CALL FOR PAPERS
ECDA solicits contributions to theoretical as well as application-oriented research on topics in the realm of data science, with a specific focus on data analytics. With its motto „Multidisciplinary Facets of Data Science“, ECDA 2019 specifically emphasizes the important interplay of disciplines involved in data science, most notably statistics and computer science. Topics of interest include, but are not limited to the following:
- Theory and Methods: Big Data; Clustering, Classification, Discrimination and Regression; Data Science; Databases and Data Management; Data Mining, Text and Web Mining; Data Visualization; Dimension Reduction; Image Analysis and Computer Vision; Impact of Technical Revolution and Library Science; Knowledge Representation and Discovery; Machine Learning; Mathematical Foundations of Data Science; Multivariate Methods; Online Algorithms and Algorithms for Data Streams; Social Network Analysis; Statistical and Econometric Methods; Symbolic Data Analysis.
- Applications: Archeology; Biostatistics; Business and Management; Economics; Education; Engineering; Finance; Geosciences; Industrial Automation; Linguistics; Marketing; Medicine and Health Care; Musicology; Psychology; Risk Management; Social Sciences.
Besides, ECDA will feature several special sessions on interesting research themes within the scope of the conference.
- Abstract submission: December 1, 2018
- Notification of abstract acceptance or rejection: December 31, 2018
- Early registration deadline: January 15, 2019
- Registration deadline: February 15, 2019
- Full paper submission: May 15, 2019
Titles and abstracts are submitted in plain text (no LaTeX, no .docx). The length of an abstract should be around 300 words (with 500 words as a strict upper bound). Formatting guidelines for full papers will be provided after the conference.
Further information about the submission procedure is coming soon.
Accepted abstracts will be published in the book of abstracts and made available at the conference. Accepted full papers will be published in the Journal „Archives of Data Science, Series A“.