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== Agenda ==
 
== Agenda ==
 
* Convening of session.  It will begin with a short (15 minute) review of related work in network science, then it will split into working groups as on Monday and Tuesday.
 
* Convening of session.  It will begin with a short (15 minute) review of related work in network science, then it will split into working groups as on Monday and Tuesday.
* '''David Hurlburt''' ''Review of Network Science''
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* '''[[George Hurlburt|George Hurlburt]]''' ''Graphs: A Fundamental shift from Linear to non-linear'' [https://go.aws/3enAu2M Slides]
 
* Splitting into working groups with each group in its own Zoom room, wiki page and soaphub chat room as follows:
 
* Splitting into working groups with each group in its own Zoom room, wiki page and soaphub chat room as follows:
 
** Room 1: [[OntologySummit2020/Whence|Whence]] - What brought the use of graphs in as persistence mechanisms.  Will need to address other non-relational persistence mechanisms; historical background; this can include parts of 'why'.
 
** Room 1: [[OntologySummit2020/Whence|Whence]] - What brought the use of graphs in as persistence mechanisms.  Will need to address other non-relational persistence mechanisms; historical background; this can include parts of 'why'.

Latest revision as of 22:15, 21 June 2020

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    (1)
Session Communiqué
Duration 2 hours
Date/Time 24 June 2020 16:00 GMT
9:00am PDT/12:00pm EDT
5:00pm BST/6:00pm CEST
Convener KenBaclawski

Contents

[edit] Ontology Summit 2020 Communiqué Development     (2)

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)

[edit] Conference Call Information     (2C)

[edit] Attendees     (2D)

[edit] Proceedings     (2E)

[edit] Resources     (2F)

[edit] Previous Meetings     (2G)


[edit] Next Meetings     (2H)