-effect of an academic field that sounds really good to people who have never built anything EVER is that it can often get a ton of funding and grant money from central government organizations, thereby creating legions of rather shitty companies (especially in the EU, where the grants were everywhere) that have the word "semantic" in the name even though they do nothing with actual semantic technology. These shitty companies are often just there to employ the academics.

The craziest thing was these projects where they would employ a dozen or so "library scientists" who were all just masters and phd students who had, for some reason, decided to study to be librarians in the digital era to create the OWL ontologies. None of them knew anything about computer science or programming, and they would just sit there and read thousands of policy documents and use an Eclipse based GUI to create and edit giant graphs of knowledge and rules. All were being paid six figures, and didn't produce a single goddammed thing of value. So much taxpayer money in those rooms going to complete waste. Glad it wasn't just me that thought the community was a joke.

The semantic web will arrive one day, but OWL and SPARQL won't be anywhere in it. And it won't be any of these academics delivering it.

ta9885• 5 years ago

Are you referring to the BFO crowd? I would be interested in your thoughts about BFO itself if thats the case.

actsofthecla• 5 years ago

I'm only a hobbyist in this area, but I wonder why the review wouldn't mention some of the graph databases as, at least, semantic web adjacent. Their relative success seems to lend credence to the overall vision of the semantic web and its supporting technologies. For example, are there really more than surface syntactical differences between SPARQL and Cypher?

Even though it was over-hyped, I like the semantic web because it supports a conception for the future that includes something other than neural network black-boxes. However, whether the ideas deliver remains to be seen.

If anyone is looking for an introduction, then I think the Linked Data book from Manning is worth mentioning--it might be a little dated at this point. The author provides a coherent introduction and helps, especially, in cutting through the confusing proliferation of acronyms that characterizes this field. As others have mentioned, reliable software is a major stumbling block. It's especially unfortunate that there isn't better browser support, of RDFa for example.

namedgraph11• 5 years ago

Check our SPARQL-driven Knowledge Graph management system :) https://atomgraph.github.io/LinkedDataHub/

tragomaskhalos• 5 years ago

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

breck3• 5 years ago

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.

cheph5• 5 years ago

Deep Learning does not even operate in the same space as where most of Semantic Web is being used today, some examples:

- https://schema.org/

- https://www.wikidata.org/

- https://lod-cloud.net/

- http://www.ontobee.org/

- https://catalog.data.gov/dataset?res_format=RDF&_res_format_...

- https://ukparliament.github.io/ontologies/

- https://ckan.publishing.service.gov.uk/dataset?res_format=SP...

- https://ckan.publishing.service.gov.uk/dataset?res_format=RD...

- https://data.nasa.gov/ontologies/atmonto/index.html

- https://data.europa.eu/euodp/linked-data

fauigerzigerk• 5 years ago

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

I don't think machine learning can ever replace data modeling, because data modeling is often creative and/or normative. If we want to express what data must look like and which relationships there should be, then machine learning doesn't help and we have no other choice than to laboriously encode or designs. And as long as we model data we will have a need for data exchange formats.

You could categorise data exchange formats as follows:

a) Ad-hoc formats with ill defined syntax and ill defined semantics. That would be something like the CSV family of formats or the many ad-hoc mini formats you find in database text fields.

b) Well defined syntax with externally defined often informal semantics. XML and JSON are examples of that.

c) Well defined syntax with some well defined formal semantics. That's where I see Semantic Web standards such as RDF (in its various notations), RDFS and OWL.

So if the task is to reliably merge, cleanse and interpret data from different sources then we can achieve that with less code on the basis of (c) type data exchange formats.

But it seems we're stuck with (b). I understand some of the reasons. The Semantic Web standards are rather complex and at the same time not powerful enough to express all the things we need. But that is a different issue than what you are talking about.

mxmilkb• 5 years ago

Nice though nothing about Turtle or LV2

https://www.w3.org/2007/02/turtle/primer/

https://github.com/lv2/lv2/wiki

Also, #swig (semantic web interest group) exists on freenode.

smarx007• 5 years ago

I do research in this field but I am a programmer by training before I entered this research field. I have talked to many academics and they agree that industry needs something simpler, more approachable and something that solves their problems in a more direct way, so it's definitely not an "academic exercise" for many researchers.

However, I failed to convince people that we need to implement the 2001 SciAm use case (https://www-sop.inria.fr/acacia/cours/essi2006/Scientific%20..., see the intro before the first section) using 2021 technologies (smartphones are here, assistants are here, shared calendars are easy, companies have APIs, the only thing missing is a proper glue using semantic web tech). This goes to the core thesis of this paper that semantic web is awesome as the set of ideas and approaches but the Semantic Web as the result of all this work may look underwhelming or irrelevant today. I like to point everyone who disagrees with me to the 1994 TimBL presentation at CERN (https://videos.cern.ch/record/2671957) where he talks about the early vision of semantic web (https://imgur.com/aS2dbf6 or around 05:00 in the video), which looks awfully like IoT (many years before the term even existed). We simply cannot fault someone who envisioned communication technologies for IoT in 1994 for getting the technology a bit wrong.

Today's technologies simply cannot handle the use-cases for which SemWeb was designed for properly:

1) The web is still not suitable for machines. Yes, we have IoT devices that use APIs but nobody will say it's truly M2M communication at its best. When APIs go down devices get bricked, there is no way to get those devices to talk to any other APIs. There is no way for two devices in a house to talk to each other unless they were explicitly programmed to do so.

2) We don't have common definitions for the simplest of terms. Schema.org made a progress but it's very limited because it serves search engine interest, not the IoT community. There is no reason something like XML NS or RDF NS should not be used across every microservice in a company. Using a key (we call them predicates, but not important here) "email:mbox" (defined in https://www.w3.org/2000/10/swap/ very long time ago) you can globally denote the value is an email.

3) Correctness of data and endpoint definition still matters. We threw away XML and WSDL but came back to develop JSON Schema and Swagger.

We are trying to get there. JSON Schema, Swagger etc. all make efforts in the direction of the problems SemWeb tried to address. One of the most "semantic" efforts I see done recently is GraphQL federation, which has been a semantic web dream for a long while: being able to get the information you need by querying more than one API. This only indicates the problems that semantic web tried to address are still viable.

If anyone has attempted an OSS reimplementation of the 2001 "Pete and Lucy" semantic web use case (ie as an Android app and a bunch of microservices), please point me in the right direction. Otherwise, if anyone is interested in doing it, I am all ears (https://gitter.im/linkeddata/chat is an active place for the LOD/EKG/SW discussion).

namedgraph11• 5 years ago

We wasted 20 years by trying to replace one form of brackets with the other (XML vs. JSON). WHATWG and the browser vendors are responsible for this. Just like for the fact that we still don't have a machine-readable web. FAANG crawls the structured schema.org metadata like nobody else can and profits from it, and the rest of use are left with the HTML5 and Javascript crap.

mark_l_watson• 5 years ago

Even though I have been working off and with SW and linked data tech for twenty years, I share some of the skeptical sentiments in comments here.

I am keenly interested in fusion of knowledge representation with SW tech and deep learning. I wrote a short and effective NLP interface to DBPedia two weekends ago that you can experiment with on Google Colab https://colab.research.google.com/drive/1FX-0eizj2vayXsqfSB2... that leverages Hugging Face’s transformer model for question answering. You can quickly see example use in my blog https://markwatson.com/blog/2021-01-18-dbpedia-qa-transforme...

ivan_ah2• 5 years ago

Wow, what a great summary with lots of realism and nuances. I agree with the author's conclusions that what is missing is consolidation and interoperability between standards (e.g. make Protégé easier to use and ensure libraries for RDF parsing and serializations exist for all languages). No technology will be adopted if it requires PhD-level ability to handle jargon and complexity... but if there were tutorials and HOWTOs, we could see big progress.

Personally, I'm not a big fan of the "fancy" layers of the Semantic Web Stack like OWL (see https://en.wikipedia.org/wiki/Semantic_Web_Stack ), but the basic layers of RDF + SPARQL as a means for structured exchange of data seem like a solid foundation to build upon.

It's really simple in the end: we've got databases and identifiers. INTERNALLY to any company or organization, you can setup a DB of your choosing and ensure data follows a given schema, with data linked through internal identifiers. When you want to publish data EXTERNALLY, you need to have "external identifiers" for each resource, and URIs are a logical choice for this (this is also a core idea of REST APIs of hyperlinked resources). Similarly, communicating data using the a generic schema capable of expressing arbitrary entities and relations like RDF and JSON-LD is also a logical next step, rather than each API using it's own bespoke data schema...

As for making web data machine-readable, the key there is KISS: efforts like schema.org with opt-in, progressive enhancements annotations are very promising.

For anyone wanting to know more about this domain, there is an online course here: https://www.youtube.com/playlist?list=PLoOmvuyo5UAeihlKcWpzV... The whole course is pretty deep (would take a month to go through it all), but you can skip ahead to lectures of specific interest.

kmerroll• 5 years ago

Honestly disconcerting to see mostly negative responses in this thread: awful community, overly complicated, research focused, academic nitwits gone wild, etc. Pretty sure there's some truth here, but would suggest the deeper argument is against semantic web as evolution of the world-wide-web. Agree this isn't likely to happen in my lifetime.

Right up there with, mostly hated, Javascript, I happen to think there are good parts of the semantic web technologies and that the pivot towards industry adoption of the graph data models related to knowledge graphs, ontologies, and SPARQL shows there are benefits outside of academic paper mills. I don't have a dog in this fight (TerminusDB), but applying some reasonable expectations and accepting the limitations of the semantic web tools has been very successful on many projects. Even more so, innovation and improvements in graph data repositories are making triple-stores and graph-based models compelling for some use cases. Not going back to CSV hell if there are better alternatives.

A Review of the Semantic Web Field

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