4 ms·

With AI at last hitting its heyday, semantic data will finally be important enough to enter general use. It's not a replacement for the web, but rather a supple

With AI at last hitting its heyday, semantic data will finally be important enough to enter general use. It's not a replacement for the web, but rather a supplement to it, where intelligent machine agents can automatically and intelligently navigate relationship connections to find or even infer the information you're looking for using various APIs. Tim Berners Lee was way ahead of his time with this (and ahead of computers' ability to make something useful out of it), which is why it languished for so long (much like AI did). schema.org is a godsend, because it's finally a serious attempt at standardizing semantics (much like foaf did in a rather anemic attempt). I've added the relationship data type to the Concise Encoding spec [1] and look forward to exciting times! [1] https://concise-encoding.org/#relationships https://concise-encoding.org/#relationships

chrismorgan 6y ago
If anything, I’d have thought AI would lead to people being lazier about marking up semantic data, because if the machine learning is good enough there’s simply no call for it. So yeah, people may consume the semantic data, but the actual markup for such semantic data could become even less important than it is now. > schema.org is a godsend, because it's finally a serious attempt at standardizing semantics schema.org is nothing new. It’s been around since 2011 (and was a direct follow-up to earlier efforts like microformats from 2005–2010), and has been valuable to search engine listings and thus widely used ever since.
- kstenerud 6y ago
  It's not about people marking up HTML to add semantic data; that's never going to happen (and never should). HTML is a presentation layer designed for comsumption by humans, and human presentation data is no place for semantic content because it's a view of the data meant for HUMANS, who will already understand the semantic meaning. "Semantic content" is about machines using common semantic identifiers in their public APIs so that their data sets can interoperate and be used as components for something bigger.
  - tannhaeuser 6y ago
    Fully agree with your criticism of "semantic HTML" though many frontend developers would (bogusly, IMO) assign HTML the role of "structure" rather than presentation which they believe CSS is for. But still, in practice, what's left of SemWeb (on the web) is used for marking up HTML for search engines, in the form of meta-tags, Open Graph annotations, location data, RDFa, microformats, etc. The question is, should they, when Google will preview their data in search results such that they don't get clicks? Which is exactly the problem with semantic technologies on the web.
    - kstenerud 6y ago
      The "semantic web" in terms of how it's been applied to HTML is effectively DOA. The real power of semantic data (which hasn't been realized yet) is in letting computer intelligences communicate in an understandable fashion. Linking databases and data sources globally has been the wet dream of distributed systems advocates for decades, but we've had neither the power nor the use cases for such things. However, once big data AI gets hungry enough, you can bet that everyone will jump headlong into the new data mining frenzy that's coming once someone writes the first successful "data connector & broker" service (much like what Lycos and Altavista did for web search).
- fauigerzigerk 6y ago
  I think the focus on semantic markup is unfortunate. The term conjures up the idea of someone going through a web page, painstakingly adding structured data to (partially) mirror the text on the page. That was never going to happen, and I agree with you that machine learning makes it even less likely to happen. In my view, the semantic web is a set of interoperabilty standards for databases. If manufacturers and merchants publish data on products and prices it would be nice if they could do that in a way that lets us easily merge, repurpose and analyse that data. The data is already structured and stored in databases. So no one needs to mark up anything. What they would have to do is create a mapping from their proprietary database schemas to a set published schemas. In principle this is nothing new. We had structured data exchange formats for decades before the web even existed. What the semantic web standards add is a more formal way of specifying such data exchange formats. Traditionally, each data exchange format was an island with no formal connections to other data exchange formats. The semantic web standards make it easier to combine data from different sources across different schemas because they allow us to formally describe how these different schemas are related. Also, we need to consider what the role of machine learning should be. We have a lot of normative data that shouldn't need to be approximated. For instance, accounting rules should not be approximated with 96% accuracy by a 175 billion parameter neural network. These rules should be specified and interpretable with 100% accuracy on a 5 year old phone. Similarly, what goes into a gadget is decided by the manufacturer. It's not desirable to learn that information by extracting text from product descriptions on the web and applying huge NLP models. Sometimes that's the only way we have, but it's certainly not a desirable state of affairs.
  - triska 6y ago
    Thank you for posting this, I think this expresses the situation perfectly! Knowledge representation and reasoning languages like RDF, SPARQL etc., as well as querying languages like XQuery, go in this direction in principle. However, at least personally, I find them too inconvenient to use, too limited, and also not coherent enough to use them in actual rule-based automation tasks that involve semantic reasoning. In my opinion, there is tremendous opportunity in making flexible rule-based reasoning about web content and interfaces more easily available in web applications, especially in heavily regulated areas such as accounting which you mentioned, and in governmental applications and legal use cases. For instance, using open standards, a government could describe for other governments how to automatically derive certain evidences and logical consequences of existing regulations, such as whether a company is eligible for a grant, whether a lawyer has certain qualifications in that country, whether and under what provisions a product can be sold in that country etc. By plugging in the pertaining data, many logical consequences can be automatically derived. However, this demands more than the proposed semantic web technologies give us currently. As I see it, such use cases would benefit most from programming languages that let us not only express rules, but flexibly and easily reason about the rules themselves too, so that they can be easily interpreted, checked, simplified etc. automatically. I think RDF missed a huge opportunity: In particular, Datalog syntax could have been used to describe RDF data, and that would have enabled easy reasoning about RDF triples with existing standardized programming languages that are ideal for reasoning about rules that represent knowledge, and are also expressive enough to dynamically compute and fetch more data when necessary. I hope that future work on the semantic web will lead into this direction.
z3t4 6y ago
I like the idea of type annotation in HTML eg itemscope="movie" , item="director" etc. Categorizing everything in the world will be a lot of work though. Schema.org is too limiting/general.
- kstenerud 6y ago
  Think of schema.org as the Yahoo of semantic authorities. Somewhat good, but doomed to be replaced in a few years when others do it much much better. The point is, you need these pioneers to help get the technology off the ground.

chrismorgan 6y ago

If anything, I’d have thought AI would lead to people being lazier about marking up semantic data, because if the machine learning is good enough there’s simply no call for it. So yeah, people may consume the semantic data, but the actual markup for such semantic data could become even less important than it is now. > schema.org is a godsend, because it's finally a serious attempt at standardizing semantics schema.org is nothing new. It’s been around since 2011 (and was a direct follow-up to earlier efforts like microformats from 2005–2010), and has been valuable to search engine listings and thus widely used ever since.

kstenerud 6y ago
It's not about people marking up HTML to add semantic data; that's never going to happen (and never should). HTML is a presentation layer designed for comsumption by humans, and human presentation data is no place for semantic content because it's a view of the data meant for HUMANS, who will already understand the semantic meaning. "Semantic content" is about machines using common semantic identifiers in their public APIs so that their data sets can interoperate and be used as components for something bigger.
- tannhaeuser 6y ago
  Fully agree with your criticism of "semantic HTML" though many frontend developers would (bogusly, IMO) assign HTML the role of "structure" rather than presentation which they believe CSS is for. But still, in practice, what's left of SemWeb (on the web) is used for marking up HTML for search engines, in the form of meta-tags, Open Graph annotations, location data, RDFa, microformats, etc. The question is, should they, when Google will preview their data in search results such that they don't get clicks? Which is exactly the problem with semantic technologies on the web.
  - kstenerud 6y ago
    The "semantic web" in terms of how it's been applied to HTML is effectively DOA. The real power of semantic data (which hasn't been realized yet) is in letting computer intelligences communicate in an understandable fashion. Linking databases and data sources globally has been the wet dream of distributed systems advocates for decades, but we've had neither the power nor the use cases for such things. However, once big data AI gets hungry enough, you can bet that everyone will jump headlong into the new data mining frenzy that's coming once someone writes the first successful "data connector & broker" service (much like what Lycos and Altavista did for web search).
fauigerzigerk 6y ago
I think the focus on semantic markup is unfortunate. The term conjures up the idea of someone going through a web page, painstakingly adding structured data to (partially) mirror the text on the page. That was never going to happen, and I agree with you that machine learning makes it even less likely to happen. In my view, the semantic web is a set of interoperabilty standards for databases. If manufacturers and merchants publish data on products and prices it would be nice if they could do that in a way that lets us easily merge, repurpose and analyse that data. The data is already structured and stored in databases. So no one needs to mark up anything. What they would have to do is create a mapping from their proprietary database schemas to a set published schemas. In principle this is nothing new. We had structured data exchange formats for decades before the web even existed. What the semantic web standards add is a more formal way of specifying such data exchange formats. Traditionally, each data exchange format was an island with no formal connections to other data exchange formats. The semantic web standards make it easier to combine data from different sources across different schemas because they allow us to formally describe how these different schemas are related. Also, we need to consider what the role of machine learning should be. We have a lot of normative data that shouldn't need to be approximated. For instance, accounting rules should not be approximated with 96% accuracy by a 175 billion parameter neural network. These rules should be specified and interpretable with 100% accuracy on a 5 year old phone. Similarly, what goes into a gadget is decided by the manufacturer. It's not desirable to learn that information by extracting text from product descriptions on the web and applying huge NLP models. Sometimes that's the only way we have, but it's certainly not a desirable state of affairs.
- triska 6y ago
  Thank you for posting this, I think this expresses the situation perfectly! Knowledge representation and reasoning languages like RDF, SPARQL etc., as well as querying languages like XQuery, go in this direction in principle. However, at least personally, I find them too inconvenient to use, too limited, and also not coherent enough to use them in actual rule-based automation tasks that involve semantic reasoning. In my opinion, there is tremendous opportunity in making flexible rule-based reasoning about web content and interfaces more easily available in web applications, especially in heavily regulated areas such as accounting which you mentioned, and in governmental applications and legal use cases. For instance, using open standards, a government could describe for other governments how to automatically derive certain evidences and logical consequences of existing regulations, such as whether a company is eligible for a grant, whether a lawyer has certain qualifications in that country, whether and under what provisions a product can be sold in that country etc. By plugging in the pertaining data, many logical consequences can be automatically derived. However, this demands more than the proposed semantic web technologies give us currently. As I see it, such use cases would benefit most from programming languages that let us not only express rules, but flexibly and easily reason about the rules themselves too, so that they can be easily interpreted, checked, simplified etc. automatically. I think RDF missed a huge opportunity: In particular, Datalog syntax could have been used to describe RDF data, and that would have enabled easy reasoning about RDF triples with existing standardized programming languages that are ideal for reasoning about rules that represent knowledge, and are also expressive enough to dynamically compute and fetch more data when necessary. I hope that future work on the semantic web will lead into this direction.

z3t4 6y ago

I like the idea of type annotation in HTML eg itemscope="movie" , item="director" etc. Categorizing everything in the world will be a lot of work though. Schema.org is too limiting/general.

kstenerud 6y ago
Think of schema.org as the Yahoo of semantic authorities. Somewhat good, but doomed to be replaced in a few years when others do it much much better. The point is, you need these pioneers to help get the technology off the ground.