TY - GEN
T1 - VDS'21
T2 - 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021
AU - Plant, Claudia
AU - Ottley, Alvitta
AU - Gou, Liang
AU - Möller, Torsten
AU - Perer, Adam
AU - Lex, Alexander
AU - Shao, Junming
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/8/14
Y1 - 2021/8/14
N2 - 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, 2021 (Held in conjunction with KDD'21). The workshop website is available at: http://www.visualdatascience.org/2021/
AB - 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, 2021 (Held in conjunction with KDD'21). The workshop website is available at: http://www.visualdatascience.org/2021/
KW - data mining
KW - data science
KW - data visualization
KW - interpretation
UR - https://www.scopus.com/pages/publications/85114940971
U2 - 10.1145/3447548.3469466
DO - 10.1145/3447548.3469466
M3 - Conference contribution
AN - SCOPUS:85114940971
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 4149
EP - 4150
BT - KDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
Y2 - 14 August 2021 through 18 August 2021
ER -