APROMORE: An advanced process model repository

Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionality and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.     

Time prediction based on process mining

Process mining allows for the automated discovery of process models from event logs. These models provide insights and enable various types of model-based analysis. This paper demonstrates that the discovered process models can be extended with information to predict the completion time of running instances. There are many scenarios where it is useful to have reliable time predictions. For example, when a customer phones her insurance company for information about her insurance claim, she can be given an estimate for the remaining processing time. In order to do this, we provide a configurable approach to construct a process model, augment this model with time information learned from earlier instances, and use this to predict e.g., the completion time. To provide meaningful time predictions we use a configurable set of abstractions that allow for a good balance between “overfitting” and “underfitting”. The approach has been implemented in ProM and through several experiments using real-life event logs we demonstrate its applicability.     

Betriebsinformatik und Wirtschaftsinformatik als notwendige anwendungsbezogene Ergänzung einer allgemeinen Informatik – Vorschläge zur Verbesserung der akademischen Ausbildung auf dem Gebiet der automatisierten Datenverarbeitung in der Bundesrepublik Deutschland

Zusammenfassung  Nachdruck eines Aufsatzes aus elektronische datenverarbeitung 11(11)1969:544–548. This article is also available in English via and : Grochla E (2008) Corporate Information Systems Engineering and Business and Information Systems Engineering as a Necessary Application-Oriented Extension of General Computer Science – Proposals for Enhancing Academic Education in the Field of Automated Data Processing in the Federal Republic of Germany. Bus Inf Syst Eng. doi .

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Reduction rules for YAWL workflows with cancellation regions and OR-joins

As the need for concepts such as cancellation and OR-joins occurs naturally in business scenarios, comprehensive support in a workflow language is desirable. However, there is a clear trade-off between the expressive power of a language (i.e., introducing complex constructs such as cancellation and OR-joins) and ease of verification. When a workflow contains a large number of tasks and involves complex control flow dependencies, verification can take too much time or it may even be impossible. There are a number of different approaches to deal with this complexity. Reducing the size of the workflow, while preserving its essential properties with respect to a particular analysis problem, is one such approach. In this paper, we present a set of reduction rules for workflows with cancellation regions and OR-joins and demonstrate how they can be used to improve the efficiency of verification. Our results are presented in the context of the YAWL workflow language.     

Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response

In radiotherapy, tumors are irradiated with a high dose, while surrounding healthy tissues are spared. To quantify the probability that a tumor is effectively treated with a given dose, statistical models were built and employed in clinical research. These are called tumor control probability (TCP) models. Recently, TCP models started incorporating additional information from imaging modalities. In this way, patient‐specific properties of tumor tissues are included, improving the radiobiological accuracy of models. Yet, the employed imaging modalities are subject to uncertainties with significant impact on the modeling outcome, while the models are sensitive to a number of parameter assumptions. Currently, uncertainty and parameter sensitivity are not incorporated in the analysis, due to time and resource constraints. To this end, we propose a visual tool that enables clinical researchers working on TCP modeling, to explore the information provided by their models, to discover new knowledge and to confirm or generate hypotheses within their data. Our approach incorporates the following four main components: (1) It supports the exploration of uncertainty and its effect on TCP models; (2) It facilitates parameter sensitivity analysis to common assumptions; (3) It enables the identification of inter‐patient response variability; (4) It allows starting the analysis from the desired treatment outcome, to identify treatment strategies that achieve it. We conducted an evaluation with nine clinical researchers. All participants agreed that the proposed visual tool provides better understanding and new opportunities for the exploration and analysis of TCP modeling.     

An algorithm for generalizing topography to grids while preserving subscale morphologic characteristics—creating a glacier bed DEM for Jakobshavn trough as low-resolution input for dynamic ice-sheet models

The objective of this paper is to derive an algorithm for preserving important subscale morphologic characteristics at grids of lower-resolution, in particular for linear features such as canyons and ridge lines. The development of such an algorithm is necessitated by applications that require reduced spatial resolution, as is common in cartographic generalization, GIS applications, and geophysical modeling. Since any algorithm that results in weighted averages, including optimum interpolation and ordinary kriging, cannot reproduce correct depths, a new algorithm is designed based on principles of mathematical morphology. The algorithm described here is applied to derive a subglacial bed of the Greenland Ice Sheet that includes the trough of Jakobshavn Isbræ as a continuous canyon at correct depth in a low-resolution (5-km) digital elevation model (DEM). Data from recent airborne radar measurements of the elevation of the subglacial bed as part of the CReSIS project are utilized. The morphologic algorithm is designed with geophysical ice-sheet modeling in mind, in the following context. Currently occurring changes in the Earth's climate and the cryosphere cause changes in sea level, and the societal relevance of these natural processes motivates estimation of maximal sea-level rise in the medium-term future. The fast-moving outlet glaciers are more sensitive to climatic change than other parts of the Greenland ice sheet. Jakobshavn Isbrae, the fastest-moving ice stream in Greenland, follows a subglacial geologic trough. Since the existence of the trough causes the acceleration of the slow-moving inland ice in the Jakobshavn region and the formation of the ice stream, correct representation of the trough in a DEM is essential to model changes in the dynamics of the ice sheet and resultant sea-level predictions, even if current ice-sheet models can typically be run only at 5-km resolution. The DEM resultant from this study helps to bridge the conceptual gap between data analysis and geophysical modeling approaches. It is available as SeaRISE Greenland bed data set dev1.2 at http://websrv.cs.umt.edu/isis/index.php/SeaRISE_Assessment.