71–76 of 76 posts
I couldn't stress how important Wikidata (and its predecessor DBpedia) is as a public example of a huge knowledge graph (versus the ones hidden at big tech companies) but also as a Wikipedia-like collaborative project to organise all the knowledge among existing semantic web / linked data publishers, government open data, libraries, galleries, archives... Also remember that Wikidata is open source and you can fire up…
I couldn't stress how important Wikidata (and its predecessor DBpedia) is as a public example of a huge knowledge graph (versus the ones hidden at big tech companies) but also as a Wikipedia-like collaborative project to organise all the knowledge among existing semantic web / linked data publishers, government open data, libraries, galleries, archives... Also remember that Wikidata is open source and you can fire up…
What is RDF?
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Modern SQL can express arbitrary queries (including transitive closure ofc.) since it allows for recursive table expressions.
That's still some ways of from what I'd call "arbitrary" but yeah you can go quite far.
How so? What's practically missing?
Earlier quoted context omitted.
That's still some ways of from what I'd call "arbitrary" but yeah you can go quite far.
> That's still some ways of from what I'd call "arbitrary" How so? What's practically missing?
Basic (non-recursive) SQL: Finite paths
Recursive SQL / Transitive closure (with negation): Regular paths
However the hierarchy of languages doesn't end there. And some graph databases allow you to add arbitrary grammar rules, which make it possible to add some complex rules like:
- If condition X,Y and Z is satisfied then person A and B are the same person
- Equality is transitive
- If two people are equal then each property of one is also a property of the other.
The part that makes this tricky is that figuring out two people are equal can cause other people to now suddenly satisfy the condition for equality.
You could also construct some examples by creating conditions which aren't "regular" (e.g. person A and B have an ancestor which is the same number of generations back for both of them).
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The size of Wikidata knowledge base / relevant graph (as well as Linked Open Data Cloud KBs and other large KBs) certainly presents some challenges. However, I think that the largest challenge and, in fact, the main obstacle, for practical programmatic solutions is the use of essentially meaningless alphanumeric identifiers assigned to entities and properties. All corresponding identifiers need to be discovered first…
Why manually, when you have APIs to find Wikidata items and properties based on their labels, descriptions, aliases, data, metadata and use? If you mean autocomplete UI or tooltips, look no further than the query editor and its Ctrl+Space at https://query.wikidata.org/
*) Here is an example of the number of attributes for a single entity: https://www.wikidata.org/w/api.php?action=wbgetentities&ids=....
I wish all of you not to fall in the trap of ontologies. I worked very hard in this domain my conclusion is that all ontologies fail to scale eventually. I would recommend people in the field to go towards "perspectivism".
what does this mean in this context?