Abstract
Knowledge-intensive processes represent a particularly challenging scenario for process mining. The flexibility that such processes allow constitutes a hurdle as it is 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 idea paper, we propose a novel framework leveraging visual analytics for the interactive visualization of multi-faceted process information, aimed at easing the investigation tasks of users in their process analysis tasks. This is primarily achieved by an interconnection of multiple visual layers, which allow our framework to display process information under different perspectives and to project these perspectives onto a domain-friendly representation of the context in which the process unfolds. We demonstrate the feasibility of the framework through its application in two use-case scenarios in the context of healthcare and personal information management.
Original language | English |
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Title of host publication | Process Mining Workshops - ICPM 2023 International Workshops, 2023, Revised Selected Papers |
Editors | Johannes De Smedt, Pnina Soffer |
Publisher | Springer |
Pages | 19-31 |
Number of pages | 13 |
ISBN (Print) | 9783031561061 |
DOIs | |
Publication status | Published - 13 Apr 2024 |
Event | International workshops which were held in conjunction with 5th International Conference on Process Mining, ICPM 2023 - Rome, Italy Duration: 23 Oct 2023 → 27 Oct 2023 |
Publication series
Name | Lecture Notes in Business Information Processing |
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Volume | 503 LNBIP |
ISSN (Print) | 1865-1348 |
ISSN (Electronic) | 1865-1356 |
Conference
Conference | International workshops which were held in conjunction with 5th International Conference on Process Mining, ICPM 2023 |
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Country/Territory | Italy |
City | Rome |
Period | 23/10/23 → 27/10/23 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- Knowledge-intensive processes
- Process mining
- Visual analytics