Data Shapes in Action: Difference between revisions

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Synergies of computational linguistics and RDF

Date: June 16, 2022

Time: Time: 16h UTC London, 17h CET (Berlin, Madrid, Zürich), 11am New York EDT and 8am San Francisco PDT

Registration Count / Attendees: 110/57

Speakers

Veronika Heimsbakk - Managing AI Engineer, Capgemini
https://www.linkedin.com/in/vheimsbakk/

Miriam Næss Jørstad - Senior Data Scientist, Capgemini
https://www.linkedin.com/in/mirnjor/

Description

At the Norwegian Maritime Authority (NMA), a pipeline for extracting context, concepts and relationships in regulatory documents, is running in production. This session will outline the application implementation. Together with technologies used as Natural Language Processing, RDF serialization, and the use of SHACL to describe regulatory requirements. Including several use cases for NMA's knowledge graph.

Shared Event Notes

https://docs.google.com/document/d/1V9YRKYUDXQeCCGALtsTzxnPSvuL4WSsBBcpDtz1PYSM/edit?usp=sharing

Session-Type: Technology - Project
Session-Level: Introduction - Intermediate

@@ Line 1: / Line 1: @@
+__NOTOC__
 ==Synergies of computational linguistics and RDF==
 Date: June 16, 2022
-Time: Time: 17h CET (Berlin, Madrid, Zürich), 16h UTC London, 12pm New York EDT and 9am San Francisco PDT
+Time: Time: 16h UTC London, 17h CET (Berlin, Madrid, Zürich), 11am New York EDT and 8am San Francisco PDT
-Registration Count: 12
+Registration Count / Attendees: 110/57
 <hr>
-Veronika Heimsbakk, Managing AI Engineer and Chief Data Science Geek at Capgemini<br>
+===Speakers===
+Veronika Heimsbakk - Managing AI Engineer, Capgemini<br>
 https://www.linkedin.com/in/vheimsbakk/
-Miriam Næss Jørstad, Senior Data Scientist, Capgemini <br>
+Miriam Næss Jørstad - Senior Data Scientist, Capgemini <br>
 https://www.linkedin.com/in/mirnjor/
+<center><youtube>https://youtu.be/8K3XYTdc3ag</youtube></center>
+===Description===
-<iframe key="lotico" path="/lotico/reg.php?event=DataShapesAction" w="500"/>
+At the [https://www.sdir.no/en/ Norwegian Maritime Authority] (NMA), a pipeline for extracting context, concepts and relationships in regulatory documents, is running in production. This session will outline the application implementation. Together with technologies used as Natural Language Processing, RDF serialization, and the use of SHACL to describe regulatory requirements. Including several use cases for NMA's knowledge graph.
+===Shared Event Notes===
+https://docs.google.com/document/d/1V9YRKYUDXQeCCGALtsTzxnPSvuL4WSsBBcpDtz1PYSM/edit?usp=sharing
+ Session-Type: Technology - Project
+ Session-Level: Introduction - Intermediate
 [[Category:Event]]