The European Conference on Data Analysis (ECDA) provides a forum for scientific exchange in the realm of data science, whereby theory and application are of equal interest. The conference offers scientists and practitioners the opportunity to present their research questions and latest results and to discuss them with a qualified expert audience. Among the special characteristics of the conference is its strong emphasis on interdisciplinarity: in addition to participants with a rather theoretical focus, especially from mathematics, statistics, and computer science, the conference is also visited by a wide circle of users of statistical and data-analytical methods, for example from econometrics, marketing, bioinformatics, or psychology.

The ECDA is organized under the auspices of the Gesellschaft für Klassifikation - Data Science Society (GfKl). It will be organzied in cooperation with the European Association for Data Science (EuADS), Dutch/Flemish Classification Society (VOC), Classification and Data Analysis Group of the Italian Statistical Society (CLADAG), Classification and Data Analysis Section of the Polish Statistical Association (SKAD) and the British Data Science Society (BDSS).

Over the years, several topics have been established. These topics do address both methodological as well as applied aspects of data science:  

Methodological topics:

Algorithmic fairness,Bayesian methods,Causal inference,Clustering,Computational statistics,Computer vision,Data visualization,Depth-based methods,Explainanble AI,Image analysis,Invariant coordinate selection,Large language models,Meta-analysis,Missing data analysis,Mixture models,Multivariate statistics,Neural networks and deep learning,Partial least squares and structural equation modeling,Preference-based learning,Robust methods,Statistical learning,Symbolic and fuzzy data analysis,Text mining,Tree-based methods,Uncertainty in machine learning

Applied data science:

Audio signal analysis, Behavioral data science, Biostatistics, Consumer preference analysis, Credit scoring, Decision making, Demography, Economics, Epidemiology, Finance, Healthcare, Data Science in HR, Journalism, Marketing, Medicine, Official statistics, Psychometrics, Risk management, Sensometrics, Social sciences, Tourism