Meike Ullrich
Karlsruhe Institute of Technology
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Publication
Featured researches published by Meike Ullrich.
business process management | 2013
Ugur Cayoglu; Remco M. Dijkman; Marlon Dumas; Peter Fettke; Luciano García-Bañuelos; Philip Hake; Christopher Klinkmüller; Henrik Leopold; André Ludwig; Peter Loos; Jan Mendling; Andreas Oberweis; Andreas Schoknecht; Eitam Sheetrit; Tom Thaler; Meike Ullrich; Ingo Weber; Matthias Weidlich
Process model matching refers to the creation of correspondences between activities of process models. Applications of process model matching are manifold, reaching from model validation over harmonization of process variants to effective management of process model collections. Recently, this demand led to the development of different techniques for process model matching. Yet, these techniques are heuristics and, thus, their results are inherently uncertain and need to be evaluated on a common basis. Currently, however, the BPM community lacks established data sets and frameworks for evaluation. The Process Model Matching Contest 2013 aimed at addressing the need for effective evaluation by defining process model matching problems over published data sets.
conference on advanced information systems engineering | 2015
Agnes Koschmider; Meike Ullrich; Antje Heine; Andreas Oberweis
A variety of methods devoted to the behavior analysis of business process models has been suggested, which diminish the task of inspecting the correctness of the model by the process modeler. Although a correct behavior has been attested, the process model might still not be feasible because the modeler or intended user is hampered in her comprehension (and thus hesitates e.g., to reuse the process model). This paper addresses the improvement of comprehension of process element labels by revising their vocabulary. Process element labels are critical for an appropriate association between the symbol instance and the real world. If users do not (fully) understand the process element labels, an improper notion of the real process might arise. To improve the comprehension of element labels algorithms are presented, which base on common hints how to effectively recognize written words. Results from an empirical study indicate a preference for such revised process element labels.
OTM Confederated International Conferences "On the Move to Meaningful Internet Systems" | 2013
Agnes Koschmider; Simone Kriglstein; Meike Ullrich
Numerous attempts have been made to research the variety of different influences on the understandability of process models. Common to all of these attempts is the limitation to the process model itself. Little empirical effort is spent on investigating the understandability of the alignment of process activities, objects, and roles. This paper tackles this issue and empirically studies preferences of how to visually align process activities with objects and roles. In particular, three visualization techniques are evaluated in order to support the combination of the object and organization units with their corresponding process model elements. The empirical study provides a strong support for the visualization of a process model that is disburdened from context information such as objects used and roles involved and thus is reduced to the sole visualization of process activities and its control-flow.
business process management | 2013
Ugur Cayoglu; Andreas Oberweis; Andreas Schoknecht; Meike Ullrich
ieee conference on business informatics | 2013
Timm Caporale; Murat Citak; Jonas Lehner; Andreas Schoknecht; Meike Ullrich
european conference on information systems | 2013
Timm Caporale; Murat Citak; Jonas Lehner; Andreas Oberweis; Andreas Schoknecht; Meike Ullrich
ZEUS | 2016
Meike Ullrich; Andreas Schoknecht
Modellierung 2016. Workshopband. Hrsg.: S. Betz | 2016
Dominik Augenstein; Murat Citak; Meike Ullrich; Arthur Vetter
DeLFI | 2016
Michael Fellmann; Peter Fettke; Constantin Houy; Peter Loos; Andreas Oberweis; Andreas Schoknecht; Michael Striewe; Tom Thaler; Meike Ullrich
Emisa Forum | 2013
Agnes Koschmider; Simone Kriglstein; Meike Ullrich