Prof. Manfred Reichert

Universitat Ulm, Institute of Databases and Information Systems, Ulm, Germany

Prof. Manfred Reichert

Universitat Ulm, Institute of Databases and Information Systems, Ulm, Germany

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Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 May 2008 in Data & Knowledge Engineering

Journal Article

Change patterns and change support features – Enhancing flexibility in process-aware information systems

Barbara Weber

Manfred Reichert

Stefanie Rinderle-Ma

21 October 2020 in IEEE Systems, Man, and Cybernetics Magazine

Journal Article

The Internet of Things Meets Business Process Management: A Manifesto

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The Internet of Things (IoT) refers to a network of connected devices that collects and exchanges data through the Internet. These things can be artificial or natural and interact as autonomous agents that form a complex system. In turn, business process management (BPM) was established to analyze, discover, design, implement, execute, monitor, and evolve collaborative business processes within and across organizations. While the IoT and BPM have been regarded as separate topics in research and in practice, we strongly believe that, on the one hand, the management of IoT applications will greatly benefit from BPM concepts, methods, and technologies. On the other hand, the IoT poses challenges that will require enhancements and extensions of the current state of the art in the BPM field. In this article, we question the extent to which these two paradigms can be combined, and we discuss emerging challenges and intersections from a research and practitioner's point of view in terms of complex software systems development.

22 April 2009 in Computer Science - Research and Development

Journal Article

The ADEPT project: a decade of research and development for robust and flexible process support

Peter Dadam

Manfred Reichert

1 April 2015 in Information Systems

Journal Article

Dealing with change in process choreographies: Design and implementation of propagation algorithms

Enabling process changes constitutes a major challenge for any process-aware information system. This not only holds for processes running within a single enterprise, but also for collaborative scenarios involving distributed and autonomous partners. In particular, if one partner adapts its private process, the change might affect the processes of the other partners as well. Accordingly, it might have to be propagated to concerned partners in a transitive way. A fundamental challenge in this context is to find ways of propagating the changes in a decentralized manner. Existing approaches are limited with respect to the change operations considered as well as their dependency on a particular process specification language. This paper presents a generic change propagation approach that is based on the Refined Process Structure Tree, i.e., the approach is independent of a specific process specification language. Further, it considers a comprehensive set of change patterns. For all these change patterns, it is shown that the provided change propagation algorithms preserve consistency and compatibility of the process choreography. Finally, a proof-of-concept prototype of a change propagation framework for process choreographies is presented. Overall, comprehensive change support in process choreographies will foster the implementation and operational support of agile collaborative process scenarios.

5 December 2019 in Sensors

Journal Article

Anomaly Detections for Manufacturing Systems Based on Sensor Data—Insights into Two Challenging Real-World Production Settings

To build, run, and maintain reliable manufacturing machines, the condition of their components has to be continuously monitored. When following a fine-grained monitoring of these machines, challenges emerge pertaining to the (1) feeding procedure of large amounts of sensor data to downstream processing components and the (2) meaningful analysis of the produced data. Regarding the latter aspect, manifold purposes are addressed by practitioners and researchers. Two analyses of real-world datasets that were generated in production settings are discussed in this paper. More specifically, the analyses had the goals (1) to detect sensor data anomalies for further analyses of a pharma packaging scenario and (2) to predict unfavorable temperature values of a 3D printing machine environment. Based on the results of the analyses, it will be shown that a proper management of machines and their components in industrial manufacturing environments can be efficiently supported by the detection of anomalies. The latter shall help to support the technical evangelists of the production companies more properly.

6 September 2012 in Requirements Engineering

Journal Article

Time patterns for process-aware information systems

Andreas Lanz

Barbara Weber

Manfred Reichert

About Me

Prof. Dr. Manfred Reichert completed his studies in business mathematics with honors at the University of Ulm and then received his doctorate in computer science on the subject of dynamic process changes in workflow management systems (with Summa Cum Laude) and was awarded the doctoral prize from Ulm University. From 2005 to 2007, he worked as an associate professor at the Chair of Information Systems at the University of Twente in the Netherlands. In Twente, he was also responsible for the strategic research areas of E-Health and Applied Science of Services for Information Society Technologies. He was also a member of the board of the Center for Telematics and Information Technology (CTIT). In January 2008, he was appointed as a university professor at the Institute for Databases and Information Systems (DBIS) at the University of Ulm. From January 2011 to October 2013, he was chairman of the examination committee for the bachelor’s and master’s degree programs in computer science, media informatics, and software engineering. Since October 2014, he has been the director of DBIS and at the same time the dean of studies in the computer science department at the Faculty of Engineering and Computer Science. He was co-opted into the Faculty of Mathematics and Economics in July 2015. His research focuses on the development of innovative technologies for business process management, mobile processes and services and knowledge-intensive processes (e-health, vehicle development).

Prof. Manfred Reichert

Prof. Manfred Reichert

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