In a number of application fields, pieces of data and information need to be modelled and visualised so as to analyse patterns of change over time, or so as to pinpoint time-related causal chains. Briefly said, understanding facts often implies understanding processes that lead to facts, or that derive from facts – and reasoning on processes implies mastering the time parameter.
However, coping with dirty
time-oriented data (inaccurate, incomplete, erroneous, contradictory, etc.) remains, by and large, an open issue. If scientists and practitioners are to foster the emergence of effective solutions, it is of great importance they get an opportunity to confront their approaches, ideas, experiences and methods.
The workshop’s ambition is to foster interdisciplinary scientific exchanges both on theoretical or technological aspects and on practical cases/feedbacks stemming from a wide range of application fields.