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 Tiramisù, 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. Tiramisù 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.
| Original language | English |
|---|---|
| Pages (from-to) | 1081-1103 |
| Number of pages | 23 |
| Journal | Journal of Intelligent Information Systems |
| Volume | 64 |
| Issue number | 3 |
| Early online date | 14 Aug 2024 |
| DOIs | |
| Publication status | Published - Jun 2026 |
Bibliographical note
Publisher Copyright:© The Author(s) 2024.
Funding
The work of A. Alman was supported by the European Social Fund via \u201CICT programme\u201D measure and by the Estonian Research Council grant PRG1226. The work of M. Resinas was partially supported by projects PID2021-126227NB-C21/ AEI/10.13039/501100011033/ FEDER, UE and TED2021-131023B-C22/ AEI/10.13039/501100011033/ Uni\u00F3n Europea NextGenerationEU/PRTR.
| Funders | Funder number |
|---|---|
| European Social Fund | |
| Estonian Research Council | PRG1226 |
| Union Europea NextGenerationEU/PRTR | PID2021-126227NB-C21/AEI, TED2021-131023B-C22/AEI |
Keywords
- Knowledge-intensive processes
- Process mining
- Visual analytics
- Visualization
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