Techniques for a posteriori analysis of declarative processes

A. Burattin, F.M. Maggi, W.M.P. Aalst, van der, A. Sperduti

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

40 Citations (Scopus)

Abstract

The increasing availability of event data recorded by information systems, electronic devices, web services and sensor networks provides detailed information about the actual processes in systems and organizations. Process mining techniques can use such event data to discover processes and check the conformance of process models. For conformance checking, we need to analyze whether the observed behavior matches the modeled behavior. In such settings, it is often desirable to specify the expected behavior in terms of a declarative process model rather than of a detailed procedural model. However, declarative models do not have an explicit notion of state, thus making it more difficult to pinpoint deviations and to explain and quantify discrepancies. This paper focuses on providing high-quality and understandable diagnostics. The notion of activation plays a key role in determining the effect of individual events on a given constraint. Using this notion, we are able to show cause-and-effect relations and measure the healthiness of the process.
Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE 16th International Enterprise Distributed Object Computing Conference (EDOC, Beijing, China, September 10-14, 2012)
PublisherIEEE Computer Society
Pages41-50
DOIs
Publication statusPublished - 2012
Event16th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2012) - Beijing, China
Duration: 10 Sep 201214 Sep 2012
Conference number: 16

Conference

Conference16th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2012)
Abbreviated titleEDOC 2012
Country/TerritoryChina
City Beijing
Period10/09/1214/09/12
Other"When Services in Cloud Meet Enterprises"

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