Tiramisù:通过时间和空间理解多方面的过程信息

IF 2.3 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Information Systems Pub Date : 2024-08-14 DOI:10.1007/s10844-024-00875-8
Anti Alman, Alessio Arleo, Iris Beerepoot, Andrea Burattin, Claudio Di Ciccio, Manuel Resinas
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引用次数: 0

摘要

对于流程挖掘而言,知识密集型流程是一个特别具有挑战性的场景。这种流程的灵活性构成了一个障碍,因为它们很难被一个单一的模型所捕捉。为了解决这个问题,对同一流程进行多种可视化表示可能是有益的,每种可视化表示都能根据具体流程工作者和利益相关者的特定需求和背景知识来处理不同的信息维度。在本文中,我们提出、描述并评估了一个名为 Tiramisù 的框架,该框架利用可视化分析技术对多方面的流程信息进行交互式可视化,旨在支持用户在流程分析任务中进行调查并提出见解。Tiramisù 基于多层可视化方法,包括提供上下文的可视化背景以及任意数量的叠加和按需维度层。这种安排使我们的框架能够从不同角度显示流程信息,并将这些信息投射到流程所处环境的领域友好表示法上。我们深入介绍了该方法的基本原则,这些原则深深植根于可视化研究,并为我们对整个框架的设计选择提供了依据。我们通过在医疗保健和个人信息管理两个使用场景中的应用,证明了该框架的可行性。此外,我们还对这两个场景的潜在最终用户进行了定性评估,收集了有关我们的框架在不同应用领域的有效性和适用性的宝贵见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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.

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来源期刊
Journal of Intelligent Information Systems
Journal of Intelligent Information Systems 工程技术-计算机:人工智能
CiteScore
7.20
自引率
11.80%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The mission of the Journal of Intelligent Information Systems: Integrating Artifical Intelligence and Database Technologies is to foster and present research and development results focused on the integration of artificial intelligence and database technologies to create next generation information systems - Intelligent Information Systems. These new information systems embody knowledge that allows them to exhibit intelligent behavior, cooperate with users and other systems in problem solving, discovery, access, retrieval and manipulation of a wide variety of multimedia data and knowledge, and reason under uncertainty. Increasingly, knowledge-directed inference processes are being used to: discover knowledge from large data collections, provide cooperative support to users in complex query formulation and refinement, access, retrieve, store and manage large collections of multimedia data and knowledge, integrate information from multiple heterogeneous data and knowledge sources, and reason about information under uncertain conditions. Multimedia and hypermedia information systems now operate on a global scale over the Internet, and new tools and techniques are needed to manage these dynamic and evolving information spaces. The Journal of Intelligent Information Systems provides a forum wherein academics, researchers and practitioners may publish high-quality, original and state-of-the-art papers describing theoretical aspects, systems architectures, analysis and design tools and techniques, and implementation experiences in intelligent information systems. The categories of papers published by JIIS include: research papers, invited papters, meetings, workshop and conference annoucements and reports, survey and tutorial articles, and book reviews. Short articles describing open problems or their solutions are also welcome.
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