Quotation Cabanillas Macias, Cristina, Ackermann, Lars, Schönig, Stefan, Sturm, Christian, Mendling, Jan. 2020. The RALph miner for automated discovery and verification of resource-aware process models. Software and Systems Modeling. 19 1415-1441.




Automated process discovery is a technique that extracts models of executed processes from event logs. Logs typically include information about the activities performed, their timestamps and the resources that were involved in their execution. Recent approaches to process discovery put a special emphasis on (human) resources, aiming at constructing resource-aware process models that contain the inferred resource assignment constraints. Such constraints can be complex and process discovery approaches so far have missed the opportunity to represent expressive resource assignments graphically together with process models. A subsequent verification of the extracted resource-aware process models is required in order to check the proper utilisation of resources according to the resource assignments. So far, research on discovering resource-aware process models has assumed that models can be put into operation without modification and checking. Integrating resource mining and resource-aware process model verification faces the challenge that different types of resource assignment languages are used for each task. In this paper, we present an integrated solution that comprises (i) a resource mining technique that builds upon a highly expressive graphical notation for defining resource assignments; and (ii) automated model-checking support to validate the discovered resource-aware process models. All the concepts reported in this paper have been implemented and evaluated in terms of feasibility and performance.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Software and Systems Modeling
Citation Index SCI
Language English
Title The RALph miner for automated discovery and verification of resource-aware process models
Volume 19
Year 2020
Page from 1415
Page to 1441
URL http://link.springer.com/content/pdf/10.1007/s10270-020-00820-7.pdf
DOI http://dx.doi.org/10.1007/s10270-020-00820-7
Open Access Y
Open Access Link https://link.springer.com/content/pdf/10.1007/s10270-020-00820-7.pdf


Cabanillas Macias, Cristina (Former researcher)
Schönig, Stefan (Former researcher)
Mendling, Jan (Details)
Ackermann, Lars (University of Bayreuth, Germany)
Sturm, Christian (University of Bayreuth, Germany)
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1138 Information systems (Details)
1140 Software engineering (Details)
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