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Auflistung nach Schlagwort "Event sequence data"

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  • Textdokument
    Event sequence analysis and visualization
    (EMISA 2024, 2024) Yeshchenko, Anton; Mendling, Jan
    Event sequence analysis is an important field of computer science due to its relevance to a diverse spectrum of application domains such as manufacturing, logistics, healthcare, financial services, education, to name but a few. Despite this broad relevance across these domains, it is striking to observe that techniques for event sequence data analysis have been developed rather independently in different fields of computer science. The most prominent research fields investigating the analysis of event sequence data are process mining and information visualization. Process mining has emerged as a subfield of research on workflow management systems. Its focus is the development of new techniques for automatic process discovery from event sequence data with the ambition to provide a meaningful and understandable summary of the behavior to the business process analyst. Information visualization is a field of computer graphics, which originated as a subfield of human–computer interaction. Its focus is on devising new techniques for visualizing event sequence data in a meaningful way such that analysts can effectively explore them. Typical representations frequently used in this field are timelines that plot conceptually related sequences of events over a time axis. As similar as the ambitions of these research areas may sound, it is surprising that there is hardly any exchange of ideas. Cross-references are scarce and mutual awareness and understanding is limited.1 All this makes research on event sequence analysis a fragmented field with scattered contributions. So far, the contributions from these two fields have neither been compared nor have they been mapped to an integrated framework. At this stage, it is not clear to which extent both fields have developed complementary concepts and insights. Such intransparency is problematic since it bears the risk of opportunities of integration are missed and concepts established in one field are independently reinvented in the other one. In this current research talk at EMISA 2024 based on a recent article, we develop such a framework that we call Event Sequence Visualization framework (ESeVis) and that gives due credit to the traditions of both fields. Our mapping study provides an integrated perspective on both fields and potential synergies for future research. In this way, our work contributes towards overcoming the fragmentation of research on event sequence data analysis.