Re: Knowledge representation for AI using domains or a universe of discourse

This is exactly right. The categorization in steps 1 and 2 is the way to go
but there may be a need to add at least one step before step 1.

Milton Ponson
Rainbow Warriors Core Foundation
CIAMSD Institute-ICT4D Program
+2977459312
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean

On Fri, Jun 27, 2025, 20:12 Peter Rivett <pete.rivett@federatedknowledge.com>
wrote:

> I'm not a member of IEEE to see the article.
> However the Wikipedia page is very good.
> One important point it makes is:
> "Every ontology is a treaty–a social agreement among people with common
> motive in sharing." There are always many competing and differing views
> that make any general-purpose ontology impossible.
>
> So what are we trying to achieve with knowledge representation, or even
> categorization of knowledge?
> If we're truly trying to enable AI then maybe we could envisage a
> multi-step process (possibly with a dedicated AI agent for each, linked in
> some sort of on-trend agentic architecture):
>
>    1. Understanding of the problem to be solved in terms of its domain,
>    granularity, and scope. This could even be decomposed into 3 sub-steps
>    e.g. for problem of "how many miles between San Diego and Los
>    Angeles", Domain = geospatial; Granularity =  city; scope = California
>    2. Find the appropriate representation(s) e.g. linked ontologies
>    3. Find the instance data (if not available for the representation it
>    might require revistign step 2)
>    4. Transform the problem into a query on the data in terms of the
>    representation
>    5. Transform the results into a form suitable for the user and for
>    feeding back into local context memory
>
>
> It seems to me that knowledge *categorization* could apply to steps 1 and
> 2.
>
> HAGW
> Pete
>
> Pete Rivett (pete.rivett@federatedknowledge.com)
> Federated Knowledge, LLC (LEI 98450013F6D4AFE18E67)
> tel: +1-701-566-9534
> Schedule a meeting at https://calendly.com/rivettp
>
> ------------------------------
> *From:* Milton Ponson <rwiciamsd@gmail.com>
> *Sent:* Friday, June 27, 2025 4:19 PM
> *To:* W3C AIKR CG <public-aikr@w3.org>; public-lod@w3.org <
> public-lod@w3.org>; public-cogai <public-cogai@w3.org>;
> paoladimaio10@googlemail.com <paoladimaio10@googlemail.com>
> *Subject:* Fwd: Knowledge representation for AI using domains or a
> universe of discourse
>
> I forgot the article link for the first abstract mentioned;
> Granularity of knowledge, indiscernibility and rough sets
> https://ieeexplore.ieee.org/document/687467
>
> Milton Ponson
> Rainbow Warriors Core Foundation
> CIAMSD Institute-ICT4D Program
> +2977459312
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
>
> ---------- Forwarded message ---------
> From: *Paola Di Maio* <paoladimaio10@gmail.com>
> Date: Fri, Jun 27, 2025, 09:23
> Subject: Re: Knowledge representation for AI using domains or a universe
> of discourse
> To: Milton Ponson <rwiciamsd@gmail.com>
> Cc: Owen Ambur <owen.ambur@verizon.net>, W3C AIKR CG <public-aikr@w3.org>,
> public-cogai <public-cogai@w3.org>, <public-lod@w3.org>
>
>
> Milton, Great to see you engage with the topic and with the categorization
> of knowledge
>
> I am reminded that several knowledge categorization systems exist
>
> It would be relevant to us to understand how the traditional knowledge
> categories that you cite
> rooted in epistemoligy, relate to the knowledge representation for AI
> *which is the focus of this CG
>
> The knowledge domain for AI KR is not the domain of 'knowledge
> categorization'
>  it would be nonetheless be very relevant to KR, perhaps to explore and
> make explicit the relations between the two
>
> PDM
>
>
> On Thu, Jun 26, 2025 at 8:49 PM Milton Ponson <rwiciamsd@gmail.com> wrote:
>
> Excellent. And ChatGPT made recommendations about expanding, tweaking and
> refining domains in line with my review of my initial list. I think we can
> make additional refinements by adding a not exhaustive list of directives,
> guidelines, legislation ( in casu EU, the Eu AI Act) currently existing in
> countries worldwide for ethical, open, accountable,  trustworthy etc AI use.
>
> Milton Ponson
> Rainbow Warriors Core Foundation
> CIAMSD Institute-ICT4D Program
> +2977459312
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
>
> On Wed, Jun 25, 2025, 23:10 Owen Ambur <owen.ambur@verizon.net> wrote:
>
> Milton, while I can imagine there might be quite a lot of quibbling over
> the domains, this additional information is now included at
> https://stratml.us/docs/EARP.xml#uuid-1f8a0ae6-1b0a-4d1b-a201-5c8c9d1c8c01
>
> ChatGPT suggests some potential modifications
> <https://chatgpt.com/share/685cb98a-dd68-800b-b751-971c639406f9>.
>
> Owen Ambur
> https://www.linkedin.com/in/owenambur/
>
>
> On Wednesday, June 25, 2025 at 12:48:02 PM EDT, Milton Ponson <
> rwiciamsd@gmail.com> wrote:
>
>
> Thanks Owen,
>
> I sense you were on to what I intend to do. Because the United Nations has
> the UNESCO, WIPO, ISO, and UNSD (UN Statistics Division) which together
> deal with various aspects of data and information, standardization and
> intellectual property rights issues, for scientific knowledge the process
> is more or less straightforward.
>
> In the UN universe of discourse, knowledge is is a concept spanning many
> domains of discourse. Traditional, indigenous and orally transmitted
> knowledge is the first category.
> It is currently being dealt with through SIL (https://www.sil.org),
>  UNESCO and several initiatives by organizations of indigenous peoples
> dealing with AI, traditional knowledge, data and knowledge sovereignty
> issues.
>
> All the other categories of knowledge and data can be categorized either
> by universal subject coding sysyems, structured text components, or
> enumeration of informal text parameters. Semiotics, symbol sets,
> pictograms, petroglyphs and alphabets, spectral data are general categories
> which help define knowledge objects.
>
> What needs to be done is to create a universal categorization for
> knowledge over the following domains of discourse:
>
>    - Mathematics;
>    - Computer Science;
>    - Physics and Astronomy;
>    - Chemistry, Biology and Biochemistry;
>    - Medical, Health and Life Sciences, including Genomics and Pharmacy;
>    - Earth Sciences; dealing with lithosphere, hydrosphere and atmosphere
>    - Marine Science including Oceanography;
>    - Engineering and Materials Sciences;
>    - Languages and Computational Linguistics;
>    - Philosophy;
>    - Social Sciences, including History, Political Sciences, Sociology
>    and Anthropology;
>    - Art, Cultural and Creative Design Studies;
>    - Education, Vocational and Professional Training;
>    - Economics, Econometrics and Statistics;
>    - Political Sciences, and Law;
>    - Business and Public Sector Management.
>
> Milton Ponson
> Rainbow Warriors Core Foundation
> CIAMSD Institute-ICT4D Program
> +2977459312
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
>
> On Wed, Jun 25, 2025, 11:54 Owen Ambur <owen.ambur@verizon.net> wrote:
>
> To help me make sense of this, I prompted ChatGPT to render a plan in
> StratML Part 2 format, which is now available at
> https://stratml.us/drybridge/index.htm#EARP or, more specifically,
> https://stratml.us/docs/EARP.xml
>
> Owen Ambur
> https://www.linkedin.com/in/owenambur/
>
>
> On Tuesday, June 24, 2025 at 10:48:45 PM EDT, Paola Di Maio <
> paola.dimaio@gmail.com> wrote:
>
>
> Thank you Milton
> Let us know how you propose to advance this suggestion
> PDM
>
> On Wed, Jun 25, 2025 at 6:27 AM Milton Ponson <rwiciamsd@gmail.com> wrote:
>
> Dear all,
>
> We have reached the point in time where we must start to generalize the
> basis of knowledge representation for artificial intelligence.
>
> In order to do so we must find (a) common denominator(s) for the different
> types of knowledge.
>
> Assuming that the knowledge is digitized we can use the concept of the
> universe of discourse or more specifically domains of discourse.
>
> These concepts lend themselves for use of set theory, type theory etc. and
> allow modeling and constructibility of consistent logical frameworks.
>
> And they also allow the use of (hyper)graphs, algebraic geometry, category
> theory etc. to allow knowledge representation in ways that can be captured
> for data (structure) creation, data analysis and machine learning.
>
> In addition we can use classification systems to uniquely identify domains
> of discourse as librarians do and as mathematicians do as well with the
> Mathematics Subject Classification.
>
> This can lead to a much more efficient use of datasets, the use of which
> can be negotiated with the respective owners, avoiding the current
> intellectual property and data rights, data and knowledge sovereignty
> debates.
>
> The indiscriminate use of scraping and unlimited production of internet
> content by artificial intelligence is contaminating available data.
>
> After having examined the current use of artificial intelligence for
> solving sustainable development problems, both at global, regional and
> local levels, the use of (open) curated and/or standardized datasets is the
> only way to go.
>
> This requires the use of a universe of discourse and more specifically
> domains of discourse.
>
>
> Milton Ponson
> Rainbow Warriors Core Foundation
> CIAMSD Institute-ICT4D Program
> +2977459312
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
>
>