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== Agenda ==
== Agenda ==
Second Synthesis Session
Second Synthesis Session
* '''[[KenBaclawski|Ken Baclawski]]''' ''Synthesis II''
* [https://ontologforum.s3.us-east-1.amazonaws.com/OntologySummit2025/Synthesis/SynthesisTopicOutline--KenBaclawski_20250514.pdf Slides]
* [https://ontologforum.s3.us-east-1.amazonaws.com/OntologySummit2025/Synthesis/SecondSynthesis_20250514.mp4 Video Recording]


== Conference Call Information ==
== Conference Call Information ==
Line 31: Line 34:


== Discussion ==
== Discussion ==
12:17 Gary Berg-Cross: From my synthesis of track 1, Barry's perspective on ontology suggests that physics and mathematics operate independently, with some relationships between them. While classical physics aligns with common-sense notions, modern physics—especially in the quantum realm—relies on mathematical models rather than truthmakers grounded in direct experience.  As part of this, it examined the role of PhysO, an ontology designed to structure physics concepts, and the broader implications of mathematical entities in ontology development. We can have a Common-Sense Views and Scientific Formalization which hypothesizes that our natural attitude toward reality is shaped by evolution and culture, guiding our common-sense understanding of nature. Scientific investigation extends and refines this view, allowing formalization through universal laws that describe relationships between elements—such as reducing sound perception to electromagnetic interactions.
12:19 Alex Shkotin: Our focus is formal ontologies, i.e. theoretical knowledge formalization.
12:20 TS: How does a rectangle ‘behave’?<br/>
12:23 TS: Then perhaps ‘quality’ is a better description (rather than ‘behavior’).<br/>
12:44 Ken Baclawski: Here is the link to my paper on the square/rectangle problem: https://ken.baclawski.org/pub/1994/02/public.pdf
12:27 Gary Berg-Cross: From my summary from Track 1 to help improve Ken's table : "Is Mathematics the Foundation of Modern Physics?
Modern physics depends on mathematical entities to interpret measurements but lacks an ontology of physical reality itself—such as Basic Formal Ontology (BFO). Physics equations describe causal relationships, but they do not cause anything themselves. Instead, they serve as models with explanatory or predictive power. For example, Newton’s equations describe the solar system as a gravitational system, providing powerful predictions and explanations for observable phenomena."
12:28 TS: Barry is coming around to understand the importance of the natural language terms used in an ontology.<br/>
12:30 TS: Barry had a large influence in biomedical fields.<br/>
12:31 TS: Terry seems to be referring to biases.<br/>
12:32 TS: A job of an ontologist is to wade through the biases.
12:34 Gary Berg-Cross: As Barry's work math concepts like point implies - "Unlike physical objects, mathematical entities are idealized, existing outside the causal world of time and change. They are:
• Intrinsically intelligible
• Known a priori
• Mind-dependent but independent of sensory experience
Mathematical entities are used across disciplines—including physics, chemistry, and computer science—to model reality, but they do not directly correspond to something in reality."
12:39 TS: An ontology is a model,
12:42 Gary Berg-Cross: I like including this summary in the synthesis
12:43 Alican Tüzün: Reacted to "{4CF03EE2-11BE-4523-B101-EEAF28A573E5}.png" with 👍
12:47 Gary Berg-Cross: There is also each cognitive agent's perspective on words and what propositions mean.  That is part of how language understanding works.  Think of the Triangle of Meaning.<br/>
12:49 Gary Berg-Cross: Surfacing assumptions is what conceptual analysis and unpacking is all about.
12:50 TS: ‘surfacing assumptions’ is part of the analysis that should be done during ontology development.
12:51 Gary Berg-Cross: Achieving seamless data and model integration/interoperability across domains requires strategies to handle incompatibilities and ensure modularity.  What did we get out of the Summit on this?
12:56 TS: Assuming computable ontologies are engineered artifacts, then they have a scope (of applicability) which may or may not provide the ‘level’ of interoperability desired. But then depending on how well the ontologies were created, their ‘scope’ may be able to be extended.
12:56 Gary Berg-Cross: I hope that the 2025 summit advanced our understanding toward interoperability, accuracy, and meaningful representation of reality. What can we say about that as part of a synthesis? We want to show how on ontologies with their features may provide a structured approach to explanation, axiomatization, and formal semantics and then say how they address or don't address challenges in areas like physics, measurement, and molecular structures.
* 13:02 janet singer: 👍
12:57 Alex Shkotin: @TS we should know how to apply theoretical knowledge.
12:58 TS: Alex, that’s where creativity comes in.
12:58 Alex Shkotin: yes, but education first.
12:59 TS: Education, yes. My ignorance knows no bounds🙁
13:00 Gary Berg-Cross: At the agent level following Piaget, pre-existing agent knowledge structures impose a degree of guidance, affordance, or constraint on the development of new knowledge. In more common terms, we do sensemaking - make sense using our memories and perceptions, including new experiences and information.  This is interpretation/assimilation in light of what we already know. We recognize and comprehend the familiar by reference to what we already know, of course, but we also make sense of novel experiences by comparison and analogy with what we already know. And math is one area we use.
13:01 Alex Shkotin: we learn theories to apply it to solve problems.
13:01 janet singer: Piaget should be brought into these issues more
13:03 TS: In terms of formalization, because she did allude to some of the aspects that Gary had just been mentioning.
You know, with regard to interoperability and performance and so on.
So no matter what assumptions you want to make. If you want to get paid, you got to get something working.
And then there are requirements that you need to conform to and decisions you have to make and assumptions that you may have to validate or invalidate, or you have to make in order to get your result to actually do what you want it to do.
13:05 janet singer: An ontology as a specification of a conceptualization is a model; the conceptualization is a theory of what an agent needs to make distinctions and act appropriately in a domain
13:06 janet singer: The agent’s interpretation of a symbol/signal is a matter of their theory
* 13:07 Alex Shkotin: theory is something but conceptualization is one of activities to get theory.
* 13:07 TS: Janet, “agent’s interpretation of a symbol/signal is a matter of their theory” ??
* 13:08 TS: Janet, more specifically, how should I understand “…their theory”?
* 13:08 Alex Shkotin: Turing machine does not have theory.
* 13:09 TS: Does a Turing machine represent a theory?
* 13:09 Alex Shkotin: We may have theory about particular T-mach.
* 13:10 janet singer: The reading head embodies a theory
13:10 janet singer: Todd, the reasoner needs to have an embodied theory of what is significant in their domain and how to respond appropriately to signs


== Resources ==
== Resources ==
* [https://ontologforum.s3.us-east-1.amazonaws.com/OntologySummit2025/Synthesis/SynthesisTopicOutline--KenBaclawski_20250514.pdf Topic Outline Slides]
* [https://ontologforum.s3.us-east-1.amazonaws.com/OntologySummit2025/Synthesis/SecondSynthesis_20250514.mp4 Session Video Recording]


== Previous Meetings ==
== Previous Meetings ==

Latest revision as of 15:40, 21 May 2025

Session Synthesis
Duration 1 hour
Date/Time 14 May 2025 16:00 GMT
9:00am PDT/12:00pm EDT
5:00pm BST/6:00pm CEST
Convener Ken Baclawski

Ontology Summit 2025 Synthesis

Agenda

Second Synthesis Session

Conference Call Information

Discussion

12:17 Gary Berg-Cross: From my synthesis of track 1, Barry's perspective on ontology suggests that physics and mathematics operate independently, with some relationships between them. While classical physics aligns with common-sense notions, modern physics—especially in the quantum realm—relies on mathematical models rather than truthmakers grounded in direct experience. As part of this, it examined the role of PhysO, an ontology designed to structure physics concepts, and the broader implications of mathematical entities in ontology development. We can have a Common-Sense Views and Scientific Formalization which hypothesizes that our natural attitude toward reality is shaped by evolution and culture, guiding our common-sense understanding of nature. Scientific investigation extends and refines this view, allowing formalization through universal laws that describe relationships between elements—such as reducing sound perception to electromagnetic interactions.

12:19 Alex Shkotin: Our focus is formal ontologies, i.e. theoretical knowledge formalization.

12:20 TS: How does a rectangle ‘behave’?
12:23 TS: Then perhaps ‘quality’ is a better description (rather than ‘behavior’).
12:44 Ken Baclawski: Here is the link to my paper on the square/rectangle problem: https://ken.baclawski.org/pub/1994/02/public.pdf

12:27 Gary Berg-Cross: From my summary from Track 1 to help improve Ken's table : "Is Mathematics the Foundation of Modern Physics? Modern physics depends on mathematical entities to interpret measurements but lacks an ontology of physical reality itself—such as Basic Formal Ontology (BFO). Physics equations describe causal relationships, but they do not cause anything themselves. Instead, they serve as models with explanatory or predictive power. For example, Newton’s equations describe the solar system as a gravitational system, providing powerful predictions and explanations for observable phenomena."

12:28 TS: Barry is coming around to understand the importance of the natural language terms used in an ontology.
12:30 TS: Barry had a large influence in biomedical fields.
12:31 TS: Terry seems to be referring to biases.
12:32 TS: A job of an ontologist is to wade through the biases.

12:34 Gary Berg-Cross: As Barry's work math concepts like point implies - "Unlike physical objects, mathematical entities are idealized, existing outside the causal world of time and change. They are: • Intrinsically intelligible • Known a priori • Mind-dependent but independent of sensory experience

Mathematical entities are used across disciplines—including physics, chemistry, and computer science—to model reality, but they do not directly correspond to something in reality."

12:39 TS: An ontology is a model,

12:42 Gary Berg-Cross: I like including this summary in the synthesis

12:43 Alican Tüzün: Reacted to "{4CF03EE2-11BE-4523-B101-EEAF28A573E5}.png" with 👍

12:47 Gary Berg-Cross: There is also each cognitive agent's perspective on words and what propositions mean. That is part of how language understanding works. Think of the Triangle of Meaning.
12:49 Gary Berg-Cross: Surfacing assumptions is what conceptual analysis and unpacking is all about.

12:50 TS: ‘surfacing assumptions’ is part of the analysis that should be done during ontology development.

12:51 Gary Berg-Cross: Achieving seamless data and model integration/interoperability across domains requires strategies to handle incompatibilities and ensure modularity. What did we get out of the Summit on this?

12:56 TS: Assuming computable ontologies are engineered artifacts, then they have a scope (of applicability) which may or may not provide the ‘level’ of interoperability desired. But then depending on how well the ontologies were created, their ‘scope’ may be able to be extended.

12:56 Gary Berg-Cross: I hope that the 2025 summit advanced our understanding toward interoperability, accuracy, and meaningful representation of reality. What can we say about that as part of a synthesis? We want to show how on ontologies with their features may provide a structured approach to explanation, axiomatization, and formal semantics and then say how they address or don't address challenges in areas like physics, measurement, and molecular structures.

  • 13:02 janet singer: 👍

12:57 Alex Shkotin: @TS we should know how to apply theoretical knowledge.

12:58 TS: Alex, that’s where creativity comes in.

12:58 Alex Shkotin: yes, but education first.

12:59 TS: Education, yes. My ignorance knows no bounds🙁

13:00 Gary Berg-Cross: At the agent level following Piaget, pre-existing agent knowledge structures impose a degree of guidance, affordance, or constraint on the development of new knowledge. In more common terms, we do sensemaking - make sense using our memories and perceptions, including new experiences and information. This is interpretation/assimilation in light of what we already know. We recognize and comprehend the familiar by reference to what we already know, of course, but we also make sense of novel experiences by comparison and analogy with what we already know. And math is one area we use.

13:01 Alex Shkotin: we learn theories to apply it to solve problems.

13:01 janet singer: Piaget should be brought into these issues more

13:03 TS: In terms of formalization, because she did allude to some of the aspects that Gary had just been mentioning. You know, with regard to interoperability and performance and so on. So no matter what assumptions you want to make. If you want to get paid, you got to get something working. And then there are requirements that you need to conform to and decisions you have to make and assumptions that you may have to validate or invalidate, or you have to make in order to get your result to actually do what you want it to do.

13:05 janet singer: An ontology as a specification of a conceptualization is a model; the conceptualization is a theory of what an agent needs to make distinctions and act appropriately in a domain 13:06 janet singer: The agent’s interpretation of a symbol/signal is a matter of their theory

  • 13:07 Alex Shkotin: theory is something but conceptualization is one of activities to get theory.
  • 13:07 TS: Janet, “agent’s interpretation of a symbol/signal is a matter of their theory” ??
  • 13:08 TS: Janet, more specifically, how should I understand “…their theory”?
  • 13:08 Alex Shkotin: Turing machine does not have theory.
  • 13:09 TS: Does a Turing machine represent a theory?
  • 13:09 Alex Shkotin: We may have theory about particular T-mach.
  • 13:10 janet singer: The reading head embodies a theory

13:10 janet singer: Todd, the reasoner needs to have an embodied theory of what is significant in their domain and how to respond appropriately to signs

Resources

Previous Meetings

 Session
ConferenceCall 2025 05 07Track 4
ConferenceCall 2025 04 30Track 4
ConferenceCall 2025 04 23Track 4
... further results

Next Meetings

 Session
ConferenceCall 2025 05 21Commnuniqé
ConferenceCall 2025 06 04Commnuniqé
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