Uncertainty Managament

Aims and Scope

Given the growth and availability of data collected from different resources, extracting knowledge and relevant information from these data has become an important challenge. Data Science techniques and methods allow the extraction of such Knowledge or insights from data in various forms, either structured or unstructured. The complexity of data and the complexity of simulating complex phenomena make the process of extracting knowledge usually uncertain. Therefore, uncertainty quantification becomes a necessary requirement when designing numerical, mathematical and computer based methods. Authors are invited to submit original work in all areas of Data Science and Uncertainty fields.

List of tracks

  •   Uncertainty theories (probability, possibility, belief functions...)
  •   Machine learning
  •   Information fusion
  •   Big Data
  •   Database management