The general objective of data and process science and engineering is the development of techniques for the efficient modelling, representation, storage and processing of data to extract knowledge and facilitate decision making. Achieving this goal requires a multidisciplinary approach combining, among others, artificial intelligence, information representation and high-performance computing strategies.
In this area, data nature imposes a series of restrictions on the problems to be solved, particularly when dealing with the management and analysis of business processes, presently a very active field both from the point of view of the development of improvements in the storage of information and the extraction of analytics to understand the behaviour and evolution of processes in order to optimise and improve business indicators.
In this framework, research is not only oriented towards processing and extracting knowledge to describe what is happening within a problem or process, but also to predict indicators of interest, diagnose the causes that explain the evolution of these indicators or propose actions to optimise process execution. This research is framed in multiple application domains, such as health, industry, finance or education.