Bite-Sized Taxonomy Boot Camp London
Virtual (online event)Bite-Sized Taxonomy Boot Camp London will feature three virtual bite-sized taxonomy tutorials.
Conferences and other events about knowledge graphs, linked data and related topics
While every effort has been made to keep these listings current, in light of the COVID-19 pandemic always check the linked event site for the most up-to-date information concerning that event.
Bite-Sized Taxonomy Boot Camp London will feature three virtual bite-sized taxonomy tutorials.
An expert panel will address the meaning, uses and business value of headless content management systems.
The ACM Conference on Web Science 2021 is an interdisciplinary conference where a multitude of research disciplines converge with the purpose of creating a greater insight into a complex global Web.
This webinar will explore knowledge graphs in the context of financial forecasting and investment management strategy.
2021 LD4 Conference on Linked Data will focus on concrete ways that linked data impacts galleries, libraries, archives and museums.
This webinar will examine an emerging approach called Enterprise 360 – where organizations can implement enterprise knowledge graphs to achieve 360-degree views of business relating to customers, employees, products, and services.
Learn how semantic models, classification, and extraction provide the context and meaning to supercharge machine learning.
In this webinar Heather Hedden will discuss various aspects of taxonomy management.
Language, Data and Knowledge (LDK) 2021 brings together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications.
This tutorial is targeted for developers (in particular of DBpedia Chapters) that wish to learn how to replicate local infrastructure such as loading and hosting an own SPARQL endpoint, and will also address the new DBpedia Stack, which contains several dockerized applications that are automatically loading data from the databus.