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* [[TomTinsley|Tom Tinsley]]
 
* [[TomTinsley|Tom Tinsley]]
  
== Proceedings ==
+
== Discussion ==
 +
[12:12] Ravi Sharma: Chaitanya - How do you set goals and metrics for measuring successful accelerator program and future directions?
 +
 
 +
[12:17] Ravi Sharma: Chaitanya (CB) - how can you interoperate heterogeneous data products?
 +
 
 +
[12:27] ToddSchneider: Is the NSF working with EU agencies or organizations on any of these topics?
 +
 
 +
[12:27] Ravi Sharma: CB - you say Supporting access by and contributions to the KG by heterogeneous
 +
communities of users but what is Definition of KG?
 +
 
 +
[12:28] Ravi Sharma: what is the common theme on KG by heterogeneous communities?
 +
 
 +
[12:34] Mark Underwood @knowlengr: re "Users" A challenge is developing models for learners / users ... E.g., in autonomous vehicles the model for drivers, repair, distributors, dealers, teachers are quite different. And within development environments (think VW Dieselgate scenario) modeling enterprise roles is nontrivial.
 +
 
 +
[12:41] David Eddy: Is there any attention directed at "un-natural language?"
 +
 
 +
[12:41] Mike Bennett: Is there potential for development of new reference ontology/ies in finance (A7153) and can new participants get involved in the upcoming phases?
 +
 
 +
[12:43] Mike Bennett: Has OKN marked out a formal distinction between reference ontology (conceptual, real world truth makers etc.) versus application ontologies in Semantic Web and elsewhere (specific do data, driven by application use case). These need to be different but not all see that.
 +
 
 +
[12:43] ToddSchneider: Yes, ambiguity can be useful.
 +
 
 +
[12:44] janet singer: Ambiguity as a feature not a bug
 +
 
 +
[12:44] Gary: At what point will the knowledge networks become accessible to other researchers and the public?  Will all phase 1 networks be accessible?
 +
 
 +
[12:45] Mark Underwood @knowlengr: @janet <g> A NewYorker cartoon caption
 +
 
 +
[12:46] Gary: Q asked "what metrics can be used?"
 +
 
 +
[12:47] BobbinTeegarden: @MikeB do you really make a distinction between what you think you see and what you see (conceptual vs 'real')? Perception is a tricky thing ...
 +
 
 +
[12:48] Mike Bennett: @Bobbin that's the Kantian thing. I'm making a distinction between that and ontologies that are specifically about computational data.
 +
 
 +
[12:50] Ravi Sharma: Janet and Todd - statisticians call it measure of uncertainties!
 +
 
 +
[12:53] Ravi Sharma: CB - will NSF CA OKN help us converge on What might be called Common KGs?
 +
 
 +
[12:55] Mark Underwood @knowlengr: Yes! "Your best friend is your use case." (Not a "definition" !)
 +
 
 +
[12:57] Ravi Sharma: CB said use-cases have more relevance to demonstrate some apps and users
 +
 
 +
[12:58] Mark Underwood @knowlengr: Use cases harken strongly back to our 2019 Ontolog theme
 +
 
 +
[12:59] Mike Bennett: Use cases can if misapplied drive you into silo-ized sets of application ontologies. Unless the use case is framed as 'need for a common language'. Otherwise someone ends up applying the rules for use cases of the sort used to drive individual computational solutions, which rules out ontologies as common business language.
 +
 
 +
[13:00] janet singer: CB distinguished knowledge networks from knowledge graphs with the latter being CS/technical. One sense of KN was simply connected human experts
 +
 
 +
[13:01] Mark Underwood @knowlengr: @Mike - what TC68 initiatives are you following (or should I follow) for standards related progress?
 +
 
 +
[13:01] Mike Bennett: @Mark SC4 WG1 Semantics for ISO 20022
 +
 
 +
[13:01] David Eddy: @MikeB... isn't "common language" back to Genesis 11: 1 - 9?
 +
 
 +
[13:02] Ravi Sharma: CB - dataset interoperability implies common metadata?
 +
 
 +
[13:02] Janette Wong: How do we (those who don't participate in the projects) keep ourselves informed of the projects' outcomes?  e.g. A7908 (Spatial Decision Support)
 +
 
 +
[13:02] Mark Underwood @knowlengr: @Mike, got it thx
 +
 
 +
[13:02] Ravi Sharma: FARE data
 +
 
 +
[13:03] Ravi Sharma: Gary - openness?
 +
 
 +
[13:03] Mike Bennett: FAIR: Findable, accessible interoperable reusable data
 +
 
 +
[13:03] Mark Underwood @knowlengr: FAIR
 +
 
 +
[13:04] Mike Bennett: @David, a good example of a construction project that went wrong when there were contractors from too many different jurisdictions and no common standards. (without looking it up I am assuming this Gen 11 is the Tower of Babel)
 +
 
 +
[13:05] Ravi Sharma: data are to be free of personal info.
 +
 
 +
[13:05] Ravi Sharma: provenance
 +
 
 +
[13:06] Ravi Sharma: Janet - great question
 +
 
 +
[13:07] Mark Underwood @knowlengr: Which Apache project?
 +
 
 +
[13:08] Sean Gordon: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn
 +
 
 +
[13:08] Gary: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn
 +
 
 +
[13:08] Ravi Sharma: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn
 +
 
 +
[13:08] Mark Underwood @knowlengr: @Janette thx
 +
 
 +
[13:09] ToddSchneider: Meeting ends @13:09 EST
 +
 
 +
[13:09] janet singer: CB: KN #1 as connected human experts; KN #2 as connected data, entities, relationships; KN #3 as technological infrastructure that enables the knowledge graphs
 +
 
 +
[13:10] Mark Underwood @knowlengr: @MikeB RE use cases can be abused, but to guide SDO work they are vastly superior endless wrangling over definitions... Even "ontology" brings the philosophers out of the woodwork
  
 
== Resources ==
 
== Resources ==

Revision as of 23:29, 10 February 2020

[ ]
    (1)
Session Chaitanya Baru
Duration 1 hour
Date/Time 05 February 2020 17:00 GMT
9:00am PST/12:00pm EST
5:00pm GMT/6:00pm CET
Convener Ram Sriram
Track Whence

Contents

Knowledge graphs, closely related to ontologies and semantic networks, have emerged in the last few years to be an important semantic technology and research area. As structured representations of semantic knowledge that are stored in a graph, KGs are lightweight versions of semantic networks that scale to massive datasets such as the entire World Wide Web. Industry has devoted a great deal of effort to the development of knowledge graphs, and they are now critical to the functions of intelligent virtual assistants such as Siri and Alexa. Some of the research communities where KGs are relevant are Ontologies, Big Data, Linked Data, Open Knowledge Network, Artificial Intelligence, Deep Learning, and many others.     (2A)

Agenda     (2B)

Conference Call Information     (2C)

Attendees     (2D)

Discussion     (2E)

[12:12] Ravi Sharma: Chaitanya - How do you set goals and metrics for measuring successful accelerator program and future directions?     (2E1)

[12:17] Ravi Sharma: Chaitanya (CB) - how can you interoperate heterogeneous data products?     (2E2)

[12:27] ToddSchneider: Is the NSF working with EU agencies or organizations on any of these topics?     (2E3)

[12:27] Ravi Sharma: CB - you say Supporting access by and contributions to the KG by heterogeneous communities of users but what is Definition of KG?     (2E4)

[12:28] Ravi Sharma: what is the common theme on KG by heterogeneous communities?     (2E5)

[12:34] Mark Underwood @knowlengr: re "Users" A challenge is developing models for learners / users ... E.g., in autonomous vehicles the model for drivers, repair, distributors, dealers, teachers are quite different. And within development environments (think VW Dieselgate scenario) modeling enterprise roles is nontrivial.     (2E6)

[12:41] David Eddy: Is there any attention directed at "un-natural language?"     (2E7)

[12:41] Mike Bennett: Is there potential for development of new reference ontology/ies in finance (A7153) and can new participants get involved in the upcoming phases?     (2E8)

[12:43] Mike Bennett: Has OKN marked out a formal distinction between reference ontology (conceptual, real world truth makers etc.) versus application ontologies in Semantic Web and elsewhere (specific do data, driven by application use case). These need to be different but not all see that.     (2E9)

[12:43] ToddSchneider: Yes, ambiguity can be useful.     (2E10)

[12:44] janet singer: Ambiguity as a feature not a bug     (2E11)

[12:44] Gary: At what point will the knowledge networks become accessible to other researchers and the public? Will all phase 1 networks be accessible?     (2E12)

[12:45] Mark Underwood @knowlengr: @janet <g> A NewYorker cartoon caption     (2E13)

[12:46] Gary: Q asked "what metrics can be used?"     (2E14)

[12:47] BobbinTeegarden: @MikeB do you really make a distinction between what you think you see and what you see (conceptual vs 'real')? Perception is a tricky thing ...     (2E15)

[12:48] Mike Bennett: @Bobbin that's the Kantian thing. I'm making a distinction between that and ontologies that are specifically about computational data.     (2E16)

[12:50] Ravi Sharma: Janet and Todd - statisticians call it measure of uncertainties!     (2E17)

[12:53] Ravi Sharma: CB - will NSF CA OKN help us converge on What might be called Common KGs?     (2E18)

[12:55] Mark Underwood @knowlengr: Yes! "Your best friend is your use case." (Not a "definition" !)     (2E19)

[12:57] Ravi Sharma: CB said use-cases have more relevance to demonstrate some apps and users     (2E20)

[12:58] Mark Underwood @knowlengr: Use cases harken strongly back to our 2019 Ontolog theme     (2E21)

[12:59] Mike Bennett: Use cases can if misapplied drive you into silo-ized sets of application ontologies. Unless the use case is framed as 'need for a common language'. Otherwise someone ends up applying the rules for use cases of the sort used to drive individual computational solutions, which rules out ontologies as common business language.     (2E22)

[13:00] janet singer: CB distinguished knowledge networks from knowledge graphs with the latter being CS/technical. One sense of KN was simply connected human experts     (2E23)

[13:01] Mark Underwood @knowlengr: @Mike - what TC68 initiatives are you following (or should I follow) for standards related progress?     (2E24)

[13:01] Mike Bennett: @Mark SC4 WG1 Semantics for ISO 20022     (2E25)

[13:01] David Eddy: @MikeB... isn't "common language" back to Genesis 11: 1 - 9?     (2E26)

[13:02] Ravi Sharma: CB - dataset interoperability implies common metadata?     (2E27)

[13:02] Janette Wong: How do we (those who don't participate in the projects) keep ourselves informed of the projects' outcomes? e.g. A7908 (Spatial Decision Support)     (2E28)

[13:02] Mark Underwood @knowlengr: @Mike, got it thx     (2E29)

[13:02] Ravi Sharma: FARE data     (2E30)

[13:03] Ravi Sharma: Gary - openness?     (2E31)

[13:03] Mike Bennett: FAIR: Findable, accessible interoperable reusable data     (2E32)

[13:03] Mark Underwood @knowlengr: FAIR     (2E33)

[13:04] Mike Bennett: @David, a good example of a construction project that went wrong when there were contractors from too many different jurisdictions and no common standards. (without looking it up I am assuming this Gen 11 is the Tower of Babel)     (2E34)

[13:05] Ravi Sharma: data are to be free of personal info.     (2E35)

[13:05] Ravi Sharma: provenance     (2E36)

[13:06] Ravi Sharma: Janet - great question     (2E37)

[13:07] Mark Underwood @knowlengr: Which Apache project?     (2E38)

[13:08] Sean Gordon: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn     (2E39)

[13:08] Gary: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn     (2E40)

[13:08] Ravi Sharma: @Janette Wong - I'm the PI for A7908, you can find info on our project at http://www.sdsconsortium.org/sds-okn     (2E41)

[13:08] Mark Underwood @knowlengr: @Janette thx     (2E42)

[13:09] ToddSchneider: Meeting ends @13:09 EST     (2E43)

[13:09] janet singer: CB: KN #1 as connected human experts; KN #2 as connected data, entities, relationships; KN #3 as technological infrastructure that enables the knowledge graphs     (2E44)

[13:10] Mark Underwood @knowlengr: @MikeB RE use cases can be abused, but to guide SDO work they are vastly superior endless wrangling over definitions... Even "ontology" brings the philosophers out of the woodwork     (2E45)

Resources     (2F)

Previous Meetings     (2G)


Next Meetings     (2H)