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

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.
Owen Amburhttps://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 PonsonRainbow Warriors Core FoundationCIAMSD Institute-ICT4D Program+2977459312PO Box 1154, OranjestadAruba, 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 Amburhttps://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 MiltonLet us know how you propose to advance this suggestionPDM
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 PonsonRainbow Warriors Core FoundationCIAMSD Institute-ICT4D Program+2977459312PO Box 1154, OranjestadAruba, Dutch Caribbean