Exploration and Assessment of Event Data

TitleExploration and Assessment of Event Data
Publication TypeConference Paper
Year of Publication2015
AuthorsBodesinsky, P., B. Alsallakh, T. Gschwandtner, and S. Miksch
EditorsBertini, E., and J. C. Roberts
Conference NameSixth International EuroVis Workshop on Visual Analytics (EuroVA) 2015
Pages5
PublisherThe Eurographics Association
Conference LocationCagliari, Italy
ISBN Number978-3-905674-86-6
Keywordsarc diagrams, event data, EventExplorer, log data, pattern mining, Visual analytics, Visual Process Mining
Abstract

Event data is generated in many domains, like business process management, industry or healthcare. These datasets are often unstructured, exhibit variant behavior, and may contain errors. Before applying automated analysis methods, such as process mining algorithms, the analyst needs to understand the dependency between events in order to decide which analysis method might fit the recorded events. We define a categorization scheme of event dependencies and describe a preliminary approach for exploring event data, combining visual exploration with pattern mining. Events of interest can be selected, grouped, and visually explored, using either a sequential or a temporal scale. We present two use cases with shopping event data and report expert feedback on our approach.

URLhttps://diglib.eg.org/handle/10.2312/eurova.20151106.067-071
DOI10.2312/eurova.20151106
AttachmentSize
paper354.99 KB
video5.86 MB
Funding projects: 
CVAST