Re: Reasoning with ontologies and knowledge graphs?

On Sat, 11 Dec 2021 at 12:00, Dave Raggett <dsr@w3.org> wrote:

> I am a member of the AIOTI WG Standardisation activity on semantic
> interoperability [1]. We are interested in getting a better feeling for
> what kinds of automated reasoning people are realising, or seeking to
> realise, with ontologies and knowledge graphs, along with the associated
> use cases.
>
> In principle, there are many opportunities for a wide variety of different
> forms of reasoning, including logical deduction and ontological entailment,
> induction, abduction, spatial and temporal reasoning, causal reasoning,
> plausible reasoning, qualitative reasoning, fuzzy reasoning, analogical
> reasoning and so forth. This spans approaches based on formal semantics,
> approaches based on probability theory, as well as informal approaches that
> mimic human reasoning.
>
> We welcome suggestions for designing a survey on automated reasoning.
>

Thanks for posing this question,  It's something I've asked myself a few
times

I've been using the semantic web for about 15 years for practical projects,
quite a lot for personal use

From my experience, it's rare that I have seen inferencing is used either
by myself, or in projects I've come across, however here was one tweet that
I collected:

https://twitter.com/bobdc/status/1318164165584891905

It uses a python script to transform data, and give back certain inferences

We used smushing a bit and (Inverse) Functional Properties in the tabulator
project w/ rdflib.js, but not all that much

I've seen domain and range discussed a few times, including in the
fediverse.  Perhaps this could used in conjunction with validations or
shapes.

I think today the de facto use of the semantic web is schema.org and iirc
https://schema.org/Person for example, I think no longer gives back machine
readable data, only html (I could be wrong)

So that leads me to think the value of the semantic web, is in the
namespacing rather than inferencing, or even shared schemas

A comment I heard on this recently: "make RDFS so light it's useless, and
OWL so complicated nobody uses it - always needed something in the middle,
that was clear from the get go", slightly tongue-in-cheek, but that did
resonate with me

I think inferencing would benefit from a rethink, if it is to gain more
traction

Very interested in practical experiences of others wrt inferencing,
particularly anything that has gained public traction

Personally, Id like to see a future of inferencing to look a bit more like
the python script above, and able to do data transformations from one form
to another.  I think that could have lots of practical applications


>
> [1] https://aioti.eu/wg_standardisation/
>
> Many thanks,
>
> Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett
> W3C Data Activity Lead & W3C champion for the Web of things
>
>
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