4 ms·

In my ears, knowledge graph sounds a bit grandiloquent. I do not have a definition, but I know that when talking about knowledge as it is embodied in people, it

In my ears, knowledge graph sounds a bit grandiloquent. I do not have a definition, but I know that when talking about knowledge as it is embodied in people, it's quite a subtle thing, hard to formalize and to be honest, something relatively rare. Why can we just call these things fact databases? Add. Knowledge evokes a lot of other associations as well, for example that what we are able to know changes over time. That a time has a certain underlying grid, into which certain factual stories appear and later disappear.

pphysch 4y ago
> Why can we just call these things fact databases? Companies that want to reinvent/repackage and sell boring RDBMS tech
- drpyser22 4y ago
  Its not rdbms though. It's RDF, triple store, graph-like data models.
  - pphysch 4y ago
    Those are easy to implement on top of RDBMS. Query performance is a different thing, which can only be evaluated on a case-by-case basis, but you can go a long way with good indexes. A few companies need real time analytics on really big graphs. Most don't and shouldn't waste their time with fancy Google-scale databases.
- nl 4y ago
  A Knowledge Graph is the data in the database, not the tech. You can absolutely implement this in a RDBMS. There are some advantages to a proper graph database though. But SPARQL is a dead-end - I don't think anyone is really using that in practice outside a dew public demonstration apps. To a large extent this is true of RDF too: triples are useful, RDF gets in the way.
  - ta988 4y ago
    Wikidata is a good example of something that works. But I agree there isn't much else.
    - afandian 4y ago
      Except the software it’s powered by, Blazegraph, by is deprecated (afaict the devs were poached by AWS to work on Neptune). https://phabricator.wikimedia.org/T206560 https://phabricator.wikimedia.org/T206560
      - ta988 4y ago
        Unfortunately yes, there were discussions about switching to another one not sure where they stand, looks like according to your link not that far...
  - namedgraph 4y ago
    That's just bullshit. Stop spreading FUD. We participated in a huge RfP for a pharma company which planned RDF KG infrastructure for the next couple of years with 500 billion triple capabilities. Biomedical, finance, defence, automotive -- all of those industries are using RDF/SPARQL. Just because your problems are not big or complex enough doesn't mean this tech is not used. It takes a certain organization size for Knowledge Graphs to make sense and pay off, that's why most industry users are Fortune 500-level companies.
hobofan 4y ago
> Why can we just call these things fact databases? Because (in theory) they are much much more than that. In practice the semantic web/data space has a problem of building complicated standard on top of complicated standard (as well as having a Java implementation monoculture, which doesn't help that). That also makes it hard to formalize all the non-trivial statements that are part of our knowledge. And yes, there are subtle aspects to knowledge, that is usually not capturable easily in manually formalized knowledge graphs, but that's where pairing knowledge graphs with ML-based methods (e.g. vector search) can really shine.
namedgraph 4y ago
Google started calling it Knowledge Graph 10 years ago: https://en.wikipedia.org/wiki/Google_Knowledge_Graph https://en.wikipedia.org/wiki/Google_Knowledge_Graph Then everyone else followed.

pphysch 4y ago

> Why can we just call these things fact databases? Companies that want to reinvent/repackage and sell boring RDBMS tech

drpyser22 4y ago
Its not rdbms though. It's RDF, triple store, graph-like data models.
- pphysch 4y ago
  Those are easy to implement on top of RDBMS. Query performance is a different thing, which can only be evaluated on a case-by-case basis, but you can go a long way with good indexes. A few companies need real time analytics on really big graphs. Most don't and shouldn't waste their time with fancy Google-scale databases.
nl 4y ago
A Knowledge Graph is the data in the database, not the tech. You can absolutely implement this in a RDBMS. There are some advantages to a proper graph database though. But SPARQL is a dead-end - I don't think anyone is really using that in practice outside a dew public demonstration apps. To a large extent this is true of RDF too: triples are useful, RDF gets in the way.
- ta988 4y ago
  Wikidata is a good example of something that works. But I agree there isn't much else.
  - afandian 4y ago
    Except the software it’s powered by, Blazegraph, by is deprecated (afaict the devs were poached by AWS to work on Neptune). https://phabricator.wikimedia.org/T206560 https://phabricator.wikimedia.org/T206560
    - ta988 4y ago
      Unfortunately yes, there were discussions about switching to another one not sure where they stand, looks like according to your link not that far...
- namedgraph 4y ago
  That's just bullshit. Stop spreading FUD. We participated in a huge RfP for a pharma company which planned RDF KG infrastructure for the next couple of years with 500 billion triple capabilities. Biomedical, finance, defence, automotive -- all of those industries are using RDF/SPARQL. Just because your problems are not big or complex enough doesn't mean this tech is not used. It takes a certain organization size for Knowledge Graphs to make sense and pay off, that's why most industry users are Fortune 500-level companies.

hobofan 4y ago

> Why can we just call these things fact databases? Because (in theory) they are much much more than that. In practice the semantic web/data space has a problem of building complicated standard on top of complicated standard (as well as having a Java implementation monoculture, which doesn't help that). That also makes it hard to formalize all the non-trivial statements that are part of our knowledge. And yes, there are subtle aspects to knowledge, that is usually not capturable easily in manually formalized knowledge graphs, but that's where pairing knowledge graphs with ML-based methods (e.g. vector search) can really shine.

namedgraph 4y ago

Google started calling it Knowledge Graph 10 years ago: https://en.wikipedia.org/wiki/Google_Knowledge_Graph https://en.wikipedia.org/wiki/Google_Knowledge_Graph Then everyone else followed.