Visualization in Data Science VDS @ KDD 2022

Claudia Plant, Nina C. Hubig, Junming Shao, Alvitta Ottley, Liang Gou, Torsten Möller, Adam Perer, Alexander Lex, Anamaria Crisan

Publications: Contribution to bookContribution to proceedingsPeer Reviewed

Abstract

Data science is the practice of deriving insight from data, enabled by modeling, computational methods, interactive visual analysis, and domain-driven problem solving. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. Machine learning and data mining and visualization are integral parts of data science, and essential to enable sophisticated analysis of data. Nevertheless, both research areas are currently still rather separated and investigated by different communities rather independently. The goal of this workshop is to bring researchers from both communities together in order to discuss common interests, to talk about practical issues in application-related projects, and to identify open research problems. This summary gives a brief overview of the ACM KDD Workshop on Visualization in Data Science (VDS at ACM KDD and IEEE VIS), which will take place virtually on Aug 14-18, 2022 (Held in conjunction with KDD'22). The workshop website is available at http://www.visualdatascience.org/2022/

Original languageEnglish
Title of host publicationKDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022
EditorsAidong Zhang, Huzefa Rangwala
PublisherACM
Pages4894-4895
Number of pages2
ISBN (Electronic)9781450393850
DOIs
Publication statusPublished - 2022

Austrian Fields of Science 2012

  • 102033 Data mining

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