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

OK, here is a more precise description of what I am looking for in
knowledge representation.

First let's look at the Wikipedia page:
https://en.wikipedia.org/wiki/Knowledge_representation_and_reasoning

My dealing with knowledge in the vast domain of sustainable development
which interacts with all academic fields, has convinced me that knowledge
exists in context.

And then there is the resolution of knowledge, or more succinctly put
granularity of knowledge.

The Buddhist philosophy of Madhyamaka, The Middle Way utilizes dependent
origination to show the interdependence of phenomena.

When we Google "dependent origination and knowledge granularity" the
resulting AI Overview is really enlightening.

And when we Google "granularity of knowledge" in the search result the
following article stands out:

 I quote the following:
Abstract:
Granularity of knowledge has attracted attention of many researchers. This
paper concerns this issue from the rough set perspective. Granularity is
inherently connected with the foundation of rough set theory. The concept
of the rough set hinges on classification of objects of interest into
similarity classes, which form elementary building blocks (atoms, granules)
of knowledge. These granules are employed to define basic concepts of the
theory. In the paper basic concepts of rough set theory are defined and
their granular structure pointed out. Next the consequences of granularity
of knowledge for reasoning about imprecise concepts are discussed.

Jumping back to the Wikipedia page I want to highlight the article:
A Theory of Formalisms for Representing Knowledge,
https://ojs.aaai.org/index.php/AAAI/article/view/33674

It should now become apparent why both Paola and I are in essence talking
about the same thing, but since artificial intelligence is used to act upon
input, react to stimuli or solve problems etc. what we are implicitly
trying to build is knowledge representation and reasoning for AI.

Using rough set theory, category theory and other fields of mathematics
that define frames, frameworks, structures, templates, types or models we
find that my reasoning for classification of objects of interest in
similarity classes is well founded.
And the Wikipedia page summarizes IMHO pretty much everything that is
relevant for KR for AI.

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

On Fri, Jun 27, 2025, 09:23 Paola Di Maio <paoladimaio10@gmail.com> wrote:

> 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
>>>
>>>