Data-aware Processes: Modeling, Mining, and Verification

Course at the
3rd International Winter School on Big Data (BigDat 2017)
Bari, Italy, 13-17 February 2017

Diego Calvanese

Research Centre for Knowledge and Data (KRDB)
Free University of Bozen-Bolzano

Slides of the course

  1. Part 1: Modeling
  2. Part 2: Mining
    (with an Oveview of OBDA)
  3. Part 3: Verification


The need of combining static (i.e., data-related) and dynamic (i.e., process-related) aspects has been increasingly recognized as a key requirement towards the design, understanding, and verification of complex systems. In this course, we analyze this combination from different points of view. We first consider the problem of modeling such systems, considering how one can capture the structural aspects of a domain of interest and their evolution over time. Specifically, we present and discuss the artifact-centric approach, and concrete modeling formalisms that are based on it. We then consider the problem of process mining, which is concerned with eliciting a model of the dynamics of a system from system logs, and we discuss how techniques developed for data access based on ontologies can be profitably exploited for this. Finally, we consider verification, starting from the observation that in the traditional case where data is abstracted away, states are propositional, resulting in a transition system capturing the system behaviour that is finite-state. However, in the presence of data, states need to be modeled relationally, causing the transition system to become infinite-state in general. Furthermore, data call for verification languages based on first-order temporal logics. The resulting verification problem is much harder than in the finite-state setting, leading to undecidability even for severely restricted systems. We address the fundamental problem of studying data-aware process formalisms and appropriate verification languages, which on the one hand guarantee decidability of verification, and on the other hand allow one to capture real-world scenarios.

Presentation style: lectures with slides

Prerequisite knowledge: basic knowledge in first-order logic and relational databases

Course duration: three lectures of 2 hours each

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Last modified: Thursday, 30-Jan-2020 22:34:04 CET