Visual pattern discovery in timed event data

Schäfer, Matthias; Wanner, Franz; Mansmann, Florian; Scheible, Christian; Stennett, Verity; Hasselrot, Anders T.; Keim, Daniel A.

Visual pattern discovery in timed event data

Dateien

Schaefer_193931.pdfGröße: 417.29 KBDownloads: 908

Datum

2011

Autor:innen

Stennett, Verity

Hasselrot, Anders T.

Keim, Daniel A.

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

WONG, Pak Chung, ed. and others. Visualization and Data Analysis 2011. SPIE, 2011, pp. 78680K-78680K-12. SPIE Proceedings. 7868. Available under: doi: 10.1117/12.871870

Zusammenfassung

Business processes have tremendously changed the way large companies conduct their business: The integration of information systems into the workflows of their employees ensures a high service level and thus high customer satisfaction. One core aspect of business process engineering are events that steer the workflows and trigger internal processes. Strict requirements on interval-scaled temporal patterns, which are common in time series, are thereby released through the ordinal character of such events. It is this additional degree of freedom that opens unexplored possibilities for visualizing event data. In this paper, we present a flexible and novel system to find significant events, event clusters and event patterns. Each event is represented as a small rectangle, which is colored according to categorical, ordinal or intervalscaled metadata. Depending on the analysis task, different layout functions are used to highlight either the ordinal character of the data or temporal correlations. The system has built-in features for ordering customers or event groups according to the similarity of their event sequences, temporal gap alignment and stacking of co-occurring events. Two characteristically different case studies dealing with business process events and news articles demonstrate the capabilities of our system to explore event data.

Fachgebiet (DDC)

004 Informatik

Konferenz

IS&T/SPIE Electronic Imaging, San Francisco, California

Zitieren

ISO 690

SCHÄFER, Matthias, Franz WANNER, Florian MANSMANN, Christian SCHEIBLE, Verity STENNETT, Anders T. HASSELROT, Daniel A. KEIM, 2011. Visual pattern discovery in timed event data. IS&T/SPIE Electronic Imaging. San Francisco, California. In: WONG, Pak Chung, ed. and others. Visualization and Data Analysis 2011. SPIE, 2011, pp. 78680K-78680K-12. SPIE Proceedings. 7868. Available under: doi: 10.1117/12.871870

BibTex

@inproceedings{Schafer2011-01-24Visua-19393,
  year={2011},
  doi={10.1117/12.871870},
  title={Visual pattern discovery in timed event data},
  number={7868},
  publisher={SPIE},
  series={SPIE Proceedings},
  booktitle={Visualization and Data Analysis 2011},
  pages={78680K--78680K-12},
  editor={Wong, Pak Chung},
  author={Schäfer, Matthias and Wanner, Franz and Mansmann, Florian and Scheible, Christian and Stennett, Verity and Hasselrot, Anders T. and Keim, Daniel A.}
}

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Universitätsbibliographie

Ja