Knowledge Graphs for Impactful Data Science

Victor de Boer*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this invited talk I will argue that to build scalable, transparent and explainable AI in various domains where heterogeneous data is available, we need to collaborate with domain experts to develop relevant and high-quality knowledge graphs as well as appropriate data science and Machine Learning methods to constantly enrich and analyse these graphs. I give examples in the Digital Humanities and Internet of Things.

Original languageEnglish
Title of host publicationSEMPDW 2022 Posters, Demos and Workshops at SEMANTiCS 2022
Subtitle of host publicationProceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022) Vienna, Austria, September 13th to 15th, 2022
EditorsUmutkan Şimşek, David Chaves-Fraga, Tassilo Pellegrini, Sahar Vahdat
PublisherCEUR-WS
Number of pages2
Publication statusPublished - 2022
Event18th International Conference on Semantic Systems, SEMPDW 2022 - Vienna, Austria
Duration: 13 Sept 202215 Sept 2022

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR Workshop Proceedings
Volume3235
ISSN (Print)1613-0073

Conference

Conference18th International Conference on Semantic Systems, SEMPDW 2022
Country/TerritoryAustria
CityVienna
Period13/09/2215/09/22

Bibliographical note

Publisher Copyright:
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

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