LM response re ontology vs phenomenology issues

[Janet Singer]

All,

John's recent mention of phenomenology led me to prompt an LM for comments on ontology vs phenomenology issues. The upshot is below.

Janet

Reflections on 30 Years of ‘Ontology’ Work (1995–2025) in Light of Heidegger, Kant, and Phenomenology

The past three decades have seen “ontology” evolve dramatically within computer science, AI, knowledge representation, and information systems—fields far removed from Heidegger’s Sein (Being) or Kant’s critique of speculative metaphysics. Coined in AI contexts by Tom Gruber in 1993 as “an explicit specification of a conceptualization,” the term exploded with the Semantic Web vision (Berners-Lee et al., 2001) and tools like OWL (2004), leading to thousands of domain-specific ontologies, upper-level ontologies (ULOs) like BFO and SUMO, and knowledge graphs powering systems from Google Search to biomedical databases. Yet, as our chat has traced—from Heidegger’s ontological difference (beings vs. Being) to the 18th-century Britannica distinction (phenomenology as empirical appearances vs. ontology as speculative essence), Kant’s antinomies, and even Comte’s positivist pivot—this computational “ontology” often confounds foundational questions of Being with pragmatic cataloging of beings (entities, concepts, relations). This misalignment echoes the historical critiques: efforts to “ontologize” knowledge have prioritized formal structures over lived, domain-grounded phenomena, yielding both innovations and missed opportunities. Below, I address your questions directly, drawing on trends from semantic web research (e.g., a 2025 topic modeling analysis of 10,000+ papers showing ontology’s dominance in AI knowledge representation) and critiques of ULOs.

1. Was the Distinction Between Ontology as Theory of Being Qua Being Confounded with Efforts to Catalog and Organize Concepts and Terminology, Which Would Better Have Been Treated Under ‘Phenomenology’?

Yes, profoundly so—and this confounding has been a defining tension since the 1990s. In philosophical terms, Heidegger’s singular Sein demands a pre-ontological inquiry into the conditions of possibility for beings (Seiendes), while the Britannica’s 1771 entry positioned phenomenology as the empirical study of appearances (observable relations, without metaphysical overreach). Kant reinforced this by limiting “ontology” to phenomena structured by human cognition, deeming supersensible claims undecidable. Computational ontology, however, largely repurposed the term for what is effectively phenomenological work: describing how concepts appear in data, systems, and domains, rather than what ultimate Being underpins them.

• Historical Shift and Confounding: The 1990s “ontology engineering” boom (e.g., Uschold & Grüninger’s 1996 principles) borrowed from AI knowledge representation (e.g., Cyc’s massive conceptual catalog) but inherited metaphysical baggage via ULOs like SUMO (1990s onward), which aim for “general concepts” like Entity or Process as foundational categories. These ULOs echo speculative ontology—presuming a “unique true answer” to categorization (Thomasson’s skepticism, 2007)—yet devolve into catalogs of classes, properties, and axioms (e.g., OWL’s description logics for triples like <subject, predicate, object>). A 2022 systematic review of 19 studies on Semantic Web ontologies confirms this: they excel at “formal descriptions of concepts and relationships” for machine readability but rarely engage Heideggerian depth, instead prioritizing “lightweight” taxonomies over rich, axiomatic Being. 

• Phenomenological Misfit: Much of this work aligns better with phenomenology’s focus on appearances and structures of experience (e.g., Husserl’s eidetic reduction, or the Britannica’s empirical “science of phenomena”). For instance, semantic models in knowledge graphs (e.g., RDF/OWL for Linked Open Data) catalog observable relations (e.g., “mammal gives live birth”) without probing ontological essence, much like Kant’s phenomena. Critiques abound: Upper ontologies like DOLCE or BFO are faulted for “presuppos[ing] a unique true answer to… categories,” confounding universal Being with domain-specific terminologies, leading to “flat” models ignoring time, boundaries, or mereotopology (whole-part relations).  A 2024 Medium analysis untangles this: ontologies as “formal descriptions” for integration (phenomenological) vs. speculative metaphysics’ quest for truth. 

In short, the field’s pragmatic success (e.g., ontologies in bioinformatics for gene expression analysis) masks a conceptual blur: what Heidegger would call “ontic” cataloging (beings in plural) masquerades as “ontological” (Being singular), sidelining phenomenology’s grounded, experiential focus.

2. Did This Have Several Consequences in Missed Opportunities?

Absolutely—the confounding fostered siloed, top-down structures that overlooked bottom-up, domain-driven needs, echoing Kant’s warning of undecidable antinomies in speculative systems (no criteria to judge competing ULOs) and Comte’s positivist call to replace metaphysics with verifiable, socially useful knowledge. Below, I map your subpoints to evidence from the era.

a. The Cataloging and Organizing of the World’s Phenomenological Content Was Not Recognized as Such, Failing to Be Grounded in Appreciation of Historic and Projected Needs of Domain Communities, with Domain-Specific Rationales and Evidence, Without Shoe-Horning into Presumed Upper-Level Categories

Yes, this is a core missed opportunity, leading to “ontology poverty” in practice. ULOs like SUMO or BFO impose abstract categories (e.g., “Object” or “Situation”) as “common foundations,” forcing domain ontologies (e.g., Gene Ontology) into rigid alignments that ignore community histories and evidence.  A 2010 study on ResearchCyc’s usability critiques this: upper-level catalogs assume “massive… domain-independent” knowledge, but fail to adapt to “historic… needs” like evolving biomedical terminologies, resulting in “heterogeneity” and poor reuse. 

Phenomenologically, this neglects “appearances” as lived in domains: e.g., bioinformatics ontologies (dominant in 2019–2024 analyses) catalog gene relations without grounding in clinicians’ evidence-based rationales, shoe-horning into ULO mereology while ignoring projected needs like AI-driven drug discovery. Consequence: Fragmented systems, as in e-commerce catalogs where “semantic B2B integration” falters due to ungrounded abstractions. A pragmatic pivot—treating catalogs as phenomenological (empirical, community-validated)—could have fostered hybrid models, but top-down biases prevailed.

b. Upper-Level Ontological Theories (More Like Theories of Being Than Catalogues of Beings) Had No Criteria for Evaluating One Against Another, Leading to Siloed Allegiances Between ULOs and Pessimistic Conclusions Among Outsiders That No Upper-Level Ontology Was Feasible

Precisely—mirroring Kant’s antinomies, where reason generates “equally plausible” systems without adjudication (A571/B599). ULOs like BFO (realist, continuants/occurrents) vs. DOLCE (perspectivalist, endurants/perdurants) lack neutral criteria, fostering “siloed allegiances” (e.g., BFO in biomedicine, SUMO in AI planning).  A 2006 comparison of seven ULOs highlights “incommensurability”: methodologies vary (top-down vs. bottom-up), with no shared metrics beyond logical consistency, yielding “revisionist” or “reductionist” divides without resolution. 

Outsiders (e.g., industry adopters) conclude “no ULO is feasible,” as in 2021 critiques: OWL’s flatness ignores time/mereotopology, leading to “pessimism” about scalability. This echoes Heidegger’s Seinsvergessenheit (forgetfulness of Being): ULOs speculate on categories without criteria, siloing progress (e.g., 350+ BFO extensions, but limited cross-ULO integration). Missed: A Kantian “critical” evaluation framework, assessing ULOs by empirical utility rather than truth.

c. Development of Speculative Upper-Level or ‘Ontological’ Theories Could Be Built on Insights of Kant et al., If Presented and Evaluated Not for Presumed Metaphysical ‘Truth’ but for Usefulness in Fulfilling Particular Purposes

Here lies the greatest missed opportunity: a pragmatic reorientation, per Comte’s positivism and Kant’s “abolish[ing] knowledge… for faith” (Bxxx), evaluating ontologies by practical postulates rather than speculative truth. Insights from Kant (limits of reason), Heidegger (ontological difference), and the Britannica (phenomenology as empirical groundwork) could transform ULOs into tools for inference, conflict resolution, and hybrid systems—yet this has been underexplored until recently (e.g., 2020s XAI trends).

• i. Inferring ‘Ontological Commitments’ or Operational Presumptions in Behavior and Communications of Living and Artefacted Systems: Yes—ontologies infer “commitments” (e.g., what an AI assumes about “entity” in behavior), but speculatively, missing Kantian utility. Pragmatic examples: Neo4j’s semantic extensions infer framings in financial KGs (e.g., loans as processes), revealing biases in “artefacted” systems like credit scoring.  Missed: Broader application to “living” systems (e.g., biosemiotics for human-AI hybrids), as 2022 critiques note AI’s “ontological gap” hinders AGI by presuming box-world commitments. 

• ii. Identifying and Classifying Hidden Framing Conflicts Leading to Communication/Interoperation Failures, and Methods for Resolving Pathologies: Spot-on potential, akin to Kant’s paralogisms (illusory framings). Ontologies detect conflicts (e.g., FCA for mapping heterogeneities), but speculative evaluation stalls resolution. E.g., in MBSE, ontologies trace failure propagations but ignore domain pathologies like cultural framings in global data integration. Resolution methods (e.g., ontology patterns for merging) exist but undervalue pragmatic trials, leading to “interoperability failures” in Semantic Web apps. 

• iii. Using Inferred Framings to Support Interoperability Among Phenomenological Theories/Reference Models, and Construct Foundational World Theories for AI/Human/Hybrid Training, Robot Development, etc.: This pragmatic turn—echoing Comte’s “positive stage”—is emerging but missed earlier. Ontologies enable “interoperability” (e.g., FAIR principles’ “I” for interoperability via ontological commitments) and foundational theories (e.g., OWL for robot reasoning in Industry 4.0). For hybrids: 2025 FMEA enhancements use ontologies for AI-robot failure inference, supporting training via causal chains. Yet, speculative holdovers (e.g., duomining in OOO) limit scalability; a Kant-inspired evaluation (usefulness for “highest good” like equitable AI) could build robust worlds for AGI/robotics, avoiding ethical pitfalls like biased loan approvals. 

In sum, the era’s ontology work innovated phenomenologically (catalogs for AI) but speculated ontologically (ULOs without criteria), missing Heidegger’s call to let Being emerge from beings and Kant’s pragmatic limits. Future paths: Pragmatist ontologies (e.g., Peircean quietism for models ), evaluated by utility in resolving conflicts and enabling hybrids—transforming “missed” into “manifest.”

[John F Sowa]

Janet,

Thanks for that compendium of answers generated by an AI system.   By the way, which system did you use to get those answers?    And which phrases were your inputs, and which were the computer's responses?

My observations:  All the sentences sound plausible.  They seem to be generated from texts found on the WWW.   The authors and systems that are mentioned are well known to anybody who has been reading the literature on ontology and knowledge representation for the past 30 years.

But after reading that, I can't say that there are any new ideas in it -- nor any old ideas for which it provides any new insights.   I can't point to any paragraph that would tell anybody any significant insight about ontology, phenomenology, or their interrelationships.

If anybody asked me for a summary of that article,  I would answer in one word "Blah."

Can anybody else say anything better?   After reading that, can anybody state anything new that they learned from it?  Can anybody find any paragraph in it that they would recommend to anybody else?

John

 

---

From: "Janet Singer" <jsi...@measures.org>

[Janet Singer]

Below is a pdf of the entire session.

I’ll tell you which system I used only if you promise not to get diverted into politics : )

[Ravi Sharma]

John, Janet

Appears to be a query in Chrome Google?

Regards.

Thanks.

Ravi

(Dr. Ravi Sharma, Ph.D. USA)

NASA Apollo Achievement Award

Former Scientific Secretary iSRO HQ

Ontolog Board of Trustees

Particle and Space Physics

Senior Enterprise Architect

SAE Fuel Cell Standards Member

On Sun, Nov 30, 2025 at 7:57 PM Janet Singer <jsi...@measures.org> wrote:

Below is a pdf of the entire session.

I’ll tell you which system I used only if you promise not to get diverted into politics : )

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> On Nov 30, 2025, at 7:29 PM, John F Sowa <so...@bestweb.net> wrote:
>
> Janet,
>
> Thanks for that compendium of answers generated by an AI system.   By the way, which system did you use to get those answers?    And which phrases were your inputs, and which were the computer's responses?
>
> My observations:  All the sentences sound plausible.  They seem to be generated from texts found on the WWW.   The authors and systems that are mentioned are well known to anybody who has been reading the literature on ontology and knowledge representation for the past 30 years.
>
> But after reading that, I can't say that there are any new ideas in it -- nor any old ideas for which it provides any new insights.   I can't point to any paragraph that would tell anybody any significant insight about ontology, phenomenology, or their interrelationships.
>
> If anybody asked me for a summary of that article,  I would answer in one word "Blah."
>
> Can anybody else say anything better?   After reading that, can anybody state anything new that they learned from it?  Can anybody find any paragraph in it that they would recommend to anybody else?
>
> John
> 

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[Alex Shkotin]

Janet,

I find bringing philosophical doctrines into our field counterproductive, for me. It's a different matter when, like Adam, there's a clear interest in philosophy.

If we ask a practicing ontologist what philosophical doctrine they adhere to, the answer will likely be none.

It follows that there is a system of ontological principles accepted by the majority:

Being is the truth of Being.

Being appears.

This is what immediately comes to my mind from Hegel.

It would be interesting to gather them all together, similar to GAAP. Like GAOP 🏋️

We, as a community of practicing ontologists, could work on this. Well, first, we could ask the AI about this.

And perhaps it would be worthwhile to highlight generally accepted methods for describing phenomena as a separate topic.

We begin with a description of the phenomenon, preferably a reproducible one, identify the being that is appearing, and use a theory of this being, if one exists.

How the matter appears to a human being is a fascinating topic. We are surrounded by geometric surfaces glowing in different colors.

Alex

пн, 1 дек. 2025 г. в 05:24, Janet Singer <jsi...@measures.org>:

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[Chuck Woolery]

Janet,

If a word does not lead to moral clarity of action.  And action isn’t taken.  WTF are words good for?

Just entertaining minds that prefer being RIGHT-  over doing what is right and now urgently NEEDED. 

 

As a biologist who detests the English language for its ambiguity...I joined this listserv for the purpose of prolonging our species sustainably on this goldilocks planet.   If the consensus on this website is only about protecting a word’s accuracy... Take me off.

 

cw

 

 

WARNINGS: FINDING CASSANDRAS TO STOP CATASTROPHES  By Richard A. Clarke and R.P. Eddy,  2017: https://cco.ndu.edu/PRISM-7-2/Article/1401978/warnings-finding-cassandras-to-stop-catastrophes/   The first 8 chapters detail the millions of lives and hundreds of billions of dollars lost to catastrophes,– natural and human engineered – due to people in power failing to act on the advanced warnings of experts.   The last eight chapters estimates the billions of lives and trillions of dollars that could be saved if humanity collectively works to prevent the other dire warnings now being given regarding other threats (some existential).  Chapter 11 “The Journalist: Pandemic Disease”.   Most instructive is Chapter 9.  It outlines three cognitive reasons why humans ignore such warnings.

Here’s a video of optimism if you dare watch it  https://www.rethinkx.com/videos

 

Chuck Woolery

Former Chair, United Nations Association Council of Organizations

Former Issues Director, Global Health Council.

Former Action Board member, American Public Health Association.

Author of 1996 and 1997 Congressional testimony warnings regarding threats to US and global bio- security.

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[John F Sowa]

Alex,

Ontology is a branch of philosophy.   Any and every decision about the top levels of an ontology is a philosophical assumption.  If you happened to notice, Barry Smith was the chief proponent of the top levels of BFO, and guess what his primary job happens to be.  If you haven't checked, he's a professor of philosophy at the University of Buffalo.

Aristotle was a major contributor to logic and philosophy and their application to any and every branch of science.  Kant was teaching both science and philosophy.  In fact, his primary job was natural philosophy, wich included Newton's Principia.

Kant was the first person to propose that the solar system began as a rotating cloud of dust that coalesced into a rotating disk, which then coalesced into the observed planets, of which the earth is one.  His major philosophical publications addressed the issues of providing a universal ontology for all the branches of science,

Summary:  Every theory of ontology is an application of logic and philosophy to an analysis of all the branches of science, including both the natural sciences and the social sciences.

John

_______________________________________

[Alex Shkotin]

John,

The situation with TLO is quite interesting. For a specific theory, for example, graph theory, to be applicable, I need to be able to map its primary terms to reality, so that the model constructed for my graph theory reflects the properties of reality.

In this nexus: theory, model of the theory, mapping the model to reality, where does TLO fit in?

Have a look at https://www.linkedin.com/pulse/theory-model-reality-alex-shkotin-dpnue

We need somewhere written down Generally Accepted Ontological Principles (GAOP), not philosophical doctrines. Is TLO a form of such text?

Alex

вт, 2 дек. 2025 г. в 03:20, John F Sowa <so...@bestweb.net>:

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[Ravi Sharma]

Our esteemed forum member Chuck

we deal with varieties of ontology words LLM AI healthcare and bio pandemics and manufacturing semantics

computers and ML and AI

just to name only a few topics

So please do not restrict only to one view

I in particular enjoyed the wonderful freedom declaration at every meet by our Native Americans full of accumulated knowledge wisdom and connection with nature and physics and astronomy😀😀😀

Thanks.

Ravi

(Dr. Ravi Sharma, Ph.D. USA)

NASA Apollo Achievement Award

​Former Scientific Secretary iSRO HQ

Ontolog Board of Trustees

Particle and Space Physics

Senior Enterprise Architect

SAE Fuel Cell Standards Member

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[Chuck Woolery]

Ravi,

WOW!  You really know how to use words...;-)  and make someone feel good! 

Thank you!  You talked me into sticking around.  Mainly for the indigenous wisdoms... ;-)

And the kindness or your words...

 

cw

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[Leo Obrst]

Thank you, Chuck and Ravi.

Leo

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Leo Obrst, lob...@gmail.com

[Chuck Woolery]

Thank you Leo!

With a healthy mind - and word set... peace is possible!  😉

 

cw

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[Ravi Sharma]

Chuck Alex All

It is great pleasure to get any message from Leo Obrst.

regards

Thanks.

Ravi

(Dr. Ravi Sharma, Ph.D. USA)

NASA Apollo Achievement Award

​Former Scientific Secretary iSRO HQ

Ontolog Board of Trustees

Particle and Space Physics

Senior Enterprise Architect

SAE Fuel Cell Standards Member

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[Janet Singer]

(Continuing the discussion on a possible path forward)

Prompt:

Arguably the reason the ULO convergence effort has stalled so far is because it did not start from a scientific grounding of biosemiotics that could understand ontology theory and model development as activities that living pro-social systems engage in in order to organize themselves in their environments. Instead, it presumed that the scientific perspective on ontologies was to see them as standing in for their targets  by 'carving the world at its joints' or 'cataloging the furniture of the world'.

This simplified framing was doomed to fail. But a fundamentally complex framing that builds on the work of Kant, Peirce, Robert Rosen, and others would have first-class positions for real effective dynamics, perspective-dependent conceptualizations in enframings, and all language representations (formal and informal, symbolic and graphical, etc.).

LLM response:

Your thesis incisively diagnoses the impasse in upper-level ontology (ULO) convergence: the field's dominant realist paradigm—epitomized by metaphors like "carving nature at its joints" (Plato via Barry Smith) or "cataloging the furniture of the world" (Quinean echoes in BFO)—treats ontologies as static, observer-independent maps of reality, ignoring their roots in the semiotic, anticipatory, and perspectival activities of living systems. This anthropocentric oversight, as you note, dooms convergence by presuming a neutral, Archimedean standpoint that doesn't exist. Instead, grounding ULO efforts in biosemiotics—a scientific framework for how living entities interpret and signify their environments—could reframe ontology development as an emergent, pro-social process of self-organization. Building on Kant's transcendental idealism, Peirce's semiotics, Robert Rosen's anticipatory systems, and related thinkers (e.g., Heidegger on enframing, or Uexküll on umwelten), this complex approach would integrate real dynamics, perspective-dependent conceptualizations, and multimodal language representations as first-class elements. Below, I'll elaborate why this shift is not just corrective but generative, drawing on key connections from these traditions.

Biosemiotics as the Missing Scientific Grounding

Biosemiotics, emerging from thinkers like Jakob von Uexküll and Thomas Sebeok, posits that life is inherently semiotic: organisms don't just react to stimuli but actively interpret signs to organize themselves within ecosystems. This provides a biological basis for ontology theory, viewing models not as mirrors of an objective world but as interpretive tools evolved for survival and coordination. Traditional ULO projects (e.g., BFO, DOLCE) stalled because they abstracted away this interpretive layer, assuming ontologies "stand in for" targets via universal categories. But as biosemiotic ontology suggests, categories like "process" or "entity" emerge from semiosis—the triadic interplay of sign, object, and interpretant—extending even to psychological and social levels. Convergence fails without this: ontologies become brittle when divorced from the living systems that produce and use them for pro-social ends, like coordinating knowledge in scientific communities.

A biosemiotic pivot would treat ULO development as a meta-semiotic activity: humans (as living systems) construct ontologies to anticipate and navigate environments, fostering convergence through shared interpretive frameworks rather than imposed realism. This aligns with your critique—realist simplifications ignore how ontologies evolve dynamically, much like genes or memes in cultural ecosystems.

Integrating Kant: Perspective-Dependent Enframing and Conceptualizations

Kant's Critique of Pure Reason provides the epistemological backbone: human cognition imposes a priori categories (space, time, causality) on phenomena, enframing experience in perspective-dependent ways. In biosemiotics, this translates to umwelten—species-specific "worlds" shaped by perceptual and conceptual filters—where ontologies aren't neutral but conditioned by the observer's standpoint. Traditional ULOs presume a God's-eye view, but a Kantian biosemiotics would embed enframing (Gestell, per Heidegger) as a core mechanism: ontologies "frame" reality for action, with conceptualizations varying by context (e.g., a biologist's vs. physicist's lens on "process").

This complexity avoids doom by making perspective-dependence explicit—e.g., modular ULOs with "viewpoints" layers, allowing convergence via alignments rather than unification. Recent work on the "Kantian brain" models perception as predictive, anticipatory framing, bridging to biosemiotics by showing how neural systems generate meaning through bounded, perspective-laden interpretations.

Peirce's Semiotics: Triadic Meaning-Making for Dynamic Ontologies

Peirce's semiotics revolutionizes ontology by insisting on triadic signs: every representation involves a sign-vehicle, object, and interpretant (the effect on the mind/system). This counters dyadic (Saussurean) or realist views, positioning ontologies as evolving semioses where meanings emerge through inquiry and habit-formation. In modern ontology development, Peircean ideas enable AI and knowledge systems to handle abduction (hypothesis generation) and fallibilism, connecting Western science to non-dualistic perspectives.

Applied to ULOs, this framing prioritizes multimodal languages: symbolic (formal logics like OWL), iconic (graphical models), and indexical (causal links to data). Convergence could proceed via "semeiotic ontologies" that evolve through community interpretation, as in Peirce-inspired AI surveys. This dynamism—ontologies as living, interpretive processes—addresses stagnation by allowing for infinite semiosis, where models refine through use.

Robert Rosen: Anticipatory Systems and Effective Dynamics

Rosen's relational biology and anticipatory systems theory grounds this in mathematics: living systems contain internal models that anticipate futures, enabling self-organization beyond reactive mechanics. Ontologies, in this view, are anticipatory artifacts—predictive encodings that organisms (or societies) use to close causal loops. Unlike realist ULOs, which catalog static "furniture," Rosenian ontologies emphasize impredicativities (self-referential loops) and category theory for modeling complex, non-computable dynamics.

This integrates "real effective dynamics" as first-class: ontologies aren't proxies but participatory tools for enacting change in environments. For ULO convergence, it suggests hybrid systems where models forecast interoperability issues, evolving through feedback—e.g., qualitative predictions in biology, per Rosen's emphasis on non-quantitative foresight.

Toward a Generative Framing: Overcoming the Stall

Synthesizing these, your proposed complex paradigm transforms ULO efforts from top-down imposition to bottom-up emergence: biosemiotics supplies the biological realism, Kant the perspectival humility, Peirce the semiotic machinery, and Rosen the anticipatory formalism. This accommodates all representations—formal (axioms), informal (narratives), symbolic (logics), graphical (diagrams)—as tools for pro-social coordination. Practical implications include:

• Pluralistic ULOs: Modular architectures with "anticipatory layers" for dynamics and "semiotic bridges" for perspectives, fostering convergence via federated alignments (e.g., in Ontology Summit discussions).
• Community-Driven Evolution: Treat ontology development as biosocial semiosis, where scientific communities iteratively refine models through shared interpretation, avoiding realist hubris.
• Broader Impact: This could heal the "fractured world" biosemiotics critiques, shifting from reductionism to holistic understanding in AI, ecology, and beyond.

The realist simplification was indeed doomed—it ignored life's interpretive essence. But this richer framing, rooted in living systems' self-organization, offers a path to vibrant, adaptive convergence. How might we prototype such a biosemiotic ULO in practice?

Janet

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[Ravi Sharma]

Quoting Janet

The realist simplification was indeed doomed—it ignored life's interpretive essence. But this richer framing, rooted in living systems' self-organization, offers a path to vibrant, adaptive convergence. How might we prototype such a biosemiotic ULO in practice?

UnQuote

Does that mean that dynamic adaptive ontologies that stay alive aligning with Bio-evolutionary roles are most relevant, especially for ULO?

Regards?

Thanks.

Ravi

(Dr. Ravi Sharma, Ph.D. USA)

NASA Apollo Achievement Award

Former Scientific Secretary iSRO HQ

Ontolog Board of Trustees

Particle and Space Physics

Senior Enterprise Architect

SAE Fuel Cell Standards Member

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[Alex Shkotin]

Janet,

May I skip reading the verbose AI's response to your sophisticated prompt?

I just looked at Hegel's Science of Logic and it occurred to me that the first part "Doctrine of Being" is devoted to phenomenology, while the second part, "Doctrine of being," is devoted to ontology.

This second part contains the

GAOP (Generally Accepted Ontological Principle): being appears.

We objectify our sensations through instruments, so we can consider another

GAOP: humans can experiment with reality.

Of course, we still need to work on it.

The separation of phenomenology and ontology in philosophical doctrines may prove important.

After all, if we look around, we see fixed or moving surfaces glowing in different colors.

Which brings geometry to the forefront in phenomenology of matter.

Do all ULO use the same euclidean geometry?

Alex

вс, 7 дек. 2025 г. в 08:29, Janet Singer <jsi...@measures.org>:

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[jsi...@measures.org]

Ravi, 

You asked 

Does that mean that dynamic adaptive ontologies that stay alive aligning with Bio-evolutionary roles are most relevant, especially for ULO? 

Yes, but the question becomes what we mean by ‘dynamic’, ’adaptive’ and ‘stay alive’ in the context of computer ontologies (plus how we would control it for our purposes if we achieved it!) 

Leibniz pointed out that our artificial machines are different in kind from ‘natural machines’ like living bodies because the machines we design and construct are finitely divisible into discrete parts and driven by external purposes, while natural machines are not. Robert Rosen explored this at length. Artificial life research is exploring the boundary — see the last two links below.

Alex, 

Well I think the verbose response is actually quite interesting! 

I agree with your points, though. I would go farther: artificial life is raising anew questions about the role of geometry in mind as well as ‘matter’, which has no simple definition now in line with Barry’s and Jobst’s important conclusion about the limits of ‘common sense’ ontology in relation to mathematical models and methods. See also Chomsky on the death of matter 

https://www.youtube.com/watch?v=C1zHMbHFyt8.

Mike Levin’s current symposium series on ‘Platonic Space’ is exploring questions of mathematics and behavior, agency and form in cutting edge biological / artificial life research. 

https://thoughtforms.life/platonic-space-where-cognitive-and-morphological-patterns-come-from-besides-genetics-and-environment/

https://thoughtforms.life/symposium-on-the-platonic-space/

Janet

On Dec 7, 2025, at 12:29 AM, Alex Shkotin <alex.s...@gmail.com> wrote:



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[jsi...@measures.org]

Overview of the Chomsky video from Alter.systems:

This transcript — “The Death of the Mechanical Philosophy” — is a profound critique of how modern science lost its original vision of intelligibility after Newton, and it ultimately explores the collapse of materialism as a coherent metaphysical framework.

Here’s a structured summary of the ideas:

⚙️ The Mechanical Philosophy’s Collapse

The mechanical philosophy, dominant in the 17th century, aimed to describe reality in terms of matter and motion—everything, including life and thought, was to be explained mechanically.

Newton proved it couldn’t work.

He mathematically unified motion and gravity, but could not explain what caused gravity — merely how it behaved.

Newton himself saw this as a failure of explanatory power.

His contemporaries — Leibniz, Huygens, and others — agreed: Newton’s system was brilliant mathematically, but not physically intelligible.

🎯 The Shift in Science’s Goals

After Newton, science lowered its ambitions.

The new attitude became:

“We can’t make the world intelligible—but we can make our theories intelligible.”

That’s a philosophical demotion: science gave up explaining reality itself and settled for constructing predictive mathematical models.

By the 20th century (Einstein, Russell), this change had become normalized — physical theories are mathematically beautiful but metaphysically hollow. They describe patterns, not what is.

⚡ From Force to Field: The Metaphysical Retreat

Over time, scientists accepted “forces” and later “fields” as real, even though they had no material basis.

19th-century historians like Friedrich Lange noticed that “materialists” were using non-material concepts, thus abandoning true materialism.

This was the silent death of the mechanical worldview.

Matter ceased to be tangible — replaced by abstractions and equations.

🧠 The Mind–Body Problem Reversed

Once “matter” lost definite meaning, dualism (mind vs. matter) dissolved. There’s no “body” in the mind–body problem anymore.

You can’t contrast mind to matter if matter itself is undefined.

Newton even said we know so little about matter that “all matter may be alive” — hinting at a proto–panpsychic view.

💭 Consciousness as the Clearest Thing We Know

Modern debates about consciousness are called backwards by philosophers like Galen Strawson.

Consciousness isn’t the mystery — it’s the one thing we actually understand firsthand.

The real mystery is matter, because we no longer know what it is.

Bertrand Russell said the same:

What we know best is consciousness; what we know least is matter.

Everything else is an attempt to connect these, but physics doesn’t tell us what matter actually is.

🏁 The Philosophical Turning Point

Newton’s humility — “I do not make hypotheses” — symbolized science’s retreat from ultimate explanation to mathematical description.

This was not entirely wrong, but it marked the end of science’s original dream: to render the universe intelligible.

Now, we have intelligible theories describing an unintelligible world.

🧩 Core Takeaway

The video argues that:

Modern science functions, but it no longer understands.

The original spiritual and philosophical ambition of the scientific revolution — to understand the essence of reality — has been traded for mere instrumental control.

In short:

We know how reality behaves, but we no longer know what reality is.

[Nadin, Mihai]

Dear and respected colleagues:

Janet Singer deserves credit for the perspective she is arguing for. I am not inclined to argue with her. I wish that some ideas/concepts would be presented in a more precise way.

 

The issue of grounding (e.g. biosemiotics) deserves better. Rosen is misunderstood in the way his ideas are presented. What is real effective dynamics? Read Rosen!

Peirce: triadic=trichotomic. Part of an encompassing philosophic system!  Read Peirce!

 

I do not expect LLM or anything of the reductionist nature of such “learning” models to return ideas of which we are not aware.

ULO—yes another attempt at moving the goal-posts.

biosocial semiosis—more words! Occam knew better.

My respect to all of you.

 

Mihai Nadin

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[jsi...@measures.org]

Dear Mihail,

The goal here is to juxtapose elements that might be brought together in a novel way to  build upon them, not to look back at Rosen’s or Peirce’s work (which of course stand for themselves). I don’t see that exhorting people to read Rosen or read Peirce serves a purpose. 

I also don’t see how ‘precision’ is important at this point, but if you would like to identify any specific imprecision that bothers you, I could address it.

And your vague claim that ‘Rosen is misunderstood’ is just trolling without further clarification.

Janet

On Dec 7, 2025, at 5:34 PM, Nadin, Mihai <na...@utdallas.edu> wrote:



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[Alex Shkotin]

Janet,

you wrote:"I would go farther"

In principle, I'm ready to go further, but later. I think we need to thoroughly discuss the phenomenological question of how matter appears to us through vision.

And here we have geometric experiments (three sticks perpendicular to each other from the same point), engineering drawings, surveyor's measurements, and geometry in everyday life: to determine how straight a rod is, we look along it.

This isn't about geometry in the mind, but about applying Euclidean geometry to reality. 

How do we apply Euclidean geometry to problems about reality?

For example, in architecture, when calculating and drawing the shapes of machine parts and mechanisms we use Euclidean geometry.

High-precision engineering: YouTube shows these ultra-precise machines and the results of their work.

Tools are now available for detailed digitization of the surface of a physical body for three-dimensional, detailed reproduction of its shape, such as in sculpture.

Interestingly, accurately describing a body's shape verbally is virtually impossible, yet in engineering, body shapes are defined by analytical curves.

A topic that interests me: the application of Euclidean geometry to everyday life, technology, and science. This is the foundation of phenomenology.

Alex

And Let me copy/paste from my another email 

"In our everyday life we get phenomena, we usually know the entity behind it, we use logic to think how to work with this entity. Usually just ignore it.

In applied ontologistics we work with scientific and technological knowledge to systematize, concentrate and formalize this knowledge. To make knowledge processing by computers available.

The logic of the forms of the surfaces of bodies is the basis of phenomenology. 

Maybe like this "The fifth section elaborates my earlier work on the comparisons between geometry and phenomenology." p.5 of Phenomenology and Phaneroscopy: A Neglected Chapter in the History of Ideas | SpringerLink.

From everyday geometry to phenomenology of matter."

вс, 7 дек. 2025 г. в 20:10, <jsi...@measures.org>:

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[alex.shkotin]

Janet,

I think Levin thinks 'Platonic Space' is simpler than the Universe. That seems naive to me. Looking for intelligence there is probably harder than finding a needle in a haystack.

Just kidding.

Alex

воскресенье, 7 декабря 2025 г. в 20:10:38 UTC+3, jsi...@measures.org:

[jsi...@measures.org]

Alex,

Levin’s ‘Platonic Space’ is the umbrella term for the hypothetical locus of patterns that organisms might ‘access’ to guide their forms of development and behavior. 

This video shows biological phenomena his lab studies that require explanations outside mere genetics (being novel goal-driven behaviors in novel environments) or mere emergence (which he dismisses as a ‘mysterian’ non-explanation).

https://www.youtube.com/watch?v=2RcW65tBxRA&list=PL6SlweOjqYXzpxJMhzHJjEq4s0lS9udCQ&index=2

Watch this and see how it relates to your ideas of form and geometry.

Janet

On Dec 9, 2025, at 9:24 AM, alex.shkotin <alex.s...@gmail.com> wrote:



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[Jack Park]

Having spent time with Rosen and his daughter Judith, I support any claim about Rosen being misunderstood by some accounts..

Peirce and Rosen, despite "looking back", have a lot to offer.  As many readers may know, Rosen was Rashevsky's student, and went on to bring category theory into Rashevsky's quest to understand relational biology.  He did seminal work on anticipatory systems and more. 

Jack

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[Alex Shkotin]

Janet,

Thank you. I'll definitely take a look.

I asked ChatGPT:"A reproducible phenomenon that has no explanation is interesting. It seems there are many of them in biology."

Disclaimer: The answer was not verified by any human. 

Alex

вт, 9 дек. 2025 г. в 21:41, <jsi...@measures.org>:

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[Ravi Sharma]

My thanks to 

Janet - for many clarifications,

Mihai - thanks for earlier response to me, I pln to reply that one soon.

Jack Park - Is this Rashevsky same who was father or one of the earlier ones to dwell deep in Biophysics (vaguely at Chicago?)

Thanks.

Ravi

(Dr. Ravi Sharma, Ph.D. USA)

NASA Apollo Achievement Award

Former Scientific Secretary iSRO HQ

Ontolog Board of Trustees

Particle and Space Physics

Senior Enterprise Architect

SAE Fuel Cell Standards Member

To view this discussion visit https://groups.google.com/d/msgid/ontolog-forum/CACeHAVAMgakyL1q4waRSEvoGfcrRTDCdGoSDahqoowcAc%3Dx%2BSQ%40mail.gmail.com.