Tiramisù: making sense of multi-faceted process information through time and space

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Abstract
Knowledge-intensive processes represent a particularly challenging scenario for process mining. The flexibility that such processes allow constitutes a hurdle as they are hard to capture in a single model. To tackle this problem, multiple visual representations of the same processes could be beneficial, each addressing different information dimensions according to the specific needs and background knowledge of the concrete process workers and stakeholders. In this paper, we propose, describe, and evaluate a framework, named , that leverages visual analytics for the interactive visualization of multi-faceted process information, aimed at supporting the investigation and insight generation of users in their process analysis tasks. is based on a multi-layer visualization methodology that includes a visual backdrop that provides context and an arbitrary number of superimposed and on-demand dimension layers. This arrangement allows our framework to display process information from different perspectives and to project this information onto a domain-friendly representation of the context in which the process unfolds. We provide an in-depth description of the approach’s founding principles, deeply rooted in visualization research, that justify our design choices for the whole framework. We demonstrate the feasibility of the framework through its application in two use-case scenarios in the context of healthcare and personal information management. Plus, we conducted qualitative evaluations with potential end users of both scenarios, gathering precious insights about the efficacy and applicability of our framework to various application domains.
Funding Information
  • European Social Fund Plus
  • Eesti Teadusagentuur (PRG1226)
  • Italian Ministry of University and Research (B87G22000450001 (PINPOINT))
  • EU-NGEU (Project SERICS (PE00000014))
  • FEDER, UE (PID2021-126227NB-C21/ AEI/10.13039/501100011033)
  • Unión Europea NextGenerationEU/PRTR (TED2021-131023B-C22/ AEI/10.13039/501100011033)

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