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Session Synthesis
Duration 1 hour
Date/Time 26 May 2021 16:00 GMT
9:00am PDT/12:00pm EDT
5:00pm BST/6:00pm CEST
Convener KenBaclawski
Track Synthesis

Contents

Ontologies are a rich and versatile construct. They can be extracted, learned, modularized, interrelated, transformed, analyzed, and harmonized as well as developed in a formal process. This summit will explore the many kinds of ontologies and how they can be manipulated. The goal is to acquaint both current and potential users of ontologies with the possibilities for how ontologies could be used for solving problems.     (2A)

Agenda     (2B)

Conference Call Information     (2C)

Attendees     (2D)

Discussion     (2E)

Introduction     (2E1)

[12:11] RaviSharma: I think instead of word role may be what Andrea said is aspect!     (2E1A)

[12:13] Andrea Westerinen: On the first slide, maybe instead of types use "development, types and roles/uses"     (2E1B)

Ontological Landscape     (2E2)

[12:14] Andrea Westerinen: There is more than one kind/type of ontology and many ways to develop them     (2E2A)

[12:14] Mike Bennett: There is historically a perception that some practitioners think that the type of thing they call an ontology is the only kind of thing there is that is an ontology. We want to counter that perception .     (2E2B)

[12:15] Andrea Westerinen: @mike +1     (2E2C)

[12:15] Gary Berg-Cross: when we look out at the ontological landscape among the things we see is the ontology lifecycle.     (2E2D)

[12:15] RaviSharma: the stage or source is implied instead of role in second bullet of second slide and is related to one categorization of source of process.     (2E2E)

[12:17] Andrea Westerinen: Ontology is used for communication ... can be expressed in different "languages"     (2E2F)

[12:17] janet singer: I agree w/ Andrea. Then the various aspects all get into lead sentence.     (2E2G)

[12:17] RaviSharma: Ontologies imply entities and relations and therefore these are constructed similar to LANGUAGES!     (2E2H)

[12:17] RaviSharma: used for Communication purpose as Gary said.     (2E2I)

[12:21] RaviSharma: Mike said about Chris Partridge's statement about ontological commitment!     (2E2J)

[12:21] Mike Bennett: Note to reference the Partridge et al paper on various dimensions of ontological commitment.     (2E2K)

[12:22] Mike Bennett: Ontological commitment includes things like e.g. Realism v Conceptualism. Also 4D/3D etc.     (2E2L)

[12:24] Mike Bennett: Those are just 2 of many dimensions of OC.     (2E2M)

[12:34] ToddSchneider: Here's a reference to ontological commitment, http://web.mit.edu/arayo/www/ontcom.pdf     (2E2N)

[12:52] Mike Bennett: Is this a salience on the landscape?     (2E2O)

[12:55] Mike Bennett: Meaning is not truth     (2E2P)

[13:06] RaviSharma: Landscape vs ecosystems these words have different contexts and also differ in symbiosis.     (2E2Q)

Uncertainty     (2E3)

[12:56] Andrea Westerinen: Here is a definition from Wikipedia ... Fuzzy logic and probability address different forms of uncertainty. While both fuzzy logic and probability theory can represent degrees of certain kinds of subjective belief, fuzzy set theory uses the concept of fuzzy set membership, i.e., how much an observation is within a vaguely defined set, and probability theory uses the concept of subjective probability, i.e., frequency of occurrence or likelihood of some event or condition[clarification needed]. The concept of fuzzy sets was developed in the mid-twentieth century at Berkeley [21] as a response to the lacking of probability theory for jointly modelling uncertainty and vagueness.[22]     (2E3A)

Bart Kosko claims in Fuzziness vs. Probability[23] that probability theory is a subtheory of fuzzy logic, as questions of degrees of belief in mutually-exclusive set membership in probability theory can be represented as certain cases of non-mutually-exclusive graded membership in fuzzy theory. In that context, he also derives Bayes' theorem from the concept of fuzzy subsethood. Lotfi A. Zadeh argues that fuzzy logic is different in character from probability, and is not a replacement for it. He fuzzified probability to fuzzy probability and also generalized it to possibility theory.     (2E3B)

[12:57] Gary Berg-Cross: Ref - "In 2005, Probabilistic Web Ontology Language (PR-OWL) (Costa P. C., 2005) was formulated to address OWLs lack of support for uncertainty, an ubiquitous factor in complex real-world problems. Costa (2005) also introduced the concept of probabilistic ontology, which allows representation of uncertainty in all elements comprising classic ontologies, and proposed PR-OWL as a language for specifying probabilistic ontologies."     (2E3C)

[12:58] Gary Berg-Cross: Matsumoto, Shou. PR-OWL decision: A framework for decision making with probabilistic ontologies. Diss. George Mason University, 2019.     (2E3D)

Definitions     (2E4)

[12:18] Andrea Westerinen: Are ontologies similar to linguistic concepts?     (2E4A)

[12:25] janet singer: Saying ontologies are specialized languages would open up both how they are similar to and different from other kinds of languages     (2E4B)

[12:27] janet singer: i agree with Todd that standardizing interpretation (or way terms are taken) is more concrete and operationalizable than standardizing meaning     (2E4C)

[12:28] RaviSharma: network needs to be defined     (2E4D)

[12:29] RaviSharma: domains come from different context and even concepts like background     (2E4E)

[12:31] RaviSharma: Gary described network glossaries and harmonization from his presentation     (2E4F)

[12:35] RaviSharma: probably we mean different word combinations or different words meaning the same semantic meaning?     (2E4G)

[12:36] Andrea Westerinen: You might really care about penguins if your ontology is about the Birds of Antarctica.     (2E4H)

[12:37] Andrea Westerinen: We are arguing about typical vs atypical examples.     (2E4I)

[12:38] RaviSharma: What I read in third bullet is related to accuracy and fuzziness of meaning or definition implying range and therefore spectrum of accuracy or extent of understanding.     (2E4J)

[12:42] RaviSharma: One more thought comes to mind is that we should convey range of applicability of ontology - meaning that accuracy of meaning can change if we broaden the scope and extent of validity of ontology     (2E4K)

[12:46] RaviSharma: I have also been emphasizing over years that Probabilistic works need attention like Kathy Lasky GMU and other related works which are being referenced here in neurosymbolic topic.     (2E4L)

[12:48] Mike Bennett: What was the question?     (2E4M)

[12:51] Mike Bennett: There is probabilistic v symbolic AI but that's not the same as probabilistic ontologies.     (2E4N)

[12:52] RaviSharma: Andrea made a good point     (2E4O)

Sustainability     (2E5)

[13:04] RaviSharma: Ken Sustainability should also include standards and infrastructure required for sustenance.     (2E5A)

[13:07] RaviSharma: Maintenance of every repository is fraught with problems in spite of NARA etc we can not sustain information and formats.     (2E5B)

Miscellaneous     (2E6)

[12:53] RaviSharma: Are we representing only what speakers said or are also including audience participation and inputs?     (2E6A)

[13:00] RaviSharma: Gary made synthesis comment     (2E6B)

[13:02] RaviSharma: Ken you did a wonderful start of synthesis and thanks to participants for injecting our views and balancing what the speakers said.     (2E6C)

[13:02] RaviSharma: Gary said KGs are relevant to this synthesis     (2E6D)

[13:08] RaviSharma: good outline of communique what is timeline     (2E6E)

[13:08] RaviSharma: when is next meeting?     (2E6F)

[13:10] RaviSharma: Track chairs will provide inputs     (2E6G)

[13:10] RaviSharma: thanks     (2E6H)

Resources     (2F)

Previous Meetings     (2G)


Next Meetings     (2H)