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Session Planning
Duration 1 hour
Date/Time September 26 2018 16:00 GMT
9:00am PDT/12:00pm EDT
5:00pm BST/6:00pm CST
Convener KenBaclawski


Agenda     (2A)

Conference Call Information     (2B)

Attendees     (2C)

Proceedings     (2D)

[11:42] Ken Baclawski: Agenda Discussion of Summit topics Industrial Ontology Foundry (IOF) and Semantic Technologies for Systems Engineering (ST4SE) Social Constructs Open Knowledge Network Processes Bad Ontologies Ontology of Ontologies (but no labels should be accepted as significant if they cant be operationalized and tied to effective distinctions) Mathematics and Statistics     (2D1)

[12:17] Ken Baclawski: Ram suggested also considering Explainable AI as a topic.     (2D2)

[12:18] Ram D. Sriram: Explainable AI & Common Sense Reasoning are two potential topics     (2D3)

[12:18] Ram D. Sriram: Open Knowledge Network is needed for Common Sense Reasoning. So it will be a part of it.     (2D4)

[12:21] Gary Berg-Cross: Are we talking about these "topics" as alternate ones from which we pick one, or as part of the same Summit "topic"?     (2D5)

[12:21] ToddSchneider: Not sure. There is overlap.     (2D6)

[12:22] Ken Baclawski: @Gary: These would be alternatives. It would be too much to try doing them all.     (2D7)

[12:22] Gary Berg-Cross: John try     (2D8)

[12:22] ToddSchneider: John, the meeting URL is You'll have to download their app.     (2D9)

[12:25] Gary Berg-Cross: There are relevant talks we might consider leveraging from at this year's FOIS: For example,     (2D10)

Some Open Issues After Twenty Years of Formal Ontology Authors Stefano Borgo, Pascal Hitzler Pages 1 - 9 DOI10.3233/978-1-61499-910-2-1     (2D11)

Ontologies for Artificial Minds Authors Alessandro Oltramari Pages 13 - 13 DOI10.3233/978-1-61499-910-2-13     (2D12)

Abstract:     (2D13)

Ontologists build formal models to understand the structure of reality. The fun starts and I had a lot of it back in the PhD days (!) when Formal Ontology is applied to understand the structure of what we indisputably use to understand reality itself: the mind. Philosophers have spent lifetimes hovering over this conundrum but I stopped ....     (2D14)

[12:32] RaviSharma: My suggestion is that we include a track on Uncertainty ontologies     (2D16)

[12:34] RaviSharma: and another on affinity among things or entities     (2D17)

[12:35] RaviSharma: both have statistics and refinement of relationships or predicates analysis     (2D18)

[12:36] RaviSharma: processes are good topic     (2D19)

[12:38] RaviSharma: for example how BPMN depictions in processes and ontology have synergy?     (2D20)

[12:40] ToddSchneider: Ontology Summit 2007 - Ontology, Taxonomy, Folksonomy: Understanding the Distinctions     (2D22)

[12:40] John Sowa: See my web page on "processes and causality" :     (2D24)

[12:41] John Sowa: For a shorter summary, see     (2D25)

[12:42] RaviSharma: A First Course in Rational Continuum Mechanics 1st Edition General Concepts Authors: C. Truesdell Editors: Samuel Eilenberg Hyman Bass eBook ISBN: 9781483220482     (2D26)

[12:43] RaviSharma: this is from Alex Shkotin     (2D27)

[12:44] RaviSharma: this includes everything     (2D28)

[12:44] Gary Berg-Cross: Ontology Summit 2016 Communique: Ontologies within semantic interoperability ecosystems     (2D29)

[12:46] AlexShkotin: @Ravi there is a Content there for ex. "12. Axioms of Mechanics     (2D30)

13. The Axioms of Inertia."     (2D31)

[12:46] RaviSharma: I like current topics suggested by Ram     (2D32)

[12:47] RaviSharma: AI - differentiation     (2D33)

[12:48] RaviSharma: explainable AI     (2D34)

[12:50] Gary Berg-Cross1: "New machine-learning systems will have the ability to explain their rationale, characterize their strengths and weaknesses, and convey an understanding of how they will behave in the future. The strategy for achieving that goal is to develop new or modified machine-learning techniques that will produce more explainable models. These models will be combined with state-of-the-art human-computer interface techniques capable of translating models into understandable and useful explanation dialogues for the end user (Figure 2). Our strategy is to pursue a variety of techniques in order to generate a portfolio of methods that will provide future developers with a range of design options covering the performance-versus-explainability trade space..."     (2D37)

[12:51] Gary Berg-Cross1: "XAI is one of a handful of current DARPA programs expected to enable third-wave AI systems, where machines understand the context and environment in which they operate, and over time build underlying explanatory models that allow them to characterize real world phenomena.     (2D38)

The XAI program is focused on the development of multiple systems by addressing challenge problems in two areas: (1) machine learning problems to classify events of interest in heterogeneous, multimedia data; and (2) machine learning problems to construct decision policies for an autonomous system to perform a variety of simulated missions. These two challenge problem areas were chosen to represent the intersection of two important machine learning approaches (classification and reinforcement learning) and two important operational problem areas for the DoD (intelligence analysis and autonomous systems).     (2D39)

In addition, researchers are examining the psychology of explanation..."     (2D40)

[12:55] EvanWallace: I have to drop off soon. I'm supportive of the other topics. Note - I also would want to make sure that we get buy in from the IOF and ST4SE communities before committing to *that* topic.     (2D43)

[12:57] RaviSharma: I would support explainable AI it has close synergy for Machine learning and deep learning     (2D44)

[12:59] Gary Berg-Cross1: Perhaps "Explanation" is the topic.     (2D45)

[12:59] Andrea Westerinen: Sorry, but I have to go ... have a 1pm call.     (2D46)

[12:59] EvanWallace: Got to go.     (2D47)

[13:01] ToddSchneider: So 'Explainable' is the subject?     (2D49)

[13:01] Ram D. Sriram: @Gary: How about Machine Reasoning Explanation     (2D50)

[13:02] RaviSharma: the link of scholar search has some good topics on XAI and ontology     (2D51)

[13:08] RaviSharma: Todd I agree     (2D52)

[13:09] ToddSchneider: 'Explanations' sounds like a good title.     (2D53)

[13:11] RaviSharma: Alex has a point in URL of Elsevier many topics of Universe including Physics and math are included but it is not clear why Mechanics word is prominent?     (2D54)

[13:12] RaviSharma: thanks and Bye it is nearly 11PM in India.     (2D55)

Resources     (2E)

Previous Meetings     (2F)

Next Meetings     (2G)

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