Re: KG as KR as rubbish?

Le mer. 28 août 2019 à 07:40, Paola Di Maio <paola.dimaio@gmail.com> a écrit :
>
> I do not normally like to call stuff I disagree with  rubbish. I rarely do that.
>
> but To propose KG as the future of KR sounds like complete rubbish to me
> (shall try to justify this statement more scientifically)


It would be best but getting into the actual analysis of all the poor
work around it would take much time. I was teached to "be positive"
and "show the way" instead of being not-very-diplomatic.

> I am shocked to see the cream of our research community being part of this
> disinformation campaign
> /aic.ai.wu.ac.at/~polleres/publications/bona-etal-DagstuhlReport18371.pdf


To this I heartedly agree. For once in my life I can say "I was there"
in the sense I was involved in graph database related work since 2011.
And since that time a massive marketing campaign was happening when
marketing is involved little or no Science is involved.

Here is the thing that I skimmed, if anyone else wants to shim in the
conversation:

- http://blog.liu.se/semanticweb/2018/09/15/dagstuhl-seminar-on-knowledge-graphs/
- https://thinklinks.wordpress.com/2018/09/18/trip-report-dagstuhl-seminar-on-knowledge-graphs/
- http://www.juansequeda.com/blog/2018/09/18/trip-report-on-knowledge-graph-dagstuhl-seminar/
- https://aic.ai.wu.ac.at/~polleres/presentations/20190827DEXA_keynote.pdf :(
- https://aic.ai.wu.ac.at/~polleres/publications/bona-etal-DagstuhlReport18371.pdf
- http://www.mkbergman.com/2244/a-common-sense-view-of-knowledge-graphs/
- First thread in
https://lists.w3.org/Archives/Public/semantic-web/2019Aug/thread.html

To repeat myself from a previous post, KG is mostly a marketing
slogan. Still, it might have good ideas and (closed) implementation.

To me the primary mistake they do in the above writings is that they
mix successful results of closed source software companies with the
blurry view they have of it and knowledge representation (KR). They
take the shortcut of saying that "KG is the way to go" because that is
the marketing term those successful companies choose to use for some
reasons. (KG is easier to spell and say that KR...)

The idea of what KG / KR is or should be is still blurry.

There is always a gap between what you want to express or represent
and the implementation because physical limitations. Take for instance
the relational-database-management-systems (RDBMS) which are at the
end of the day .csv files on steroids. They draw on paper or
blackboard using a graph. Are they graph? Yes! Everything is graph.
Are they Knowledge Graph: Yes! They represent knowledge, rows can
relate to each other so they are definitely graph in the common sense
not just single dot points in vast empty space. They are graphs, but
still we do not call them graphs or knowledge graph.

Something I note in the SW thread is that at least LinkedIn, Ebay,
Apple, WikiData, Uber and maybe Google are relying on some software
implementation that relates to n-tuple store (or chunks store). To me
it means that n-tuple stores are not a mistakes in terms of
implementation and are not a mistake in terms of representation even
if less common sense compared to property graphs. At the end of the
day, it is very clear to me that Ordered Key-Value Store (OKVS) are
the future of database management. And on top of OKVS, n-tuple
(chunks) is a very good candidate compared to other approaches because
it is both sparse, relational and more powerful that "document store"
approach (like mongodb). Any way all those consideration are mostly
implementation details.

Maybe what happens to KG vs. KR is what happened to Probabilistic
Models vs. Machine Learning (don't quote me on that :).

NB: KG as in property-graph ala neo4j is not a bullet proof solution
to data problems modern applications are facing.

Received on Wednesday, 18 September 2019 20:34:02 UTC